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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
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App and account limits
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API-specific limits
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Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
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Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app...
|
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Refer to each associated guide for more information.","depth":11,"bounds":{"left":0.59258646,"top":0.34796488,"width":0.2165891,"height":0.029928172},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Associations API","depth":12,"bounds":{"left":0.601895,"top":0.3942538,"width":0.035904255,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Associations API","depth":13,"bounds":{"left":0.601895,"top":0.3942538,"width":0.035904255,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"CRM Search API","depth":12,"bounds":{"left":0.601895,"top":0.41580206,"width":0.034408245,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"CRM Search API","depth":13,"bounds":{"left":0.601895,"top":0.41580206,"width":0.034408245,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"GraphQL API","depth":12,"bounds":{"left":0.601895,"top":0.43774942,"width":0.028424202,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"GraphQL API","depth":13,"bounds":{"left":0.601895,"top":0.43774942,"width":0.028424202,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Publicly distributed OAuth app limits","depth":9,"bounds":{"left":0.57629657,"top":0.49082202,"width":0.25531915,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"bounds":{"left":0.56299865,"top":0.49082202,"width":0.013297873,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.56266624,"top":0.4924182,"width":0.0004986702,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Publicly distributed OAuth app limits","depth":11,"bounds":{"left":0.57629657,"top":0.49201915,"width":0.116855055,"height":0.019952115},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For","depth":10,"bounds":{"left":0.57629657,"top":0.52593774,"width":0.009640957,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"legacy public apps","depth":10,"bounds":{"left":0.5859375,"top":0.5263368,"width":0.04737367,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"legacy public apps","depth":11,"bounds":{"left":0.5859375,"top":0.5263368,"width":0.04737367,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", and apps on the latest versions of the developer platform (2025.2 and 2026.03) using","depth":10,"bounds":{"left":0.57629657,"top":0.52593774,"width":0.23420878,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth authentication","depth":10,"bounds":{"left":0.6140292,"top":0.54868317,"width":0.053856384,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth authentication","depth":11,"bounds":{"left":0.6140292,"top":0.54868317,"width":0.053856384,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"distributed","depth":10,"bounds":{"left":0.6693817,"top":0.54868317,"width":0.027925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"distributed","depth":11,"bounds":{"left":0.6693817,"top":0.54868317,"width":0.027925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the","depth":10,"bounds":{"left":0.57629657,"top":0.5482841,"width":0.23454122,"height":0.038707104},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"CRM Search API","depth":10,"bounds":{"left":0.57629657,"top":0.5714286,"width":0.24019282,"height":0.03790902},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"CRM Search API","depth":11,"bounds":{"left":0.57629657,"top":0.5714286,"width":0.24019282,"height":0.03790902},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":10,"bounds":{"left":0.6028923,"top":0.5933759,"width":0.0011635638,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":11,"bounds":{"left":0.59258646,"top":0.6432562,"width":0.008976064,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"API limit increase add-on","depth":11,"bounds":{"left":0.6015625,"top":0.64365524,"width":0.05501995,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"API limit increase add-on","depth":12,"bounds":{"left":0.6015625,"top":0.64365524,"width":0.05501995,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"does","depth":11,"bounds":{"left":0.6565825,"top":0.6432562,"width":0.013131649,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"not","depth":11,"bounds":{"left":0.6697141,"top":0.6432562,"width":0.00731383,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"increase the limits of","depth":11,"bounds":{"left":0.67702794,"top":0.6432562,"width":0.048038565,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"legacy public apps","depth":11,"bounds":{"left":0.7250665,"top":0.64365524,"width":0.04138963,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"legacy public apps","depth":12,"bounds":{"left":0.7250665,"top":0.64365524,"width":0.04138963,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using","depth":11,"bounds":{"left":0.59258646,"top":0.6432562,"width":0.22323804,"height":0.030327214},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth authentication","depth":11,"bounds":{"left":0.72888964,"top":0.66001594,"width":0.04720745,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth authentication","depth":12,"bounds":{"left":0.72888964,"top":0.66001594,"width":0.04720745,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"that are","depth":11,"bounds":{"left":0.77609706,"top":0.65961695,"width":0.020113032,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"distributed","depth":11,"bounds":{"left":0.7962101,"top":0.66001594,"width":0.024268618,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"distributed","depth":12,"bounds":{"left":0.7962101,"top":0.66001594,"width":0.024268618,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"via the HubSpot marketplace.","depth":11,"bounds":{"left":0.59258646,"top":0.6755786,"width":0.0653258,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Privately distributed app limits","depth":9,"bounds":{"left":0.57629657,"top":0.7234637,"width":0.25531915,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"bounds":{"left":0.56299865,"top":0.7234637,"width":0.013297873,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.56266624,"top":0.72505987,"width":0.0004986702,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Privately distributed app limits","depth":11,"bounds":{"left":0.57629657,"top":0.7246608,"width":0.09840426,"height":0.019952115},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The limits in the table below apply to","depth":10,"bounds":{"left":0.57629657,"top":0.75857943,"width":0.0930851,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"legacy private apps","depth":10,"bounds":{"left":0.6693817,"top":0.7589784,"width":0.049867023,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"legacy private apps","depth":11,"bounds":{"left":0.6693817,"top":0.7589784,"width":0.049867023,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a","depth":10,"bounds":{"left":0.57629657,"top":0.75857943,"width":0.25465426,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"distribution","depth":10,"bounds":{"left":0.69581115,"top":0.7813248,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"distribution","depth":11,"bounds":{"left":0.69581115,"top":0.7813248,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"set to","depth":10,"bounds":{"left":0.7250665,"top":0.78092575,"width":0.017287234,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private","depth":11,"bounds":{"left":0.7450133,"top":0.7821229,"width":0.019448139,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". Note that for these privately distributed app types:","depth":10,"bounds":{"left":0.57629657,"top":0.78092575,"width":0.24135639,"height":0.038707104},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The burst limit, detailed in the","depth":11,"bounds":{"left":0.58693486,"top":0.84197927,"width":0.075465426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per 10 seconds","depth":12,"bounds":{"left":0.66240025,"top":0.84197927,"width":0.037400264,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"column below, applies individually per app.","depth":11,"bounds":{"left":0.69980055,"top":0.84197927,"width":0.10887633,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The daily limit, detailed in the","depth":11,"bounds":{"left":0.58693486,"top":0.8707103,"width":0.074634306,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per day","depth":12,"bounds":{"left":0.6615692,"top":0.8707103,"width":0.019281914,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"column below, is shared across all apps within the same HubSpot account.","depth":11,"bounds":{"left":0.58693486,"top":0.8707103,"width":0.23487367,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Product Tier","depth":15,"bounds":{"left":0.6381317,"top":0.9417398,"width":0.028091755,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per 10 Seconds","depth":15,"bounds":{"left":0.6953125,"top":0.9417398,"width":0.034906916,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per Day","depth":15,"bounds":{"left":0.74517953,"top":0.9417398,"width":0.018118352,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Privately distributed apps","depth":14,"bounds":{"left":0.57629657,"top":0.97126895,"width":0.05618351,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"bounds":{"left":0.6381317,"top":0.97126895,"width":0.022107713,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Free and Starter","depth":14,"bounds":{"left":0.6381317,"top":0.98723066,"width":0.036070477,"height":0.0127693415},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100 / app","depth":14,"bounds":{"left":0.6953125,"top":0.97126895,"width":0.021775266,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"250,000 / account","depth":14,"bounds":{"left":0.74517953,"top":0.97126895,"width":0.040724736,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"bounds":{"left":0.6381317,"top":1.0,"width":0.022107713,"height":-0.016759753},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Professional","depth":14,"bounds":{"left":0.6381317,"top":1.0,"width":0.026761968,"height":-0.03272152},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"190 / app","depth":14,"bounds":{"left":0.6953125,"top":1.0,"width":0.02144282,"height":-0.016759753},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"625,000 / account","depth":14,"bounds":{"left":0.74517953,"top":1.0,"width":0.04055851,"height":-0.016759753},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"bounds":{"left":0.6381317,"top":1.0,"width":0.022107713,"height":-0.062250614},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enterprise","depth":14,"bounds":{"left":0.6381317,"top":1.0,"width":0.022273935,"height":-0.07821226},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"190 / app","depth":14,"bounds":{"left":0.6953125,"top":1.0,"width":0.02144282,"height":-0.062250614},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Associate records - HubSpot docs
Associate records - HubSpot docs
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Associate records
API Guide
API Guide
POST Report high usage
POST
Report high usage
PUT Associate records (labeled)
PUT
Associate records (labeled)
PUT Associate records (default)
PUT
Associate records (default)
DEL Remove association between records
DEL
Remove association between records
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On this page
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Associate records
Associate records
Associate records without a label
Associate records without a label
Associate records with a label
Associate records with a label
Retrieve associated records
Retrieve associated records
Update record association labels
Update record association labels
Remove record associations
Remove record associations
Remove all associations between records
Remove all associations between records
Remove associations with specific labels
Remove associations with specific labels
Report on high association usage
Report on high association usage
Limits
Limits
Association type ID values
Association type ID values
Company to object
Company to object
Contact to object
Contact to object
Deal to object
Deal to object
Ticket to object
Ticket to object
Lead to object
Lead to object
Appointment to object
Appointment to object
Goal to object
Goal to object
Course to object
Course to object
Listing to object
Listing to object
Service to object
Service to object
Call to object
Call to object
Email to object
Email to object
Feedback submission to object
Feedback submission to object
Meeting to object
Meeting to object
Note to object
Note to object
Postal mail to object
Postal mail to object
Task to object
Task to object
Communication (SMS, WhatsApp, or LinkedIn message) to object
Communication (SMS, WhatsApp, or LinkedIn message) to object
Invoice to object
Invoice to object
Payment to object
Payment to object
Payment link to object
Payment link to object
Quote to object
Quote to object
Line item to object
Line item to object
Order to object
Order to object
Cart to object
Cart to object
Discount to object
Discount to object
Fee to object
Fee to object
Subscription to object
Subscription to object
Tax to object
Tax to object
Project to object
Project to object
v1 associations (legacy)
v1 associations (legacy)
Associate records
Associate records
Associate records
Use the associations API to create, manage, and remove associations between CRM records.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
For the previous version, please see the documentation for the
v3 Associations API
v3 Associations API
.
Scope requirements
Scope requirements
Associations represent the relationships between objects and activities in the HubSpot CRM. Record associations can exist between records of different objects (e.g., Contact to Company), as well as within the same object (e.g., Company to Company).
The Associations API includes two sets of endpoints:
Association details endpoints
: create, edit, and remove associations between records. In this article, you’ll learn more about using the associations details endpoints.
Association schema endpoints
Association schema endpoints
: view your account’s association definitions (also known as types), create and manage custom association labels, and set limits for associations. Learn more about using the
associations schema endpoints
associations schema endpoints
.
Learn more about objects, records, properties, and associations APIs in the
Understanding the CRM
Understanding the CRM
guide.
Navigate to header Associate records
Navigate to header
Associate records
You can associate records with each other unlabeled (i.e. contact and company associated with no descriptor) or with labels (e.g., contact and company associated and the contact is the company’s
Decision maker
).
The number of associations a record can have depends on
the object and your HubSpot subscription.
the object and your HubSpot subscription.
Navigate to header Associate records without a label
Navigate to header
Associate records without a label
You can create a default unlabeled association between two records, or set up unlabeled associations for records in bulk. To set up an individual default association between two records, make a
PUT
request to
/crm/objects/2026-03/{fromObjectType}/{fromObjectId}/associations/default/{toObjectType}/{toObjectId}
In the request URL, include:
fromObjectType
:
the ID of the object you’re associating. To find the ID values, refer to this
list of object type IDs,
list of object type IDs,
or for contacts, companies, deals, tickets, and notes, you can use the object name (e.g.,
contact
,
company
).
fromObjectId
:
the ID of the record to associate.
toObjectType
:
the ID of the object you’re associating the record to. To find the ID values, refer to this
list of object type IDs,
list of object type IDs,
or for contacts, companies, deals, tickets, and notes, you can use the object name (e.g.,
contact
,
company
).
toObjectId
:
the ID of the record to associate to.
For example, to associate a contact record whose ID is
12345
with a company record whose ID is
67891
, your request URL would be:
/crm/objects/2026-03/contact/12345/associations/default/company/67891
.
To associate records without a label in bulk, make a
POST
request to
/crm/associations/2026-03/{fromObjectType}/{toObjectType}/batch/associate/default
. In the request body, include
objectId
values for the records you want to associate. For example:
Report incorrect code...
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Learn more about using the","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"associations schema endpoints","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"associations schema endpoints","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Learn more about objects, records, properties, and associations APIs in the","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Understanding the CRM","depth":10,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Understanding the CRM","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"guide.","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Associate records","depth":9,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Associate records","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can associate records with each other unlabeled (i.e. contact and company associated with no descriptor) or with labels (e.g., contact and company associated and the contact is the company’s","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Decision maker","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of associations a record can have depends on","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"the object and your HubSpot subscription.","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"the object and your HubSpot subscription.","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Associate records without a label","depth":9,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Associate records without a label","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You can create a default unlabeled association between two records, or set up unlabeled associations for records in bulk. 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To find the ID values, refer to this","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"list of object type IDs,","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"list of object type IDs,","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"or for contacts, companies, deals, tickets, and notes, you can use the object name (e.g.,","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"contact","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"company","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fromObjectId","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the ID of the record to associate.","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"toObjectType","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"the ID of the object you’re associating the record to. 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In the request body, include","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"objectId","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"values for the records you want to associate. For example:","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
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JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Associate records - HubSpot docs
Associate records - HubSpot docs
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Associate records
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POST Report high usage
POST
Report high usage
PUT Associate records (labeled)
PUT
Associate records (labeled)
PUT Associate records (default)
PUT
Associate records (default)
DEL Remove association between records
DEL
Remove association between records
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Associations schema
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Exports
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Associate records
Associate records
Associate records without a label
Associate records without a label
Associate records with a label
Associate records with a label
Retrieve associated records
Retrieve associated records
Update record association labels
Update record association labels
Remove record associations
Remove record associations
Remove all associations between records
Remove all associations between records
Remove associations with specific labels
Remove associations with specific labels
Report on high association usage
Report on high association usage
Limits
Limits
Association type ID values
Association type ID values
Company to object
Company to object
Contact to object
Contact to object
Deal to object
Deal to object
Ticket to object
Ticket to object
Lead to object
Lead to object
Appointment to object
Appointment to object
Goal to object
Goal to object
Course to object
Course to object
Listing to object
Listing to object
Service to object
Service to object
Call to object
Call to object
Email to object
Email to object
Feedback submission to object
Feedback submission to object
Meeting to object
Meeting to object
Note to object
Note to object
Postal mail to object
Postal mail to object
Task to object
Task to object
Communication (SMS, WhatsApp, or LinkedIn message) to object
Communication (SMS, WhatsApp, or LinkedIn message) to object
Invoice to object
Invoice to object
Payment to object
Payment to object
Payment link to object
Payment link to object
Quote to object
Quote to object
Line item to object
Line item to object
Order to object
Order to object
Cart to object
Cart to object
Discount to object
Discount to object
Fee to object
Fee to object
Subscription to object
Subscription to object
Tax to object
Tax to object
Project to object
Project to object
v1 associations (legacy)
v1 associations (legacy)
Associate records
Associate records
Associate records
Use the associations API to create, manage, and remove associations between CRM records.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
For the previous version, please see the documentation for the
v3 Associations API
v3 Associations API
.
Scope requirements
Scope requirements
Associations represent the relationships between objects and activities in the HubSpot CRM. Record associations can exist between records of different objects (e.g., Contact to Company), as well as within the same object (e.g., Company to Company).
The Associations API includes two sets of endpoints:
Association details endpoints
: create, edit, and remove associations between records. In this article, you’ll learn more about using the associations details endpoints.
Association schema endpoints
Association schema endpoints
: view your account’s association definitions (also known as types), create and manage custom association labels, and set limits for associations. Learn more about using the
associations schema endpoints
associations schema endpoints
.
Learn more about objects, records, properties, and associations APIs in the
Understanding the CRM
Understanding the CRM
guide.
Navigate to header Associate records
Navigate to header
Associate records
You can associate records with each other unlabeled (i.e. contact and company associated with no descriptor) or with labels (e.g., contact and company associated and the contact is the company’s
Decision maker
).
The number of associations a record can have depends on
the object and your HubSpot subscription.
the object and your HubSpot subscription.
Navigate to header Associate records without a label
Navigate to header
Associate records without a label
You can create a default unlabeled association between two records, or set up unlabeled associations for records in bulk. To set up an individual default association between two records, make a
PUT
request to
/crm/objects/2026-03/{fromObjectType}/{fromObjectId}/associations/default/{toObjectType}/{toObjectId}
In the request URL, include:
fromObjectType
:
the ID of the object you’re associating. To find the ID values, refer to this
list of object type IDs,
list of object type IDs,
or for contacts, companies, deals, tickets, and notes, you can use the object name (e.g.,
contact
,
company
).
fromObjectId
:
the ID of the record to associate.
toObjectType
:
the ID of the object you’re associating the record to. To find the ID values, refer to this
list of object type IDs,
list of object type IDs,
or for contacts, companies, deals, tickets, and notes, you can use the object name (e.g.,
contact
,
company
).
toObjectId
:
the ID of the record to associate to.
For example, to associate a contact record whose ID is
12345
with a company record whose ID is
67891
, your request URL would be:
/crm/objects/2026-03/contact/12345/associations/default/company/67891
.
To associate records without a label in bulk, make a
POST
request to
/crm/associations/2026-03/{fromObjectType}/{toObjectType}/batch/associate/default
. In the request body, include
objectId
values for the records you want to associate. For example:
Report incorrect code...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
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Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
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Userpilot | Ask Jiminny Report Generated
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JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Associate records - HubSpot docs
Associate records - HubSpot docs
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API Guide
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POST Report high usage
POST
Report high usage
PUT Associate records (labeled)
PUT
Associate records (labeled)
PUT Associate records (default)
PUT
Associate records (default)
DEL Remove association between records
DEL
Remove association between records
Toggle Batch section
Batch
Toggle Associations schema section
Associations schema
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Extensions
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Define events
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Retrieve events
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Send event data
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Associate records - HubSpot docs
Associate records - HubSpot docs
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POST Report high usage
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Company to object...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps...
|
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps...
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Search the CRM - HubSpot docs — Work
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,...
|
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engagements","depth":13,"bounds":{"left":0.8528923,"top":0.23024741,"width":0.062832445,"height":0.03312051},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Objects","depth":12,"bounds":{"left":0.8528923,"top":0.26895452,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Objects","depth":13,"bounds":{"left":0.85821146,"top":0.27494013,"width":0.01662234,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Engagements","depth":12,"bounds":{"left":0.8528923,"top":0.29449323,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Engagements","depth":13,"bounds":{"left":0.85821146,"top":0.30047885,"width":0.03025266,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Search default searchable properties","depth":12,"bounds":{"left":0.8528923,"top":0.3200319,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Search default searchable properties","depth":13,"bounds":{"left":0.8528923,"top":0.32601756,"width":0.080784574,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Filter search results","depth":12,"bounds":{"left":0.8528923,"top":0.34557062,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Filter search results","depth":13,"bounds":{"left":0.8528923,"top":0.35155627,"width":0.042386968,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Search through associations","depth":12,"bounds":{"left":0.8528923,"top":0.37110934,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Search through associations","depth":13,"bounds":{"left":0.8528923,"top":0.37709498,"width":0.06216755,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Sort search results","depth":12,"bounds":{"left":0.8528923,"top":0.39664805,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Sort search results","depth":13,"bounds":{"left":0.8528923,"top":0.40263367,"width":0.04055851,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Paging through results","depth":12,"bounds":{"left":0.8528923,"top":0.42218676,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Paging through results","depth":13,"bounds":{"left":0.8528923,"top":0.42817238,"width":0.04936835,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Limits","depth":12,"bounds":{"left":0.8528923,"top":0.44772545,"width":0.082446806,"height":0.025538707},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Limits","depth":13,"bounds":{"left":0.8528923,"top":0.4537111,"width":0.013297873,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Search the CRM","depth":9,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search the CRM","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The CRM search endpoints make getting data more efficient by allowing developers to filter, sort, and search across any CRM object type.","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Documentation Index","depth":10,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Documentation Index","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Fetch the complete documentation index at:","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/llms.txt","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/llms.txt","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use this file to discover all available pages before exploring further.","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use the CRM search endpoints to filter, sort, and search objects, records, and engagements across your CRM. For example, use the endpoints to get a list of contacts in your account, or a list of all open deals. To use these endpoints from an app, a CRM scope is required. Refer to this","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"list of available scopes","depth":10,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"list of available scopes","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to learn which granular CRM scopes can be used to accomplish your goal.","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Make a search request","depth":9,"on_screen":false,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Make a search request","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"To search your CRM, make a","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"POST","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"request to the object’s search endpoint. CRM search endpoints are constructed using the following format:","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"/crm/objects/2026-03/{object}/search","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". In the request body, you’ll include","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"filters","depth":10,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"filters","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to narrow your search by CRM property values. For example, the code snippet below would retrieve a list of all contacts that have a specific company email address.","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy the contents from the code block","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Ask AI","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"filterGroups\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"filters\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"propertyName\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"email\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"operator\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"CONTAINS_TOKEN\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"value\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"*@hubspot.com\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Each object that you search will include a set of","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"default properties","depth":10,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"default properties","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"that gets returned. For contacts, a search will return","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"createdate","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"email","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"firstname","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hs_object_id","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"lastmodifieddate","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", and","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"lastname","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". For example, the above request would return the following response:","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy the contents from the code block","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Ask AI","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"total\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"results\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"100451\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"properties\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": {","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-01-17T19:55:04.281Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"email\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"testperson@hubspot.com\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"firstname\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Test\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"100451\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
3470595331823119664
|
-1523914635266527280
|
visual_change
|
accessibility
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
2470
|
106
|
13
|
2026-05-07T11:21:01.873295+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152861873_m2.jpg...
|
Firefox
|
Search the CRM - HubSpot docs — Work
|
True
|
developers.hubspot.com/docs/api-reference/latest/c developers.hubspot.com/docs/api-reference/latest/crm/search-the-crm#limits...
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Search the CRM - HubSpot docs
Search the CRM - HubSpot docs
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Make a search request
Make a search request
Searchable CRM objects and engagements
Searchable CRM objects and engagements
Objects
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Engagements
Search default searchable properties
Search default searchable properties
Filter search results
Filter search results
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Limits
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CRM
Search the CRM
Search the CRM
The CRM search endpoints make getting data more efficient by allowing developers to filter, sort, and search across any CRM object type.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Use the CRM search endpoints to filter, sort, and search objects, records, and engagements across your CRM. For example, use the endpoints to get a list of contacts in your account, or a list of all open deals. To use these endpoints from an app, a CRM scope is required. Refer to this
list of available scopes
list of available scopes
to learn which granular CRM scopes can be used to accomplish your goal.
Navigate to header Make a search request
Navigate to header
Make a search request
To search your CRM, make a
POST...
|
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Search the CRM - HubSpot docs
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Search the CRM
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The CRM search endpoints make getting data more efficient by allowing developers to filter, sort, and search across any CRM object type.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Use the CRM search endpoints to filter, sort, and search objects, records, and engagements across your CRM. For example, use the endpoints to get a list of contacts in your account, or a list of all open deals. To use these endpoints from an app, a CRM scope is required. Refer to this
list of available scopes
list of available scopes
to learn which granular CRM scopes can be used to accomplish your goal.
Navigate to header Make a search request
Navigate to header
Make a search request
To search your CRM, make a
POST...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
Search the CRM - HubSpot docs
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
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Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
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JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
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Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
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Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
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Userpilot | Ask Jiminny Report Generated
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JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
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API usage guidelines and limits - HubSpot docs
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Authentication and security
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Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
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Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
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API-specific limits
API-specific limits
Timeline event limits
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Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
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Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Privately distributed apps
Privately distributed apps with
API Limit Increase
API Limit Increase
Product Tier
(Any Hub)
Free and Starter
(Any Hub)
Professional
(Any Hub)
Enterprise
(Any Hub)
Free, Starter, Professional, and Enterprise
Per 10 Seconds
100 / app
190 / app
190 / app
250 / app
Per Day
250,000 / account
625,000 / account
1,000,000 / account
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Navigate to header Exemptions
Navigate to header
Exemptions
Some APIs are exempt from the 10-second and daily limits (e.g., certain
marketing single send API
marketing single send API
and
source code API
source code API
endpoints). However, you should note the following for the exempt APIs:
API requests that are exempt from daily or secondary limits will
not
be logged in HubSpot. If you want to store these exempted requests, you’ll need to log these requests externally.
A high number of requests may result in
5xx
errors. These can be addressed the same as you would
429 errors
429
errors
.
Navigate to header App and account limits
Navigate to header
App and account limits
The following limits apply for creating legacy apps, webhook subscriptions, and CRM extension settings.
You can create up to 100
legacy public apps
legacy public apps
per developer account.
You can create up to 20
legacy private apps
legacy private apps
per HubSpot account.
You can create up to 1,000
webhook subscriptions
webhook subscriptions
per app.
You can create up to 25 CRM extension settings per
legacy public app
legacy public app
.
Navigate to header API-specific limits
Navigate to header
API-specific limits
Some features and APIs have more limits that are listed below. Additional limis for each API can also be found on an API’s associated guide (e.g., the
exports API
exports API
).
Navigate to header Timeline event limits
Navigate to header
Timeline event limits
Timeline events
Timeline events
in a legacy public app are subject to the following limits:
You can create up to 750 timeline event types per public app.
You can create up to 500 properties per timeline event type.
Each serialized event instance has the following size limits:
500 bytes for the event instance ID
510 KB per property/token
1 MB in total size for the event instance
Navigate to header Custom event limits
Navigate to header
Custom event limits
Custom events
Custom events
are subject to the following limits:
There is a limit of 500 unique event definitions per account.
There is a limit of 30 million event completions per month.
The send custom event completions endpoint supports up to 1250 requests per second.
The custom event completion batch endpoint supports batches of 500.
Consult the other custom event restrictions in the
API guide
API guide
.
Navigate to header Service limits
Navigate to header
Service limits
Learn more about service limits and pricing on
HubSpot’s Product & Services Catalog
HubSpot’s Product & Services Catalog
.
Navigate to header Rate limit error responses
Navigate to header
Rate limit error responses
Any app or integration exceeding its rate limits will receive a
429
error response for all subsequent API calls. Requests resulting in an error response shouldn’t exceed 5% of your total daily requests. If you plan on listing your app in the
HubSpot Marketplace
HubSpot Marketplace
, it must stay under this 5% limit to be certified.
The
429
response will have the following format:
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{
"status"
:
"error"
,
"message"
:
"You have reached your daily limit."
,
"errorType"
:
"RATE_LIMIT"
,
"correlationId"
:
"c033cdaa-2c40-4a64-ae48-b4cec88dad24"
,
"policyName"
:
"DAILY"
,
"requestId"
:
"3d3e35b7-0dae-4b9f-a6e3-9c230cbcf8dd"
}
The
message
and
policyName
will indicate which limit you hit (either daily or secondly).
The
daily
limit resets at midnight based on your
time zone setting
time zone setting
.
The following table details the rate limit headers included in the response of each API request to HubSpot, subject to the exceptions listed below the table.
Header
Description
X-HubSpot-RateLimit-Daily
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Daily-Remaining
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Interval-Milliseconds
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
X-HubSpot-RateLimit-Max
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
X-HubSpot-RateLimit-Remaining
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
Header
X-HubSpot-RateLimit-Daily
X-HubSpot-RateLimit-Daily-Remaining
X-HubSpot-RateLimit-Interval-Milliseconds
X-HubSpot-RateLimit-Max
X-HubSpot-RateLimit-Remaining
Description
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
The...
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Note that this header is not included in the response to API requests authorized using","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth","depth":14,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The window of time that the","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Max","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"headers apply to.For example, a value of 10000 would be a window of 10 seconds.","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of requests allowed in the window specified in","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".For example, if this header had a value of 100, and the","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"header was 10000, the enforced limit would be 100 requests per 10 seconds.","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of API requests still allowed for the window specified in","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Privately distributed apps
Privately distributed apps with
API Limit Increase
API Limit Increase
Product Tier
(Any Hub)
Free and Starter
(Any Hub)
Professional
(Any Hub)
Enterprise
(Any Hub)
Free, Starter, Professional, and Enterprise
Per 10 Seconds
100 / app
190 / app
190 / app
250 / app
Per Day
250,000 / account
625,000 / account
1,000,000 / account
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Navigate to header Exemptions
Navigate to header
Exemptions
Some APIs are exempt from the 10-second and daily limits (e.g., certain
marketing single send API
marketing single send API
and
source code API
source code API
endpoints). However, you should note the following for the exempt APIs:
API requests that are exempt from daily or secondary limits will
not
be logged in HubSpot. If you want to store these exempted requests, you’ll need to log these requests externally.
A high number of requests may result in
5xx
errors. These can be addressed the same as you would
429 errors
429
errors
.
Navigate to header App and account limits
Navigate to header
App and account limits
The following limits apply for creating legacy apps, webhook subscriptions, and CRM extension settings.
You can create up to 100
legacy public apps
legacy public apps
per developer account.
You can create up to 20
legacy private apps
legacy private apps
per HubSpot account.
You can create up to 1,000
webhook subscriptions
webhook subscriptions
per app.
You can create up to 25 CRM extension settings per
legacy public app
legacy public app
.
Navigate to header API-specific limits
Navigate to header
API-specific limits
Some features and APIs have more limits that are listed below. Additional limis for each API can also be found on an API’s associated guide (e.g., the
exports API
exports API
).
Navigate to header Timeline event limits
Navigate to header
Timeline event limits
Timeline events
Timeline events
in a legacy public app are subject to the following limits:
You can create up to 750 timeline event types per public app.
You can create up to 500 properties per timeline event type.
Each serialized event instance has the following size limits:
500 bytes for the event instance ID
510 KB per property/token
1 MB in total size for the event instance
Navigate to header Custom event limits
Navigate to header
Custom event limits
Custom events
Custom events
are subject to the following limits:
There is a limit of 500 unique event definitions per account.
There is a limit of 30 million event completions per month.
The send custom event completions endpoint supports up to 1250 requests per second.
The custom event completion batch endpoint supports batches of 500.
Consult the other custom event restrictions in the
API guide
API guide
.
Navigate to header Service limits
Navigate to header
Service limits
Learn more about service limits and pricing on
HubSpot’s Product & Services Catalog
HubSpot’s Product & Services Catalog
.
Navigate to header Rate limit error responses
Navigate to header
Rate limit error responses
Any app or integration exceeding its rate limits will receive a
429
error response for all subsequent API calls. Requests resulting in an error response shouldn’t exceed 5% of your total daily requests. If you plan on listing your app in the
HubSpot Marketplace
HubSpot Marketplace
, it must stay under this 5% limit to be certified.
The
429
response will have the following format:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"status"
:
"error"
,
"message"
:
"You have reached your daily limit."
,
"errorType"
:
"RATE_LIMIT"
,
"correlationId"
:
"c033cdaa-2c40-4a64-ae48-b4cec88dad24"
,
"policyName"
:
"DAILY"
,
"requestId"
:
"3d3e35b7-0dae-4b9f-a6e3-9c230cbcf8dd"
}
The
message
and
policyName
will indicate which limit you hit (either daily or secondly).
The
daily
limit resets at midnight based on your
time zone setting
time zone setting
.
The following table details the rate limit headers included in the response of each API request to HubSpot, subject to the exceptions listed below the table.
Header
Description
X-HubSpot-RateLimit-Daily
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Daily-Remaining
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Interval-Milliseconds
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
X-HubSpot-RateLimit-Max
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
X-HubSpot-RateLimit-Remaining
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
Header
X-HubSpot-RateLimit-Daily
X-HubSpot-RateLimit-Daily-Remaining
X-HubSpot-RateLimit-Interval-Milliseconds
X-HubSpot-RateLimit-Max
X-HubSpot-RateLimit-Remaining
Description
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
The...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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On this page
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Privately distributed apps
Privately distributed apps with
API Limit Increase
API Limit Increase
Product Tier
(Any Hub)
Free and Starter
(Any Hub)
Professional
(Any Hub)
Enterprise
(Any Hub)
Free, Starter, Professional, and Enterprise
Per 10 Seconds
100 / app
190 / app
190 / app
250 / app
Per Day
250,000 / account
625,000 / account
1,000,000 / account
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Navigate to header Exemptions
Navigate to header
Exemptions
Some APIs are exempt from the 10-second and daily limits (e.g., certain
marketing single send API
marketing single send API
and
source code API
source code API
endpoints). However, you should note the following for the exempt APIs:
API requests that are exempt from daily or secondary limits will
not
be logged in HubSpot. If you want to store these exempted requests, you’ll need to log these requests externally.
A high number of requests may result in
5xx
errors. These can be addressed the same as you would
429 errors
429
errors
.
Navigate to header App and account limits
Navigate to header
App and account limits
The following limits apply for creating legacy apps, webhook subscriptions, and CRM extension settings.
You can create up to 100
legacy public apps
legacy public apps
per developer account.
You can create up to 20
legacy private apps
legacy private apps
per HubSpot account.
You can create up to 1,000
webhook subscriptions
webhook subscriptions
per app.
You can create up to 25 CRM extension settings per
legacy public app
legacy public app
.
Navigate to header API-specific limits
Navigate to header
API-specific limits
Some features and APIs have more limits that are listed below. Additional limis for each API can also be found on an API’s associated guide (e.g., the
exports API
exports API
).
Navigate to header Timeline event limits
Navigate to header
Timeline event limits
Timeline events
Timeline events
in a legacy public app are subject to the following limits:
You can create up to 750 timeline event types per public app.
You can create up to 500 properties per timeline event type.
Each serialized event instance has the following size limits:
500 bytes for the event instance ID
510 KB per property/token
1 MB in total size for the event instance
Navigate to header Custom event limits
Navigate to header
Custom event limits
Custom events
Custom events
are subject to the following limits:
There is a limit of 500 unique event definitions per account.
There is a limit of 30 million event completions per month.
The send custom event completions endpoint supports up to 1250 requests per second.
The custom event completion batch endpoint supports batches of 500.
Consult the other custom event restrictions in the
API guide
API guide
.
Navigate to header Service limits
Navigate to header
Service limits
Learn more about service limits and pricing on
HubSpot’s Product & Services Catalog
HubSpot’s Product & Services Catalog
.
Navigate to header Rate limit error responses
Navigate to header
Rate limit error responses
Any app or integration exceeding its rate limits will receive a
429
error response for all subsequent API calls. Requests resulting in an error response shouldn’t exceed 5% of your total daily requests. If you plan on listing your app in the
HubSpot Marketplace
HubSpot Marketplace
, it must stay under this 5% limit to be certified.
The
429
response will have the following format:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"status"
:
"error"
,
"message"
:
"You have reached your daily limit."
,
"errorType"
:
"RATE_LIMIT"
,
"correlationId"
:
"c033cdaa-2c40-4a64-ae48-b4cec88dad24"
,
"policyName"
:
"DAILY"
,
"requestId"
:
"3d3e35b7-0dae-4b9f-a6e3-9c230cbcf8dd"
}
The
message
and
policyName
will indicate which limit you hit (either daily or secondly).
The
daily
limit resets at midnight based on your
time zone setting
time zone setting
.
The following table details the rate limit headers included in the response of each API request to HubSpot, subject to the exceptions listed below the table.
Header
Description
X-HubSpot-RateLimit-Daily
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Daily-Remaining
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Interval-Milliseconds
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
X-HubSpot-RateLimit-Max
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
X-HubSpot-RateLimit-Remaining
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
Header
X-HubSpot-RateLimit-Daily
X-HubSpot-RateLimit-Daily-Remaining
X-HubSpot-RateLimit-Interval-Milliseconds
X-HubSpot-RateLimit-Max...
|
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Note that this header is not included in the response to API requests authorized using","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth","depth":14,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Daily-Remaining","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth","depth":14,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The window of time that the","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Max","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"headers apply to.For example, a value of 10000 would be a window of 10 seconds.","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Max","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of requests allowed in the window specified in","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".For example, if this header had a value of 100, and the","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"header was 10000, the enforced limit would be 100 requests per 10 seconds.","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The number of API requests still allowed for the window specified in","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Header","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Daily","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Daily-Remaining","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Interval-Milliseconds","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Max","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
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accessibility
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NULL
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Privately distributed apps
Privately distributed apps with
API Limit Increase
API Limit Increase
Product Tier
(Any Hub)
Free and Starter
(Any Hub)
Professional
(Any Hub)
Enterprise
(Any Hub)
Free, Starter, Professional, and Enterprise
Per 10 Seconds
100 / app
190 / app
190 / app
250 / app
Per Day
250,000 / account
625,000 / account
1,000,000 / account
1,000,000 / account on top of your base subscription, for each limit increase. You can purchase a maximum of two API limit increases.
Navigate to header Exemptions
Navigate to header
Exemptions
Some APIs are exempt from the 10-second and daily limits (e.g., certain
marketing single send API
marketing single send API
and
source code API
source code API
endpoints). However, you should note the following for the exempt APIs:
API requests that are exempt from daily or secondary limits will
not
be logged in HubSpot. If you want to store these exempted requests, you’ll need to log these requests externally.
A high number of requests may result in
5xx
errors. These can be addressed the same as you would
429 errors
429
errors
.
Navigate to header App and account limits
Navigate to header
App and account limits
The following limits apply for creating legacy apps, webhook subscriptions, and CRM extension settings.
You can create up to 100
legacy public apps
legacy public apps
per developer account.
You can create up to 20
legacy private apps
legacy private apps
per HubSpot account.
You can create up to 1,000
webhook subscriptions
webhook subscriptions
per app.
You can create up to 25 CRM extension settings per
legacy public app
legacy public app
.
Navigate to header API-specific limits
Navigate to header
API-specific limits
Some features and APIs have more limits that are listed below. Additional limis for each API can also be found on an API’s associated guide (e.g., the
exports API
exports API
).
Navigate to header Timeline event limits
Navigate to header
Timeline event limits
Timeline events
Timeline events
in a legacy public app are subject to the following limits:
You can create up to 750 timeline event types per public app.
You can create up to 500 properties per timeline event type.
Each serialized event instance has the following size limits:
500 bytes for the event instance ID
510 KB per property/token
1 MB in total size for the event instance
Navigate to header Custom event limits
Navigate to header
Custom event limits
Custom events
Custom events
are subject to the following limits:
There is a limit of 500 unique event definitions per account.
There is a limit of 30 million event completions per month.
The send custom event completions endpoint supports up to 1250 requests per second.
The custom event completion batch endpoint supports batches of 500.
Consult the other custom event restrictions in the
API guide
API guide
.
Navigate to header Service limits
Navigate to header
Service limits
Learn more about service limits and pricing on
HubSpot’s Product & Services Catalog
HubSpot’s Product & Services Catalog
.
Navigate to header Rate limit error responses
Navigate to header
Rate limit error responses
Any app or integration exceeding its rate limits will receive a
429
error response for all subsequent API calls. Requests resulting in an error response shouldn’t exceed 5% of your total daily requests. If you plan on listing your app in the
HubSpot Marketplace
HubSpot Marketplace
, it must stay under this 5% limit to be certified.
The
429
response will have the following format:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"status"
:
"error"
,
"message"
:
"You have reached your daily limit."
,
"errorType"
:
"RATE_LIMIT"
,
"correlationId"
:
"c033cdaa-2c40-4a64-ae48-b4cec88dad24"
,
"policyName"
:
"DAILY"
,
"requestId"
:
"3d3e35b7-0dae-4b9f-a6e3-9c230cbcf8dd"
}
The
message
and
policyName
will indicate which limit you hit (either daily or secondly).
The
daily
limit resets at midnight based on your
time zone setting
time zone setting
.
The following table details the rate limit headers included in the response of each API request to HubSpot, subject to the exceptions listed below the table.
Header
Description
X-HubSpot-RateLimit-Daily
The number of API requests that are allowed per day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Daily-Remaining
The number of API requests still allowed for the current day. Note that this header is not included in the response to API requests authorized using
OAuth
OAuth
.
X-HubSpot-RateLimit-Interval-Milliseconds
The window of time that the
X-HubSpot-RateLimit-Max
and
X-HubSpot-RateLimit-Remaining
headers apply to.For example, a value of 10000 would be a window of 10 seconds.
X-HubSpot-RateLimit-Max
The number of requests allowed in the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.For example, if this header had a value of 100, and the
X-HubSpot-RateLimit-Interval-Milliseconds
header was 10000, the enforced limit would be 100 requests per 10 seconds.
X-HubSpot-RateLimit-Remaining
The number of API requests still allowed for the window specified in
X-HubSpot-RateLimit-Interval-Milliseconds
.
Header
X-HubSpot-RateLimit-Daily
X-HubSpot-RateLimit-Daily-Remaining
X-HubSpot-RateLimit-Interval-Milliseconds
X-HubSpot-RateLimit-Max...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
Close tab
New Tab
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Open Google Gemini (⌃X)
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Open history (⇧⌘H)
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Get Started
Apps
Apps
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Developer Tooling
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Overview
Overview
Platform
Platform
Versioning
Versioning
API usage guidelines
API usage guidelines
APIs by tier
APIs by tier
Breaking change guidelines
Breaking change guidelines
Local development
Local development
Toggle HubSpot CLI section
HubSpot CLI
Build with config profiles
Build with config profiles
Configurable test accounts
Configurable test accounts
Toggle Developer MCP section
Developer MCP
VS Code extension
VS Code extension
Troubleshooting
Troubleshooting
Third-party tools
Third-party tools
Set up GitHub Actions
Set up GitHub Actions
Postman for HubSpot APIs
Postman for HubSpot APIs
SDKs
SDKs
Node
Node
Php
Php
Python
Python
Ruby
Ruby
English
English
Toggle dark mode
close
close
On this page
On this page
Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app...
|
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add-on","depth":12,"bounds":{"left":0.6015625,"top":0.76256984,"width":0.05501995,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"does","depth":11,"bounds":{"left":0.6565825,"top":0.7621708,"width":0.013131649,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"not","depth":11,"bounds":{"left":0.6697141,"top":0.7621708,"width":0.00731383,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"increase the limits of","depth":11,"bounds":{"left":0.67702794,"top":0.7621708,"width":0.048038565,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"legacy public apps","depth":11,"bounds":{"left":0.7250665,"top":0.76256984,"width":0.04138963,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"legacy public apps","depth":12,"bounds":{"left":0.7250665,"top":0.76256984,"width":0.04138963,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using","depth":11,"bounds":{"left":0.59258646,"top":0.7621708,"width":0.22323804,"height":0.030327214},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"OAuth authentication","depth":11,"bounds":{"left":0.72888964,"top":0.77893054,"width":0.04720745,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"OAuth authentication","depth":12,"bounds":{"left":0.72888964,"top":0.77893054,"width":0.04720745,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"that are","depth":11,"bounds":{"left":0.77609706,"top":0.77853155,"width":0.020113032,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"distributed","depth":11,"bounds":{"left":0.7962101,"top":0.77893054,"width":0.024268618,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"distributed","depth":12,"bounds":{"left":0.7962101,"top":0.77893054,"width":0.024268618,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"via the HubSpot marketplace.","depth":11,"bounds":{"left":0.59258646,"top":0.7944932,"width":0.0653258,"height":0.01396648},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Navigate to header Privately distributed app limits","depth":9,"bounds":{"left":0.57629657,"top":0.8423783,"width":0.25531915,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXLink","text":"Navigate to header","depth":11,"bounds":{"left":0.56299865,"top":0.8423783,"width":0.013297873,"height":0.022346368},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"","depth":12,"bounds":{"left":0.56266624,"top":0.8439745,"width":0.0004986702,"height":0.01915403},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Privately distributed app limits","depth":11,"bounds":{"left":0.57629657,"top":0.8435754,"width":0.09840426,"height":0.019952115},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The limits in the table below apply to","depth":10,"bounds":{"left":0.57629657,"top":0.87749404,"width":0.0930851,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"legacy private apps","depth":10,"bounds":{"left":0.6693817,"top":0.87789303,"width":0.049867023,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"legacy private apps","depth":11,"bounds":{"left":0.6693817,"top":0.87789303,"width":0.049867023,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a","depth":10,"bounds":{"left":0.57629657,"top":0.87749404,"width":0.25465426,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"distribution","depth":10,"bounds":{"left":0.69581115,"top":0.9002394,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"distribution","depth":11,"bounds":{"left":0.69581115,"top":0.9002394,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"set to","depth":10,"bounds":{"left":0.7250665,"top":0.89984035,"width":0.017287234,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"private","depth":11,"bounds":{"left":0.7450133,"top":0.9010375,"width":0.019448139,"height":0.015163607},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". Note that for these privately distributed app types:","depth":10,"bounds":{"left":0.57629657,"top":0.89984035,"width":0.24135639,"height":0.038707104},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The burst limit, detailed in the","depth":11,"bounds":{"left":0.58693486,"top":0.96089387,"width":0.075465426,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per 10 seconds","depth":12,"bounds":{"left":0.66240025,"top":0.96089387,"width":0.037400264,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"column below, applies individually per app.","depth":11,"bounds":{"left":0.69980055,"top":0.96089387,"width":0.10887633,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The daily limit, detailed in the","depth":11,"bounds":{"left":0.58693486,"top":0.9896249,"width":0.074634306,"height":0.0103750825},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per day","depth":12,"bounds":{"left":0.6615692,"top":0.9896249,"width":0.019281914,"height":0.0103750825},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"column below, is shared across all apps within the same HubSpot account.","depth":11,"bounds":{"left":0.58693486,"top":0.9896249,"width":0.23487367,"height":0.0103750825},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Product Tier","depth":15,"bounds":{"left":0.6381317,"top":1.0,"width":0.028091755,"height":-0.0606544},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per 10 Seconds","depth":15,"bounds":{"left":0.6953125,"top":1.0,"width":0.034906916,"height":-0.0606544},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Per Day","depth":15,"bounds":{"left":0.74517953,"top":1.0,"width":0.018118352,"height":-0.0606544},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Privately distributed apps","depth":14,"bounds":{"left":0.57629657,"top":1.0,"width":0.05618351,"height":-0.090183616},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"bounds":{"left":0.6381317,"top":1.0,"width":0.022107713,"height":-0.090183616},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Free and Starter","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"100 / app","depth":14,"bounds":{"left":0.6953125,"top":1.0,"width":0.021775266,"height":-0.090183616},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"250,000 / account","depth":14,"bounds":{"left":0.74517953,"top":1.0,"width":0.040724736,"height":-0.090183616},"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Professional","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"190 / app","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"625,000 / account","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enterprise","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"190 / app","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1,000,000 / account","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Privately distributed apps with","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"API Limit Increase","depth":14,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"API Limit Increase","depth":15,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"(Any Hub)","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Free, Starter, Professional, and Enterprise","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"250 / app","depth":14,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
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Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Authentication and security
Authentication and security
Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API
GraphQL API
GraphQL API
Navigate to header Publicly distributed OAuth app limits
Navigate to header
Publicly distributed OAuth app limits
For
legacy public apps
legacy public apps
, and apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
distributed
distributed
via the HubSpot marketplace, each HubSpot account that installs your app is limited to 110 requests every 10 seconds. This excludes the
CRM Search API
CRM Search API
.
The
API limit increase add-on
API limit increase add-on
does
not
increase the limits of
legacy public apps
legacy public apps
nor apps on the latest versions of the developer platform (2025.2 and 2026.03) using
OAuth authentication
OAuth authentication
that are
distributed
distributed
via the HubSpot marketplace.
Navigate to header Privately distributed app limits
Navigate to header
Privately distributed app limits
The limits in the table below apply to
legacy private apps
legacy private apps
, as well as apps on the latest versions of the developer platform (2025.2 and 2026.03) with a
distribution
distribution
set to
private
. Note that for these privately distributed app types:
The burst limit, detailed in the
Per 10 seconds
column below, applies individually per app.
The daily limit, detailed in the
Per day
column below, is shared across all apps within the same HubSpot account.
Product Tier
Per 10 Seconds
Per Day
Privately distributed apps
(Any Hub)
Free and Starter
100 / app
250,000 / account
(Any Hub)
Professional
190 / app
625,000 / account
(Any Hub)
Enterprise
190 / app
1,000,000 / account
Privately distributed apps with
API Limit Increase
API Limit Increase
(Any Hub)
Free, Starter, Professional, and Enterprise
250 / app...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Platform
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Breaking change guidelines
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Toggle HubSpot CLI section
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Build with config profiles
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Toggle Developer MCP section
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Authentication and security
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Checking API usage
Checking API usage
Apps built on version 2025.2 and 2026.03 of the developer platform
Apps built on version 2025.2 and 2026.03 of the developer platform
Legacy apps
Legacy apps
Rate limits
Rate limits
Publicly distributed OAuth app limits
Publicly distributed OAuth app limits
Privately distributed app limits
Privately distributed app limits
Exemptions
Exemptions
App and account limits
App and account limits
API-specific limits
API-specific limits
Timeline event limits
Timeline event limits
Custom event limits
Custom event limits
Service limits
Service limits
Rate limit error responses
Rate limit error responses
Address rate limit issues
Address rate limit issues
Use batch APIs and cache results when possible
Use batch APIs and cache results when possible
Use webhooks to get updated data from HubSpot
Use webhooks to get updated data from HubSpot
Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API...
|
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requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the","depth":10,"bounds":{"left":0.57629657,"top":0.37230647,"width":0.2526596,"height":0.03830806},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"exports API","depth":10,"bounds":{"left":0.57629657,"top":0.41739824,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"exports API","depth":11,"bounds":{"left":0.57629657,"top":0.41739824,"width":0.02925532,"height":0.01556265},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":").","depth":10,"bounds":{"left":0.60555184,"top":0.4169992,"width":0.0029920214,"height":0.015961692},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.","depth":11,"bounds":{"left":0.59258646,"top":0.4668795,"width":0.2165891,"height":0.029928172},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Associations API","depth":12,"bounds":{"left":0.601895,"top":0.5131684,"width":0.035904255,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Associations API","depth":13,"bounds":{"left":0.601895,"top":0.5131684,"width":0.035904255,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"CRM Search API","depth":12,"bounds":{"left":0.601895,"top":0.53471667,"width":0.034408245,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"CRM Search API","depth":13,"bounds":{"left":0.601895,"top":0.53471667,"width":0.034408245,"height":0.013567438},"on_screen":true,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
API usage guidelines and limits - HubSpot docs
API usage guidelines and limits - HubSpot docs
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Apps built on version 2025.2 and 2026.03 of the developer platform
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Use batch APIs and cache results when possible
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Platform
API usage guidelines and limits
API usage guidelines and limits
Learn about the different API and developer feature limits in HubSpot.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
HubSpot closely monitors usage of all APIs to ensure a quality experience for every user. All app and integration developers must comply with the
HubSpot Acceptable Use Policy
HubSpot Acceptable Use Policy
and
API Terms
API Terms
. While HubSpot reserves the right to change or deprecate the APIs over time, updates will always be provided in advance through the
Developer Changelog
Developer Changelog
.
Navigate to header Authentication and security
Navigate to header
Authentication and security
For optimal security, all apps must use HubSpot’s
OAuth protocol
OAuth protocol
directly, or use your app’s static auth token if you’re building an
app installed in a single account
app installed in a single account
. Apps are responsible for storing time-to-live (TTL) data and refreshing user access tokens in accordance with this protocol. When an access token is generated, it will include an
expires_in
parameter indicating how long it can be used to make API calls before refreshing.
Unauthorized (401)
requests are not a valid indicator that a new access token must be retrieved.
Navigate to header Checking API usage
Navigate to header
Checking API usage
Navigate to header Apps built on version 2025.2 and 2026.03 of the developer platform
Navigate to header
Apps built on version 2025.2 and 2026.03 of the developer platform
To view API usage for your apps built on the
new developer platform
new developer platform
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
>
API call usage
.
Your API usage across all your apps will be listed at the top of the page. You can also review usage for the apps you built in your specific account, along with any third-party apps you’ve installed.
Navigate to header Legacy apps
Navigate to header
Legacy apps
To view API usage for a legacy
private app
private app
:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Legacy apps
.
Click the
name
of the private app.
On the app details page, click the
Logs
tab.
Review the API calls listed in the table. You can also use the
search bar
,
filters
, and
date pickers
to further refine the displayed API calls.
Learn more about
checking API usage in legacy private apps
checking API usage in legacy private apps
.
To view API usage for a public app using OAuth:
In your HubSpot account, navigate to
Development
in the main navigation bar.
In the left sidebar menu, navigate to
Monitoring
, then select
Logs
.
At the top, select the
name
of the app.
Use the
tabs
to view different types of requests being made to or from the app. While viewing these logs, you can click an
individual request
to view more information.
Learn more about
monitoring API usage for legacy public apps
monitoring API usage for legacy public apps
.
Navigate to header Rate limits
Navigate to header
Rate limits
The number of calls your app can make is based on your account subscription in the account it’s installed in, and whether you’ve purchased the
API limit increase
API limit increase
.
You can keep the following general limits in mind when making requests to HubSpot’s API endpoints, however some APIs may also have more specific limits listed on their relevant API guide (e.g., the
exports API
exports API
).
The following APIs have limits that are unique from or stricter than the general limits. Refer to each associated guide for more information.
Associations API
Associations API
CRM Search API
CRM Search API...
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2479
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106
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19
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2026-05-07T11:22:10.018872+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152930018_m2.jpg...
|
Firefox
|
Search the CRM - HubSpot docs — Work
|
True
|
developers.hubspot.com/docs/api-reference/latest/c developers.hubspot.com/docs/api-reference/latest/crm/search-the-crm...
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monitor_2
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,
"lastmodifieddate"
:
"2024-09-11T13:27:39.356Z"
,
"lastname"
:
"Person"
},
"createdAt"
:
"2024-01-17T19:55:04.281Z"
,
"updatedAt"
:
"2024-09-11T13:27:39.356Z"
,
"archived"
:
false
},
{
"id"
:
"57156923994"
,
"properties"
: {
"createdate"
:
"2024-09-11T18:21:50.012Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Maria"
,
"hs_object_id"
:
"57156923994"
,
"lastmodifieddate"
:
"2024-10-21T21:36:02.961Z"
,
"lastname"
:
"Johnson (Sample Contact)"
},
"createdAt"
:
"2024-09-11T18:21:50.012Z"
,
"updatedAt"
:
"2024-10-21T21:36:02.961Z"
,
"archived"
:
false
}
]
}
To return a specific set of properties, include a
properties
array in the request body. For example:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"filterGroups"
: [
{
"filters"
: [
{
"propertyName"
:
"annualrevenue"
,
"operator"
:
"GT"
,
"value"
:
"10000000"
}
]
}
],
"properties"
: [
"annualrevenue"
,
"name"
]
}
The response for the above request would look like:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
38
,
"results"
: [
{
"id"
:
"2810868468"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2020-01-09T20:11:27.309Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.333Z"
,
"hs_object_id"
:
"2810868468"
,
"name"
:
"Google"
},
"createdAt"
:
"2020-01-09T20:11:27.309Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.333Z"
,
"archived"
:
false
},...
|
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{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-11T18:21:50.012Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"email\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"emailmaria@hubspot.com\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"firstname\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Maria\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"57156923994\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"lastmodifieddate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-10-21T21:36:02.961Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"lastname\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Johnson 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For example:","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy the contents from the code block","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Ask 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|
4726026835847557837
|
-1272135264186433584
|
visual_change
|
accessibility
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,
"lastmodifieddate"
:
"2024-09-11T13:27:39.356Z"
,
"lastname"
:
"Person"
},
"createdAt"
:
"2024-01-17T19:55:04.281Z"
,
"updatedAt"
:
"2024-09-11T13:27:39.356Z"
,
"archived"
:
false
},
{
"id"
:
"57156923994"
,
"properties"
: {
"createdate"
:
"2024-09-11T18:21:50.012Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Maria"
,
"hs_object_id"
:
"57156923994"
,
"lastmodifieddate"
:
"2024-10-21T21:36:02.961Z"
,
"lastname"
:
"Johnson (Sample Contact)"
},
"createdAt"
:
"2024-09-11T18:21:50.012Z"
,
"updatedAt"
:
"2024-10-21T21:36:02.961Z"
,
"archived"
:
false
}
]
}
To return a specific set of properties, include a
properties
array in the request body. For example:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"filterGroups"
: [
{
"filters"
: [
{
"propertyName"
:
"annualrevenue"
,
"operator"
:
"GT"
,
"value"
:
"10000000"
}
]
}
],
"properties"
: [
"annualrevenue"
,
"name"
]
}
The response for the above request would look like:
Report incorrect code
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
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Make a search request
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Searchable CRM objects and engagements
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CRM
Search the CRM
Search the CRM
The CRM search endpoints make getting data more efficient by allowing developers to filter, sort, and search across any CRM object type.
Documentation Index
Documentation Index
Fetch the complete documentation index at:
https://developers.hubspot.com/docs/llms.txt
https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Use the CRM search endpoints to filter, sort, and search objects, records, and engagements across your CRM. For example, use the endpoints to get a list of contacts in your account, or a list of all open deals. To use these endpoints from an app, a CRM scope is required. Refer to this
list of available scopes
list of available scopes
to learn which granular CRM scopes can be used to accomplish your goal.
Navigate to header Make a search request
Navigate to header
Make a search request
To search your CRM, make a
POST
request to the object’s search endpoint. CRM search endpoints are constructed using the following format:
/crm/objects/2026-03/{object}/search
. In the request body, you’ll include
filters...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
Service-Desk - Queues - Platform team - Service space - Jira
Service-Desk - Queues - Platform team - Service space - Jira
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Jy 20807 check various issues with stages by nikolaybiaivanov · Pull Request #12041 · jiminny/app
Sentry
Sentry
Pull requests · jiminny/app
Pull requests · jiminny/app
Userpilot | Ask Jiminny Report Generated
Userpilot | Ask Jiminny Report Generated
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
JY-20773 fix user pilot tracking ofr automated report generated by LakyLak · Pull Request #12024 · jiminny/app
Jiminny
Jiminny
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Fetch the complete documentation index at:
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https://developers.hubspot.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
Use the CRM search endpoints to filter, sort, and search objects, records, and engagements across your CRM. For example, use the endpoints to get a list of contacts in your account, or a list of all open deals. To use these endpoints from an app, a CRM scope is required. Refer to this
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. In the request body, you’ll include
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot...
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reference","depth":19,"bounds":{"left":0.08344415,"top":0.65682364,"width":0.005984043,"height":0.014365523},"on_screen":true,"role_description":"pop-up button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tracking location history from last week","depth":18,"bounds":{"left":0.0043218085,"top":0.6743815,"width":0.08643617,"height":0.011173184},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXPopUpButton","text":"More options for Tracking location history from last week","depth":19,"bounds":{"left":0.08344415,"top":0.6775738,"width":0.005984043,"height":0.007980846},"on_screen":true,"role_description":"pop-up button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXPopUpButton","text":"Lukas Pro","depth":15,"bounds":{"left":0.0043218085,"top":0.6943336,"width":0.037898935,"height":0.01915403},"on_screen":true,"role_description":"pop-up button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Get apps and extensions","depth":15,"bounds":{"left":0.08277926,"top":0.6943336,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"HubSpot rate limit implementation strategy, rename chat","depth":19,"bounds":{"left":0.043218084,"top":0.02793296,"width":0.09773936,"height":0.022346368},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"HubSpot rate limit implementation strategy","depth":21,"bounds":{"left":0.04454787,"top":0.031923383,"width":0.09507979,"height":0.014365523},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.04454787,"top":0.031923383,"width":0.003656915,"height":0.014365523}},{"char_start":1,"char_count":41,"bounds":{"left":0.048204787,"top":0.031923383,"width":0.09142287,"height":0.014365523}}],"role_description":"text"},{"role":"AXPopUpButton","text":"More options for HubSpot rate limit implementation strategy","depth":19,"bounds":{"left":0.14128989,"top":0.02793296,"width":0.0066489363,"height":0.022346368},"on_screen":true,"role_description":"pop-up button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Open sidebar","depth":21,"bounds":{"left":0.47340426,"top":0.026336791,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Share chat","depth":21,"bounds":{"left":0.48537233,"top":0.026336791,"width":0.010638298,"height":0.025538707},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Claude finished the response","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"You said: So just a solution for rate limit implementation.","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: So just a solution for rate limit implementation.","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating activity (engagement, meeting, call, note)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"searching for a company or contact","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating deal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"patching IDs\nReview what the limit is at the moment in the HubSpot documentation and then think of the solution:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). Example of such a error Client error:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST https://api.hubapi.com/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"resulted in a","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"429 Too Many Requests","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"response: {\"status\":\"error\",\"message\":\"You have reached your secondly limit.\",\"errorType\":\"RATE_LIMIT\",\"correlationId\":\"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot...
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152942106_m2.jpg...
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Firefox
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Search the CRM - HubSpot docs — Work
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developers.hubspot.com/docs/api-reference/latest/c developers.hubspot.com/docs/api-reference/latest/crm/search-the-crm#limits...
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,
"lastmodifieddate"
:
"2024-09-11T13:27:39.356Z"
,
"lastname"
:
"Person"
},
"createdAt"
:
"2024-01-17T19:55:04.281Z"
,
"updatedAt"
:
"2024-09-11T13:27:39.356Z"
,
"archived"
:
false
},
{
"id"
:
"57156923994"
,
"properties"
: {
"createdate"
:
"2024-09-11T18:21:50.012Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Maria"
,
"hs_object_id"
:
"57156923994"
,
"lastmodifieddate"
:
"2024-10-21T21:36:02.961Z"
,
"lastname"
:
"Johnson (Sample Contact)"
},
"createdAt"
:
"2024-09-11T18:21:50.012Z"
,
"updatedAt"
:
"2024-10-21T21:36:02.961Z"
,
"archived"
:
false
}
]
}
To return a specific set of properties, include a
properties
array in the request body. For example:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"filterGroups"
: [
{
"filters"
: [
{
"propertyName"
:
"annualrevenue"
,
"operator"
:
"GT"
,
"value"
:
"10000000"
}
]
}
],
"properties"
: [
"annualrevenue"
,
"name"
]
}
The response for the above request would look like:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
38
,
"results"
: [
{
"id"
:
"2810868468"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2020-01-09T20:11:27.309Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.333Z"
,
"hs_object_id"
:
"2810868468"
,
"name"
:
"Google"
},
"createdAt"
:
"2020-01-09T20:11:27.309Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.333Z"
,
"archived"
:
false
},
{
"id"
:
"2823023532"
,
"properties"
: {
"annualrevenue"
:
"10000000000"
,
"createdate"
:
"2020-01-13T16:21:08.270Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"2823023532"
,
"name"
:
"Pepsi"
},
"createdAt"
:
"2020-01-13T16:21:08.270Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.064Z"
,
"archived"
:
false
},
{
"id"
:
"5281147580"
,
"properties"
: {
"annualrevenue"
:
"50000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.332Z"
,
"hs_object_id"
:
"5281147580"
,
"name"
:
"CORKCICLE"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.332Z"
,
"archived"
:
false
},
{
"id"
:
"5281147581"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"5281147581"
,
"name"
:
"Ulta Beauty"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
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{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"annualrevenue\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"10000000000\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2020-01-13T16:21:08.270Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_lastmodifieddate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.064Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2823023532\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"name\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Pepsi\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2020-01-13T16:21:08.270Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"updatedAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.064Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"archived\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"false","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"5281147580\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":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{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"annualrevenue\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"50000000\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.250Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_lastmodifieddate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.332Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"5281147580\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"name\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"CORKCICLE\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.250Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"updatedAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.332Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"archived\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"false","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"5281147581\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen"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{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"annualrevenue\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"1000000000\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.250Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_lastmodifieddate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.064Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"5281147581\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"name\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Ulta Beauty\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.250Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
8034325307381220201
|
-1242932235369480624
|
visual_change
|
accessibility
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,
"lastmodifieddate"
:
"2024-09-11T13:27:39.356Z"
,
"lastname"
:
"Person"
},
"createdAt"
:
"2024-01-17T19:55:04.281Z"
,
"updatedAt"
:
"2024-09-11T13:27:39.356Z"
,
"archived"
:
false
},
{
"id"
:
"57156923994"
,
"properties"
: {
"createdate"
:
"2024-09-11T18:21:50.012Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Maria"
,
"hs_object_id"
:
"57156923994"
,
"lastmodifieddate"
:
"2024-10-21T21:36:02.961Z"
,
"lastname"
:
"Johnson (Sample Contact)"
},
"createdAt"
:
"2024-09-11T18:21:50.012Z"
,
"updatedAt"
:
"2024-10-21T21:36:02.961Z"
,
"archived"
:
false
}
]
}
To return a specific set of properties, include a
properties
array in the request body. For example:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"filterGroups"
: [
{
"filters"
: [
{
"propertyName"
:
"annualrevenue"
,
"operator"
:
"GT"
,
"value"
:
"10000000"
}
]
}
],
"properties"
: [
"annualrevenue"
,
"name"
]
}
The response for the above request would look like:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
38
,
"results"
: [
{
"id"
:
"2810868468"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2020-01-09T20:11:27.309Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.333Z"
,
"hs_object_id"
:
"2810868468"
,
"name"
:
"Google"
},
"createdAt"
:
"2020-01-09T20:11:27.309Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.333Z"
,
"archived"
:
false
},
{
"id"
:
"2823023532"
,
"properties"
: {
"annualrevenue"
:
"10000000000"
,
"createdate"
:
"2020-01-13T16:21:08.270Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"2823023532"
,
"name"
:
"Pepsi"
},
"createdAt"
:
"2020-01-13T16:21:08.270Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.064Z"
,
"archived"
:
false
},
{
"id"
:
"5281147580"
,
"properties"
: {
"annualrevenue"
:
"50000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.332Z"
,
"hs_object_id"
:
"5281147580"
,
"name"
:
"CORKCICLE"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.332Z"
,
"archived"
:
false
},
{
"id"
:
"5281147581"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"5281147581"
,
"name"
:
"Ulta Beauty"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
,...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
2486
|
106
|
23
|
2026-05-07T11:22:25.142559+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152945142_m2.jpg...
|
Firefox
|
Search the CRM - HubSpot docs — Work
|
True
|
developers.hubspot.com/docs/api-reference/latest/c developers.hubspot.com/docs/api-reference/latest/crm/search-the-crm#limits...
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
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properties
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Report incorrect code
Copy the contents from the code block
Ask AI
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The response for the above request would look like:
Report incorrect code
Copy the contents from the code block
Ask AI
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{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"annualrevenue\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"50000000\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.251Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_lastmodifieddate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.332Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"hs_object_id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"5281147583\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"name\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Narvar\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"},","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2021-02-01T21:17:12.251Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"updatedAt\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"2024-09-13T20:23:03.332Z\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"archived\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"false","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
-3783795568805523168
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-414274301979820464
|
visual_change
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accessibility
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NULL
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:
"2024-01-17T19:55:04.281Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Test"
,
"hs_object_id"
:
"100451"
,
"lastmodifieddate"
:
"2024-09-11T13:27:39.356Z"
,
"lastname"
:
"Person"
},
"createdAt"
:
"2024-01-17T19:55:04.281Z"
,
"updatedAt"
:
"2024-09-11T13:27:39.356Z"
,
"archived"
:
false
},
{
"id"
:
"57156923994"
,
"properties"
: {
"createdate"
:
"2024-09-11T18:21:50.012Z"
,
"email"
:
"[EMAIL]"
,
"firstname"
:
"Maria"
,
"hs_object_id"
:
"57156923994"
,
"lastmodifieddate"
:
"2024-10-21T21:36:02.961Z"
,
"lastname"
:
"Johnson (Sample Contact)"
},
"createdAt"
:
"2024-09-11T18:21:50.012Z"
,
"updatedAt"
:
"2024-10-21T21:36:02.961Z"
,
"archived"
:
false
}
]
}
To return a specific set of properties, include a
properties
array in the request body. For example:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"filterGroups"
: [
{
"filters"
: [
{
"propertyName"
:
"annualrevenue"
,
"operator"
:
"GT"
,
"value"
:
"10000000"
}
]
}
],
"properties"
: [
"annualrevenue"
,
"name"
]
}
The response for the above request would look like:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
38
,
"results"
: [
{
"id"
:
"2810868468"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2020-01-09T20:11:27.309Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.333Z"
,
"hs_object_id"
:
"2810868468"
,
"name"
:
"Google"
},
"createdAt"
:
"2020-01-09T20:11:27.309Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.333Z"
,
"archived"
:
false
},
{
"id"
:
"2823023532"
,
"properties"
: {
"annualrevenue"
:
"10000000000"
,
"createdate"
:
"2020-01-13T16:21:08.270Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"2823023532"
,
"name"
:
"Pepsi"
},
"createdAt"
:
"2020-01-13T16:21:08.270Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.064Z"
,
"archived"
:
false
},
{
"id"
:
"5281147580"
,
"properties"
: {
"annualrevenue"
:
"50000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.332Z"
,
"hs_object_id"
:
"5281147580"
,
"name"
:
"CORKCICLE"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.332Z"
,
"archived"
:
false
},
{
"id"
:
"5281147581"
,
"properties"
: {
"annualrevenue"
:
"1000000000"
,
"createdate"
:
"2021-02-01T21:17:12.250Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.064Z"
,
"hs_object_id"
:
"5281147581"
,
"name"
:
"Ulta Beauty"
},
"createdAt"
:
"2021-02-01T21:17:12.250Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.064Z"
,
"archived"
:
false
},
{
"id"
:
"5281147583"
,
"properties"
: {
"annualrevenue"
:
"50000000"
,
"createdate"
:
"2021-02-01T21:17:12.251Z"
,
"hs_lastmodifieddate"
:
"2024-09-13T20:23:03.332Z"
,
"hs_object_id"
:
"5281147583"
,
"name"
:
"Narvar"
},
"createdAt"
:
"2021-02-01T21:17:12.251Z"
,
"updatedAt"
:
"2024-09-13T20:23:03.332Z"
,
"archived"
:
false...
|
2485
|
NULL
|
NULL
|
NULL
|
|
2488
|
106
|
24
|
2026-05-07T11:22:31.090897+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152951090_m2.jpg...
|
Claude
|
Claude
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call...
|
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The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating activity (engagement, meeting, call, note)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"searching for a company or contact","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating deal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"patching IDs\nReview what the limit is at the moment in the HubSpot documentation and then think of the solution:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). Example of such a error Client error:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST https://api.hubapi.com/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"resulted in a","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"429 Too Many Requests","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"response: {\"status\":\"error\",\"message\":\"You have reached your secondly limit.\",\"errorType\":\"RATE_LIMIT\",\"correlationId\":\"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). 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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. 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Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. 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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding window","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZREMRANGEBYSCORE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZCARD'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"daily_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"tonumber","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'GET'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'0'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":">=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"tonumber","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"3","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"then","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Tell caller how long to sleep until oldest entry expires","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"oldest","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
2489
|
106
|
25
|
2026-05-07T11:22:31.849829+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152951849_m2.jpg...
|
Claude
|
Claude
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
Retry
Edit
Copy
Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
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Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"EXPIRE","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"plus Lua scripting for true CAS semantics.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Key layout I'd use:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:search:{portalId} ZSET (sliding 1s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId} HASH (last seen headers)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The two short-window buckets are sliding-window-log (Redis ZSET, score =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"microtime","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The daily bucket is a plain","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with TTL set to seconds-until-midnight in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubSpot's account timezone","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"After the call, parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and store them in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId}","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. 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Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to 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HubSpot rate limit implementation strategy, rename chat
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
1
,
'OK'
,
tonumber
(...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
2490
|
106
|
26
|
2026-05-07T11:22:34.875546+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152954875_m2.jpg...
|
Claude
|
Claude
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
Retry
Edit
Copy
Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
1
,
'OK'
,
tonumber
(
ARGV
[
3
]
)
-
burst_used
-
1
}
One
EVALSHA
call. Two keys touched. Returns either
{1, OK, remaining}
or
{0, reason, retry_ms}
. No race conditions because Lua is single-threaded inside Redis. No "check then increment" gap that other workers can sneak through.
The math on whether this is heavy
The math on whether this is heavy
For your 100,000 requests, with 100 PATCHes batched into 1 batch_update call per 100 deals, you're realistically making more like
1,000–2,000 actual API calls
(assuming you're using
/batch/update
and
/batch/read
properly). But let's pretend you really make all 100k.
At HubSpot's ceiling of ~240 calls/sec across both buckets, 100k calls take roughly
7 minutes
of wall time. That means:
Redis ops/sec:
~240. A laptop-grade Redis instance handles 50,000+. You're using under half a percent.
Per-request overhead:
~0.3–1.0 ms for an
EVALSHA
against local-network Redis....
|
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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. 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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
1
,
'OK'
,
tonumber
(
ARGV
[
3
]
)
-
burst_used
-
1
}
One
EVALSHA
call. Two keys touched. Returns either
{1, OK, remaining}
or
{0, reason, retry_ms}
. No race conditions because Lua is single-threaded inside Redis. No "check then increment" gap that other workers can sneak through.
The math on whether this is heavy
The math on whether this is heavy
For your 100,000 requests, with 100 PATCHes batched into 1 batch_update call per 100 deals, you're realistically making more like
1,000–2,000 actual API calls
(assuming you're using
/batch/update
and
/batch/read
properly). But let's pretend you really make all 100k.
At HubSpot's ceiling of ~240 calls/sec across both buckets, 100k calls take roughly
7 minutes
of wall time. That means:
Redis ops/sec:
~240. A laptop-grade Redis instance handles 50,000+. You're using under half a percent.
Per-request overhead:
~0.3–1.0 ms for an
EVALSHA
against local-network Redis....
|
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|
2026-05-07T11:22:40.038021+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152960038_m2.jpg...
|
Claude
|
Claude
|
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
Retry
Edit
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
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php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
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lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,...
|
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The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating activity (engagement, meeting, call, note)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"searching for a company or contact","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating deal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"patching IDs\nReview what the limit is at the moment in the HubSpot documentation and then think of the solution:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). Example of such a error Client error:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST https://api.hubapi.com/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"resulted in a","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"429 Too Many Requests","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"response: {\"status\":\"error\",\"message\":\"You have reached your secondly limit.\",\"errorType\":\"RATE_LIMIT\",\"correlationId\":\"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. 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Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. 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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. 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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding window","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZREMRANGEBYSCORE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZCARD'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"daily_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"tonumber","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'GET'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'0'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":">=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"tonumber","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"3","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"then","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Tell caller how long to sleep until oldest entry expires","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"oldest","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZRANGE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
2494
|
106
|
28
|
2026-05-07T11:22:44.290053+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152964290_m2.jpg...
|
Firefox
|
Search the CRM - HubSpot docs — Work
|
True
|
developers.hubspot.com/docs/api-reference/latest/c developers.hubspot.com/docs/api-reference/latest/crm/search-the-crm#limits...
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:...
|
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For example, the code snippet below would retrieve a list of all contacts that have a specific company email address.","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy the contents from the code block","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Ask AI","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"filterGroups\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"filters\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"propertyName\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"email\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"operator\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"CONTAINS_TOKEN\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"value\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"*@hubspot.com\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Each object that you search will include a set of","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"default properties","depth":10,"on_screen":false,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"default properties","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"that gets returned. For contacts, a search will return","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"createdate","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"email","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"firstname","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"hs_object_id","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"lastmodifieddate","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":", and","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"lastname","depth":11,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". For example, the above request would return the following response:","depth":10,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Report incorrect code","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Copy the contents from the code block","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Ask AI","depth":10,"on_screen":false,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"total\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"2","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"results\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": [","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"id\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"100451\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"properties\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":": {","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"createdate\"","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":":","depth":12,"on_screen":false,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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1608081594001673193
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accessibility
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Platform Sprint 3 Q2 - Platform Team - Scrum Board Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
Platform Sprint 3 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS]
}
]
}
]
}
Each object that you search will include a set of
default properties
default properties
that gets returned. For contacts, a search will return
createdate
,
email
,
firstname
,
hs_object_id
,
lastmodifieddate
, and
lastname
. For example, the above request would return the following response:
Report incorrect code
Copy the contents from the code block
Ask AI
{
"total"
:
2
,
"results"
: [
{
"id"
:
"100451"
,
"properties"
: {
"createdate"
:...
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2026-05-07T11:22:46.053941+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152966053_m2.jpg...
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iTerm2
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True
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monitor_2
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can ttell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalld, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilPlatform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilcaJiminnuo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/detailsnttps://api.nubapi.com/account-info/vs/details= DocsAuthorization • Headers 9 Body ScriptsSettinasAuth TypeTokenine autnorization neader will oe automaticallygenerated when you send the reauest. Learnmore about Bearer Token authorization.GET read ci{tokenl}GET httos://:suppont Dally • In 3omNo environmentv~ SaveCookies100% L24* AIVariables in requestG token› All VarlablesInu / May 14-22.40UparadeCNeR-JHaMxlZoiNd.v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth› Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concold# TermBody Cookiesistatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingreport-tocontent-encodind200 OK • 209 ms • 1.24 KB • (| .•Thu. 07 Mav 2026 11:15:08 GMTIapplication/ison:charset=utf-89f7fce1hd89dhda6.sopDYNAMICmax-age=31536000; includeSubDomains: preloadorigin, Accept-Encodingralsehcid:desc="019e0226-0dba-7a1a-853b-a97a211c97f2" cfr'desc="9f7fce1be11d3402-IAD"nosniff019e0226-0dba-7a1a-853b-a97a211c976210000f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=%2B8ZxvcfkqBM4vc64itFbi.f"cuecoss fraction".0.01 "ronort tol."of_nolkimayaao".604900}cloudflareGlobals Vault Tools?000...
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click
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ocr
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can ttell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalld, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilPlatform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilcaJiminnuo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/detailsnttps://api.nubapi.com/account-info/vs/details= DocsAuthorization • Headers 9 Body ScriptsSettinasAuth TypeTokenine autnorization neader will oe automaticallygenerated when you send the reauest. Learnmore about Bearer Token authorization.GET read ci{tokenl}GET httos://:suppont Dally • In 3omNo environmentv~ SaveCookies100% L24* AIVariables in requestG token› All VarlablesInu / May 14-22.40UparadeCNeR-JHaMxlZoiNd.v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth› Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concold# TermBody Cookiesistatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingreport-tocontent-encodind200 OK • 209 ms • 1.24 KB • (| .•Thu. 07 Mav 2026 11:15:08 GMTIapplication/ison:charset=utf-89f7fce1hd89dhda6.sopDYNAMICmax-age=31536000; includeSubDomains: preloadorigin, Accept-Encodingralsehcid:desc="019e0226-0dba-7a1a-853b-a97a211c97f2" cfr'desc="9f7fce1be11d3402-IAD"nosniff019e0226-0dba-7a1a-853b-a97a211c976210000f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=%2B8ZxvcfkqBM4vc64itFbi.f"cuecoss fraction".0.01 "ronort tol."of_nolkimayaao".604900}cloudflareGlobals Vault Tools?000...
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2026-05-07T11:22:51.810507+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152971810_m2.jpg...
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PostmanFileEditVIewWindowmelpHubSpot rate limit i PostmanFileEditVIewWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil# Support Daily - in 38 mNo environmentvg SaveThu 7 May 14:22:51Platform Sprint 3 Q2SevenShores|Hubsp.Service-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET read ciHTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsAuthorization • Headers 9 Body ScriptsSettinasTokenine autnorization neader will oe automaticallygenerated when you send the reauest. Learnmore about Bearer Token authorization.{tokenl}GET httos://:100% L24* AIVariables in requestG token› All Varlablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concold# TermCNeR-JHaMxlZoiNd.CookiesBodyHeaders 20 lest Resultsstatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingcontent-encodind200 OK • 209 ms • 1.24 KB • (| .•Thu. 07 Mav 2026 11:15:08 GMTIapplication/ison:charset=utf-89f7fce1hd89dhda6.sopDYNAMICmax-age=31536000; includeSubDomains: preloadorigin, Accept-Encodingralsehcid:desc="019e0226-0dba-7a1a-853b-a97a211c97f2" cfr'desc="9f7fce1be11d3402-IAD"nosniff019e0226-0dba-7a1a-853b-a97a211c9762f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=%2B8ZxvcfkqBM4vc64itFbi.f"cuecoss fraction".0.01 "ronort tol."of_nolkimayaao".604900}cloudflareGlobals Vault Tools?000...
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PostmanFileEditVIewWindowmelpHubSpot rate limit i PostmanFileEditVIewWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil# Support Daily - in 38 mNo environmentvg SaveThu 7 May 14:22:51Platform Sprint 3 Q2SevenShores|Hubsp.Service-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET read ciHTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsAuthorization • Headers 9 Body ScriptsSettinasTokenine autnorization neader will oe automaticallygenerated when you send the reauest. Learnmore about Bearer Token authorization.{tokenl}GET httos://:100% L24* AIVariables in requestG token› All Varlablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concold# TermCNeR-JHaMxlZoiNd.CookiesBodyHeaders 20 lest Resultsstatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingcontent-encodind200 OK • 209 ms • 1.24 KB • (| .•Thu. 07 Mav 2026 11:15:08 GMTIapplication/ison:charset=utf-89f7fce1hd89dhda6.sopDYNAMICmax-age=31536000; includeSubDomains: preloadorigin, Accept-Encodingralsehcid:desc="019e0226-0dba-7a1a-853b-a97a211c97f2" cfr'desc="9f7fce1be11d3402-IAD"nosniff019e0226-0dba-7a1a-853b-a97a211c9762f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=%2B8ZxvcfkqBM4vc64itFbi.f"cuecoss fraction".0.01 "ronort tol."of_nolkimayaao".604900}cloudflareGlobals Vault Tools?000...
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2501
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2026-05-07T11:22:58.857059+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152978857_m2.jpg...
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iTerm2
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NULL
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True
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monitor_2
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NULL
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profle anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET [URL_WITH_CREDENTIALS] fraction":0.01"renort to"."cf-ne|""max age".604800%AlmurtorGlobals Vault Tools?000...
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NULL
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-3680811856101357322
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NULL
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click
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ocr
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profle anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET [URL_WITH_CREDENTIALS] fraction":0.01"renort to"."cf-ne|""max age".604800%AlmurtorGlobals Vault Tools?000...
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2499
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NULL
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NULL
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NULL
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2503
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106
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32
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2026-05-07T11:23:00.703996+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152980703_m2.jpg...
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iTerm2
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NULL
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can ttell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET [URL_WITH_CREDENTIALS] fraction":0.01"renort to"."cf-ne|""max age".604800%AlmudtoreGlobals Vault Tools?000...
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NULL
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-5458530078756501377
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NULL
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click
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ocr
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can ttell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET [URL_WITH_CREDENTIALS] fraction":0.01"renort to"."cf-ne|""max age".604800%AlmudtoreGlobals Vault Tools?000...
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NULL
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NULL
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NULL
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NULL
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2505
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106
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33
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2026-05-07T11:23:15.289669+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152995289_m2.jpg...
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iTerm2
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NULL
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilThu 7 May 14:23:14Platform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-appsE Docs Params Authorization • Headers 9 Body AScripts SettingsQuery ParamsKeyValueValueGET httos://:# Support Daily - in 37 mNo environmentv~ SaveCookiesBulk Edit ..100% L24* AIVariables in requestG token› All Varlablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWSConnect Git E Console 2 TermCNeR-JHaMxlZoiNd.DescriotionBodyHeaders 20 lest Resultsistatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingservecontent-encodind200 OK • 190 ms • 1.2 KB •C| .•Thu. 07 May 2026 11:23:01 GMTIapplication/ison:charset=utf-89f7fd9a4cfcA2d79-SoFDYNAMICmax-age=31536000: includeSubDomains: preloadorigin, Accept-Encodingralsehaid.daea-"0100022d.424h.2122.0222.179An6dd9780" Afridocn-"06764004d9602402-160"nosniff019e022d-434b-71c3-922a-178cafdd878e108f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=qhtousin4YfDIMG27vDtmAf.f"cuecoss fraction".0.01 "ronort to"."af_nelkimay aao".604900}cloudflareGlobals Vault Tools?000...
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NULL
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-6135975031239005473
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NULL
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click
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ocr
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NULL
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilThu 7 May 14:23:14Platform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-appsE Docs Params Authorization • Headers 9 Body AScripts SettingsQuery ParamsKeyValueValueGET httos://:# Support Daily - in 37 mNo environmentv~ SaveCookiesBulk Edit ..100% L24* AIVariables in requestG token› All Varlablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWSConnect Git E Console 2 TermCNeR-JHaMxlZoiNd.DescriotionBodyHeaders 20 lest Resultsistatuscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remainingservecontent-encodind200 OK • 190 ms • 1.2 KB •C| .•Thu. 07 May 2026 11:23:01 GMTIapplication/ison:charset=utf-89f7fd9a4cfcA2d79-SoFDYNAMICmax-age=31536000: includeSubDomains: preloadorigin, Accept-Encodingralsehaid.daea-"0100022d.424h.2122.0222.179An6dd9780" Afridocn-"06764004d9602402-160"nosniff019e022d-434b-71c3-922a-178cafdd878e108f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=qhtousin4YfDIMG27vDtmAf.f"cuecoss fraction".0.01 "ronort to"."af_nelkimay aao".604900}cloudflareGlobals Vault Tools?000...
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2503
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NULL
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NULL
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NULL
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2507
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106
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34
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2026-05-07T11:23:17.511063+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778152997511_m2.jpg...
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iTerm2
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NULL
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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PostmanFileEditVIewWindowmelpHubSpot rate limit i PostmanFileEditVIewWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilPlatform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsAuthorization • Headers 9 Body Scripts Settinas© 9 hiddenValueValueGET httos://:# Support Daily - in 37 mNo environmentv~ SaveCookiesBulk Edit Presets v100% L24* AIVariables in requestG token› All VarlablesThu 7 May 14:23:17UparadeCNeR-JHaMxlZoiNd.v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth› Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notespost Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWSConnect Git E Console 2 TermDescriotionBOSNHeaders 20 lest Resultscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remaining200 OK • 190 ms • 1.2 KB •C| .•Thu. 07 May 2026 11:23:01 GMTIapplication/ison:charset=utf-89f7fd9a4cfcA2d79-SoFDYNAMICmax-age=31536000: includeSubDomains: preloadorigin, Accept-Encodingralsehaid.daea-"0100022d.424h.2122.0222.179An6dd9780" Afridocn-"06764004d9602402-160"nosniff019e022d-434b-71c3-922a-178cafdd878e108f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=qhtousin4YfDIMG27vDtmAf.f"cuecoss fraction".0.01 "ronort to"."af_nelkimay aao".604900}cloudflarecontent-encodindGlobals Vault Tools?000...
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NULL
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2945955814782390426
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NULL
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click
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ocr
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NULL
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PostmanFileEditVIewWindowmelpHubSpot rate limit i PostmanFileEditVIewWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tenl from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply ^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the trequests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 AdaptilPlatform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsAuthorization • Headers 9 Body Scripts Settinas© 9 hiddenValueValueGET httos://:# Support Daily - in 37 mNo environmentv~ SaveCookiesBulk Edit Presets v100% L24* AIVariables in requestG token› All VarlablesThu 7 May 14:23:17UparadeCNeR-JHaMxlZoiNd.v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingspost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth› Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notespost Soarch calle v2POST Search related meetinas v3ENMIDANMENTS> SPFCS>FLOWSConnect Git E Console 2 TermDescriotionBOSNHeaders 20 lest Resultscontent-tvoecf-rayef-cache-statusstrict-transport-securityaccess-control-allow-credentialsserver-timingyacontent-tune.ontionsx-hubspot-correlation-idx-hubspot-ratelimit-interval-millisecondswwlwerrwollmteohhnay-hubsnot-ratelimit-secondlv-remaining200 OK • 190 ms • 1.2 KB •C| .•Thu. 07 May 2026 11:23:01 GMTIapplication/ison:charset=utf-89f7fd9a4cfcA2d79-SoFDYNAMICmax-age=31536000: includeSubDomains: preloadorigin, Accept-Encodingralsehaid.daea-"0100022d.424h.2122.0222.179An6dd9780" Afridocn-"06764004d9602402-160"nosniff019e022d-434b-71c3-922a-178cafdd878e108f"endpoints":[("url":*httos:Wa.nel.cloudflare.comVreportVv4?s=qhtousin4YfDIMG27vDtmAf.f"cuecoss fraction".0.01 "ronort to"."af_nelkimay aao".604900}cloudflarecontent-encodindGlobals Vault Tools?000...
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil40 hiGET httos://:Thu 7 May 14:23:18Platform Sprint 3 Q2SevenShores|Hubsp.Service-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts SettinasHeaders© 9 hidden# Support Daily - in 37 mNo environmentg SaveCookiesBulk Edit Presetsv100% L24* AIVariables in requestG tokenAll variablesv COLLECtIONs> CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiespost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenGET get subscriptionsPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTAL.GET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBOСK""JSONvPreviewe. Visualize"results":"name": "private-aops-aoi-calls-dailv"."ucadel imi+". 1000000"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002200 OK • 190 ms • 1.2 KB •C| .•=Q108Globals Vault Tools?000...
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6272796448807505190
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.in Pactman cand.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil40 hiGET httos://:Thu 7 May 14:23:18Platform Sprint 3 Q2SevenShores|Hubsp.Service-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts SettinasHeaders© 9 hidden# Support Daily - in 37 mNo environmentg SaveCookiesBulk Edit Presetsv100% L24* AIVariables in requestG tokenAll variablesv COLLECtIONs> CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiespost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenGET get subscriptionsPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTAL.GET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBOСK""JSONvPreviewe. Visualize"results":"name": "private-aops-aoi-calls-dailv"."ucadel imi+". 1000000"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002200 OK • 190 ms • 1.2 KB •C| .•=Q108Globals Vault Tools?000...
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PostmanFileEditVIeWWindowmelpHubSpot rate limit PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all papps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from acthat app made.Postman recipe to fully profile a portalThree calls, in order:1. GET /account-info/v3/details → grab portalId, timeZone, also note the X-HubSpot-RateLimit-* res Reply * lers (this is your burst profile).2. GET /account-info/v3/api-usage/daily/private-apps → daily limit, current spereserome3. (Optional) Trigger a 429 deliberately on a sandbox to confirm policyName shape, biisn't necessary just for inspection.That gives you everything HubSpot will tell you about a specific portal's limits. Save the trequests as a Postman collection with ({{access_token}} and {{portal_idf} as collectvariables and you can profile any portal in two clicks.I can see daily [URL_WITH_CREDENTIALS] fix user pilo8JiminnyDổ Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts SettinasHeaderso 9 hiddenSupport Daily - in 37 mNo environmentg SaveCookiesBulk Edit Presetsv100% L2* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners› CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiesPost search tasksGET read call> Post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenGET get subscriptionsPOST create subscriptionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth› Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetings v3PoSt search deals>ENVIRONMENTS> SPFCS>FLOWS$ Connect Git @ Console TermirCNeR-JHaMxlZoiNd.DescriotionBOdVCookiesJSONvPreviewe. Visualize"results":- nane"i mfrivatg-appo-api-calls-daily*,#currontllcado". Ol"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002"200 OK • 190 ms • 1.2 KB •C| .•=Q108Globals Vault Tools?000...
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NULL
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8150849826291258279
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click
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PostmanFileEditVIeWWindowmelpHubSpot rate limit PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all papps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from acthat app made.Postman recipe to fully profile a portalThree calls, in order:1. GET /account-info/v3/details → grab portalId, timeZone, also note the X-HubSpot-RateLimit-* res Reply * lers (this is your burst profile).2. GET /account-info/v3/api-usage/daily/private-apps → daily limit, current spereserome3. (Optional) Trigger a 429 deliberately on a sandbox to confirm policyName shape, biisn't necessary just for inspection.That gives you everything HubSpot will tell you about a specific portal's limits. Save the trequests as a Postman collection with ({{access_token}} and {{portal_idf} as collectvariables and you can profile any portal in two clicks.I can see daily [URL_WITH_CREDENTIALS] fix user pilo8JiminnyDổ Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts SettinasHeaderso 9 hiddenSupport Daily - in 37 mNo environmentg SaveCookiesBulk Edit Presetsv100% L2* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners› CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiesPost search tasksGET read call> Post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenGET get subscriptionsPOST create subscriptionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET next offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth› Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetings v3PoSt search deals>ENVIRONMENTS> SPFCS>FLOWS$ Connect Git @ Console TermirCNeR-JHaMxlZoiNd.DescriotionBOdVCookiesJSONvPreviewe. Visualize"results":- nane"i mfrivatg-appo-api-calls-daily*,#currontllcado". Ol"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002"200 OK • 190 ms • 1.2 KB •C| .•=Q108Globals Vault Tools?000...
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2514
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2026-05-07T11:23:23.612995+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153003612_m2.jpg...
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.n Pactman cond.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil40 hiGET httos://:Thu 7 May 14:23:23Platform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - HubXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts Settinas© 9 hidden# Support Daily - in 37 mNo environmentvg SaveCookiesBulk Edit Presets v100% L24* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiespost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenGET get subscriptionsPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTAL.GET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notespost Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBOdVCookiesJSONvPreviewe. Visualize"results":"name": "private-apos-api-calls-dailly""usagelimit": 1000000,"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002200 OK • 190 ms • 1.2 KB •C| .•Globals Vault Tools?000...
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-853511464853379865
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click
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PostmanFileEditVIeWWindowmelpHubSpot rate limit i PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all piapps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from a clthat app madePostman recipe to rully pronle a portalThree calls. in order:1. GET /account-info/v3/details →grab portalId, timeZone , also note the x-HubSpot-RateLimit-* res Reply^ iers (this is vour burst profile).2. GET /account-info/v3/api-usage/daily/private-apps daily limit, current spelreserome3. (Optional) Trigger a 429 deliberatelv on a sandbox to confirm policvName shape.brisn't necessarv iust for inspectionThat gives you everything Hubspot will tell you about a specific portal's limits. Save the 1requests as a Postman collection with {{access token?? and {{portal id?? as collecivariables and vou can profile anv nortal in two clicks.I can see daily https:api.hubapi.com/account-info/v3/details what aborsearch and ourstDistinguished burst limits via headers fromBurst: visible, but in response headers, not the body. Any non-search call works.n Pactman cond.GET https://api.hubapi.com/account-info/v3/detailsAuthorization: Bearer {token?Then in the response panel click the Headerst J .ot Body). You'll see something like:Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..Write a message…Opus 4.7 Adaptil40 hiGET httos://:Thu 7 May 14:23:23Platform Sprint 3 Q2SevenShores\HubspeService-Desk - Queu• Jy 20807 check varioa Sentry••Pull requests • jiminnyU Useroilot I Ask JiminJY-20773 fix user pilc8Jiminnyo Search the CRM - HubXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaboration.GET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts Settinas© 9 hidden# Support Daily - in 37 mNo environmentvg SaveCookiesBulk Edit Presets v100% L24* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPOST search moditied companiespost coarch tackeGET read call> PosT search callsGET list callsPOST meetings scheduledGET get meetingPOST get link to task> POST Create Contact with Association> HubsnotJournal & webhoooks v4POSt Get tokenGET get subscriptionsPOST create subscrintionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SURSCRIPTION DER PORTAL.GET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPOST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notespost Soarch calle v2POST Search related meetinas v3post coarch doalsENMIDANMENTS> SPFCS>FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBOdVCookiesJSONvPreviewe. Visualize"results":"name": "private-apos-api-calls-dailly""usagelimit": 1000000,"collectedat": "2026-05-07T11:23:01.362Z""2026-05-08T04:00:002200 OK • 190 ms • 1.2 KB •C| .•Globals Vault Tools?000...
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PostmanFileEditVIeWWindowmelpHubSpot rate limit PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all papps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from acthat app made.Postman recipe to fully profile a portalThree calls, in order:1. GET /account-info/v3/details → grab portalId, timeZone, also note the X-HubSpot-RateLimit-* res Reply * lers (this is your burst profile).2. GET /account-info/v3/api-usage/daily/private-apps → daily limit, current spereserome3. (Optional) Trigger a 429 deliberately on a sandbox to confirm policyName shape, biisn't necessary just for inspection.That gives you everything HubSpot will tell you about a specific portal's limits. Save thetrequests as a Postman collection with ({{access_token}} and {{portal_id}} as collectvariables and you can profile any portal in two clicks.I can see daily [URL_WITH_CREDENTIALS] fix user piloaJiminnuDổ Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaborationGET next off. • POST search •i https://api.hubapi.com/account-info/v3/api-usage/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps# DocsHeaderso 9 hiddenAuthorization • Headers 9 Body Scripts SettingsSO WOSupport Daily • in 37 mGET httos://:No environng SaveCookiesBulk Edit Presets100% C4)* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners› CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPost search tasksGET read call> post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenPOST create subscriptionGET Journal earliestGET Journal latestGET httos:/ubspot-webhooks-journal-na1.sGET neyt offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3>ENVIRONMENTS) spFcs>FLOWS@ Connect Git = Concole 5.) TermCNeR-JHaMxlZoiNO.DescriotionBOdVCookies 1# IB USON ~Previewe. Visualize200 OK • 190 ms • 1.2 KB •C| .•=aIDO"collectedAt" : "2026-05-07711:23:01,3622*.Globals Vault Toos S 0 00...
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PostmanFileEditVIeWWindowmelpHubSpot rate limit PostmanFileEditVIeWWindowmelpHubSpot rate limit implementation strategythem), not in any endpoint. It's a documented cons• Daily usage broken out by app within a portal — the daily endpoint aggregates all papps. You can t tell from the Art wnich app spent the buaget.• Per-app burst limit programmatically — only inferred from Max in headers from acthat app made.Postman recipe to fully profile a portalThree calls, in order:1. GET /account-info/v3/details → grab portalId, timeZone, also note the X-HubSpot-RateLimit-* res Reply * lers (this is your burst profile).2. GET /account-info/v3/api-usage/daily/private-apps → daily limit, current spereserome3. (Optional) Trigger a 429 deliberately on a sandbox to confirm policyName shape, biisn't necessary just for inspection.That gives you everything HubSpot will tell you about a specific portal's limits. Save thetrequests as a Postman collection with ({{access_token}} and {{portal_id}} as collectvariables and you can profile any portal in two clicks.I can see daily [URL_WITH_CREDENTIALS] fix user piloaJiminnuDổ Search the CRM - Hub— New TabXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaborationGET next off. • POST search •i https://api.hubapi.com/account-info/v3/api-usage/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps# DocsHeaderso 9 hiddenAuthorization • Headers 9 Body Scripts SettingsSO WOSupport Daily • in 37 mGET httos://:No environng SaveCookiesBulk Edit Presets100% C4)* AIVariables in requestG tokenAll variablesv COLLECtIONs› CRM ObjectsCRM Owners› CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPost search tasksGET read call> post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenPOST create subscriptionGET Journal earliestGET Journal latestGET httos:/ubspot-webhooks-journal-na1.sGET neyt offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3> OAuth> Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3>ENVIRONMENTS) spFcs>FLOWS@ Connect Git = Concole 5.) TermCNeR-JHaMxlZoiNO.DescriotionBOdVCookies 1# IB USON ~Previewe. Visualize200 OK • 190 ms • 1.2 KB •C| .•=aIDO"collectedAt" : "2026-05-07711:23:01,3622*.Globals Vault Toos S 0 00...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(...
|
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Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"EXPIRE","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"plus Lua scripting for true CAS semantics.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Key layout I'd use:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:search:{portalId} ZSET (sliding 1s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId} HASH (last seen headers)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The two short-window buckets are sliding-window-log (Redis ZSET, score =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"microtime","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The daily bucket is a plain","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with TTL set to seconds-until-midnight in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubSpot's account timezone","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"After the call, parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and store them in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId}","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding 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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(...
|
2515
|
NULL
|
NULL
|
NULL
|
|
2518
|
106
|
40
|
2026-05-07T11:23:28.069229+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153008069_m2.jpg...
|
Claude
|
Claude
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Edit
Copy
Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact...
|
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What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). 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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. 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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact...
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Claude
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
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hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
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php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
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lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[...
|
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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. 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Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding window","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZREMRANGEBYSCORE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZCARD'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[...
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PostmancaltVIewWindowmelpHubSpot rate limit implem PostmancaltVIewWindowmelpHubSpot rate limit implementation strategyX-HubSpot-RateLimit-Max: 190X-HubSpot-RateLimit-Remaining: 189X-Hubspot-kateL1m1t-Incerval-M1111seconds: 10000That tells you the portal is on 190 calls per 10 seconds. The Remaining value is live — fire thesame call again immediately and it drops to 188. etc. There is no endpoint that returns this inJSON; the headers are the only channel.Search: not visible. At all.• No endpoint exposes the 5/sec search limit• Search responses ( POST /crm/v3/objects/{type}/search ) deliberately strip all x-HubSpot-RateLimit-* headers, so you can't read it from a search call either.• The 5/sec figure is a documented constant — you assume it, you don't query it.• The only way to "observe" the search limit empirically is to deliberately exceed it andinspect the 429 response, where the body contains "policyName": "SECONDLY" and"message": "You have reached your secondly limit." — which is what you alreadysaw in your original error.So your rull per-portal picture from the APl 1S:uimitlow to see it via PostmanDailyGET /account-info/v3/api-usage/daily/private-apps (body)Any non-search call (response Headers t. VKeep going in Claude CodeSwitch to Claude Code and let Claude work directly in your repo,running and testing as it goes."results": ["name": "private-apps-api-calls-daily","currentusage": 0."2026-05-07T11:23:01. 362Z","fetchStatus":ncueeecen"resetsAt": "2026-05-08T04:00: 00Z"v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPost search tasksGET read call> Post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenGET get subscriptionsPOST create subscriptionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth> Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3PoSt search deals>ENVIRONMENTS> SPFCS> FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBodyCookiesHeadss 20JSONvPreview? Visualize"results":"name": "private-apps-api-calls-daily*."2026-05-07T11:23:01.3622"resetsAt": "2026-05-08T04:00:002'200 OK • 190 ms • 1.2 KB •C| .•=a1D0Opus 4.7 AdaptiveXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaborationGET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts Settinas© 9 hiddenSO WOSupport Daily • in 37 mGET httos://:No environng SaveCookiesBulk Edit Presets100% C4)* AIVariables in requestG tokenAll variablesThu 7 May 14:23:33Globals Vault Toos S 0 00...
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PostmancaltVIewWindowmelpHubSpot rate limit implem PostmancaltVIewWindowmelpHubSpot rate limit implementation strategyX-HubSpot-RateLimit-Max: 190X-HubSpot-RateLimit-Remaining: 189X-Hubspot-kateL1m1t-Incerval-M1111seconds: 10000That tells you the portal is on 190 calls per 10 seconds. The Remaining value is live — fire thesame call again immediately and it drops to 188. etc. There is no endpoint that returns this inJSON; the headers are the only channel.Search: not visible. At all.• No endpoint exposes the 5/sec search limit• Search responses ( POST /crm/v3/objects/{type}/search ) deliberately strip all x-HubSpot-RateLimit-* headers, so you can't read it from a search call either.• The 5/sec figure is a documented constant — you assume it, you don't query it.• The only way to "observe" the search limit empirically is to deliberately exceed it andinspect the 429 response, where the body contains "policyName": "SECONDLY" and"message": "You have reached your secondly limit." — which is what you alreadysaw in your original error.So your rull per-portal picture from the APl 1S:uimitlow to see it via PostmanDailyGET /account-info/v3/api-usage/daily/private-apps (body)Any non-search call (response Headers t. VKeep going in Claude CodeSwitch to Claude Code and let Claude work directly in your repo,running and testing as it goes."results": ["name": "private-apps-api-calls-daily","currentusage": 0."2026-05-07T11:23:01. 362Z","fetchStatus":ncueeecen"resetsAt": "2026-05-08T04:00: 00Z"v COLLECtIONs› CRM ObjectsCRM Owners> CRM Pipelines> DealsEngagements• D OLD ENGAGEMENTSGET list meetingsPost search tasksGET read call> Post search callsGET list callsPoST meetings scheduledGET get meetingPost get link to task> POST Create Contact with Association› HubspotJournal & webhoooks v4POST Get tokenGET get subscriptionsPOST create subscriptionGET Journal earliestGET Journal latestGET https:/ubspot-webhooks-journal-nal.s.GET neyt offsetPOST aet Token prodDEL DELETE SUBSCRIPTION PER PORTALGET DEAL WITH HISTORY PROPERTIES V3› OAuth> Properties> PESCAPCHV SEARCHIPoST search contact by phonePost search contact ov emailliPOST search meetingsPOST search notes> post Soarch calle v2POST Search related meetinas v3PoSt search deals>ENVIRONMENTS> SPFCS> FLOWS@ Connect Git = Concole 5.) TerminCNeR-JHaMxlZoiNd.DescriotionBodyCookiesHeadss 20JSONvPreview? Visualize"results":"name": "private-apps-api-calls-daily*."2026-05-07T11:23:01.3622"resetsAt": "2026-05-08T04:00:002'200 OK • 190 ms • 1.2 KB •C| .•=a1D0Opus 4.7 AdaptiveXx Hubspot vQ SearchYour team is now on the Free plan with 1 admin. You retain editing access and other members are read-only. View team permissions to see who can edit, or upgrade to restore collaborationGET next off. • POST search •HTTP https:pi.hubapi.com/account-info/v3/api-usaqe/daily/private-appshttps://api.hubapi.com/account-info/v3/api-usage/daily/private-apps= DocsParams Authorization • Headers 9 Body Scripts Settinas© 9 hiddenSO WOSupport Daily • in 37 mGET httos://:No environng SaveCookiesBulk Edit Presets100% C4)* AIVariables in requestG tokenAll variablesThu 7 May 14:23:33Globals Vault Toos S 0 00...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
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php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
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lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2...
|
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The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating activity (engagement, meeting, call, note)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"searching for a company or contact","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating deal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"patching IDs\nReview what the limit is at the moment in the HubSpot documentation and then think of the solution:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). Example of such a error Client error:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST https://api.hubapi.com/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"resulted in a","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"429 Too Many Requests","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"response: {\"status\":\"error\",\"message\":\"You have reached your secondly limit.\",\"errorType\":\"RATE_LIMIT\",\"correlationId\":\"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. 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Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. 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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. 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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding window","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZREMRANGEBYSCORE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"burst_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZCARD'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"daily_used","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"tonumber","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'GET'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_descriptio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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2...
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|
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|
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44
|
2026-05-07T11:23:37.465894+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153017465_m2.jpg...
|
Claude
|
Claude
|
True
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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Give positive feedback
Give negative feedback
Retry
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
1
,
'OK'
,
tonumber
(
ARGV
[
3
]
)
-
burst_used
-
1
}
One
EVALSHA
call. Two keys touched. Returns either
{1, OK, remaining}
or
{0, reason, retry_ms}
. No race conditions because Lua is single-threaded inside Redis. No "check then increment" gap that other workers can sneak through.
The math on whether this is heavy
The math on whether this is heavy
For your 100,000 requests, with 100 PATCHes batched into 1 batch_update call per 100 deals, you're realistically making more like
1,000–2,000 actual API calls
(assuming you're using
/batch/update
and
/batch/read
properly). But let's pretend you really make all 100k.
At HubSpot's ceiling of ~240 calls/sec across both buckets, 100k calls take roughly
7 minutes
of wall time. That means:
Redis ops/sec:
~240. A laptop-grade Redis instance handles 50,000+. You're using under half a percent.
Per-request overhead:
~0.3–1.0 ms for an
EVALSHA...
|
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collapse","depth":16,"bounds":{"left":0.10239362,"top":0.06703911,"width":0.030585106,"height":0.011971269},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.10239362,"top":0.06703911,"width":0.0029920214,"height":0.011971269}},{"char_start":1,"char_count":16,"bounds":{"left":0.10538564,"top":0.06703911,"width":0.027925532,"height":0.011971269}}],"role_description":"text"},{"role":"AXStaticText","text":"⌘B","depth":16,"bounds":{"left":0.1349734,"top":0.06703911,"width":0.0063164895,"height":0.011971269},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Drag to 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That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"EXPIRE","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"plus Lua scripting for true CAS semantics.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Key layout I'd use:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:search:{portalId} ZSET (sliding 1s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId} HASH (last seen headers)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The two short-window buckets are sliding-window-log (Redis ZSET, score =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"microtime","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The daily bucket is a plain","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with TTL set to seconds-until-midnight in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubSpot's account timezone","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"After the call, parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and store them in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId}","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. 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Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? 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No \"check then increment\" gap that other workers can sneak through.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The math on whether this is heavy","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The math on whether this is heavy","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For your 100,000 requests, with 100 PATCHes batched into 1 batch_update call per 100 deals, you're realistically making more like","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1,000–2,000 actual API calls","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(assuming you're using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/batch/update","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/batch/read","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"properly). But let's pretend you really make all 100k.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"At HubSpot's ceiling of ~240 calls/sec across both buckets, 100k calls take roughly","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 minutes","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of wall time. That means:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis ops/sec:","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240. A laptop-grade Redis instance handles 50,000+. You're using under half a percent.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-request overhead:","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~0.3–1.0 ms for an","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"EVALSHA","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Retry
Edit
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then
return
{
0
,
'DAILY'
,
-
1
}
end
redis
.
call
(
'ZADD'
,
KEYS
[
1
]
,
ARGV
[
1
]
,
ARGV
[
5
]
)
redis
.
call
(
'PEXPIRE'
,
KEYS
[
1
]
,
ARGV
[
2
]
+
1000
)
local
d
=
redis
.
call
(
'INCR'
,
KEYS
[
2
]
)
if
d
==
1
then
redis
.
call
(
'EXPIRE'
,
KEYS
[
2
]
,
ARGV
[
6
]
)
end
return
{
1
,
'OK'
,
tonumber
(
ARGV
[
3
]
)
-
burst_used
-
1
}
One
EVALSHA
call. Two keys touched. Returns either
{1, OK, remaining}
or
{0, reason, retry_ms}
. No race conditions because Lua is single-threaded inside Redis. No "check then increment" gap that other workers can sneak through.
The math on whether this is heavy
The math on whether this is heavy
For your 100,000 requests, with 100 PATCHes batched into 1 batch_update call per 100 deals, you're realistically making more like
1,000–2,000 actual API calls
(assuming you're using
/batch/update
and
/batch/read
properly). But let's pretend you really make all 100k.
At HubSpot's ceiling of ~240 calls/sec across both buckets, 100k calls take roughly
7 minutes
of wall time. That means:
Redis ops/sec:
~240. A laptop-grade Redis instance handles 50,000+. You're using under half a percent.
Per-request overhead:
~0.3–1.0 ms for an
EVALSHA...
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Claude is responding
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then...
|
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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding 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Tell caller how long to sleep until oldest entry expires","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"local","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"oldest","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"call","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'ZRANGE'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"KEYS","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'WITHSCORES'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"return","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'BURST'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"oldest","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ARGV","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"[","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"]","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text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HubSpot rate limit implementation strategy, rename chat
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Claude is responding
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
Give negative feedback
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
Copy
Give positive feedback
Give negative feedback
You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
Edit
Copy
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
.
call
(
'ZREMRANGEBYSCORE'
,
KEYS
[
1
]
,
0
,
ARGV
[
1
]
-
ARGV
[
2
]
)
local
burst_used
=
redis
.
call
(
'ZCARD'
,
KEYS
[
1
]
)
local
daily_used
=
tonumber
(
redis
.
call
(
'GET'
,
KEYS
[
2
]
)
or
'0'
)
if
burst_used
>=
tonumber
(
ARGV
[
3
]
)
then
-- Tell caller how long to sleep until oldest entry expires
local
oldest
=
redis
.
call
(
'ZRANGE'
,
KEYS
[
1
]
,
0
,
0
,
'WITHSCORES'
)
return
{
0
,
'BURST'
,
(
oldest
[
2
]
+
ARGV
[
2
]
)
-
ARGV
[
1
]
}
end
if
daily_used
>=
tonumber
(
ARGV
[
4
]
)
then...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:54DEV (docker)83DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:54DEV (docker)83DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:55DEV (docker)83DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:55DEV (docker)83DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:59DEV (docker)T81DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:24:59DEV (docker)T81DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:25:00DEV (docker)T81DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
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-8543218788614548688
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 36 m100% [Thu 7 May 14:25:00DEV (docker)T81DOCKERLast login: Thu MayO ₴1DEV (docker)7 09:44:56 on ttys006H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴6Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
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NULL
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NULL
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NULL
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NULL
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2543
|
107
|
5
|
2026-05-07T11:25:16.598356+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153116598_m1.jpg...
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iTerm2
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NULL
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True
|
NULL
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monitor_1
|
NULL
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NULL
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NULL
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NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100%8DEV (docker)83Thu 7 May 14:25:16181₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
|
8058715589498286472
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100%8DEV (docker)83Thu 7 May 14:25:16181₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
2540
|
NULL
|
NULL
|
NULL
|
|
2546
|
107
|
6
|
2026-05-07T11:25:19.372478+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153119372_m1.jpg...
|
iTerm2
|
NULL
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
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NULL
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [Thu 7 May 14:25:19DEV (docker)181DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴67 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
|
-3251558231255590342
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [Thu 7 May 14:25:19DEV (docker)181DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)83-zsh• 84screenpipe*•$5-zsh₴67 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
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NULL
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NULL
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NULL
|
|
2547
|
107
|
7
|
2026-05-07T11:25:21.337824+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153121337_m1.jpg...
|
iTerm2
|
NULL
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True
|
NULL
|
monitor_1
|
NULL
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NULL
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NULL
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NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [8DEV (docker)83Thu 7 May 14:25:21181₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
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-3805931885094005568
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [8DEV (docker)83Thu 7 May 14:25:21181₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*•$5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
2546
|
NULL
|
NULL
|
NULL
|
|
2550
|
107
|
8
|
2026-05-07T11:25:23.959113+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153123959_m1.jpg...
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iTerm2
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NULL
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True
|
NULL
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monitor_1
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NULL
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NULL
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NULL
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [DEV (docker)83Thu 7 May 14:25:23T81₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe** *5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
|
4421466829041639247
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [DEV (docker)83Thu 7 May 14:25:23T81₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe** *5-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
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NULL
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NULL
|
NULL
|
|
2552
|
107
|
9
|
2026-05-07T11:25:25.269545+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153125269_m1.jpg...
|
iTerm2
|
NULL
|
True
|
NULL
|
monitor_1
|
NULL
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NULL
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NULL
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [DEV (docker)83Thu 7 May 14:25:25T81₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
NULL
|
8072196716277446747
|
NULL
|
click
|
ocr
|
NULL
|
iTerm2ShellEditViewSessionScriptsProfilesWindowHel iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ah]• Support Daily • in 35 m100% [DEV (docker)83Thu 7 May 14:25:25T81₴6DOCKERLast login: Thu MayDEV (docker)H82APP (-zsh)-zsh• 84screenpipe*-zsh7 09:44:56 on ttys006Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentsPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parentslukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ devroot@docker_lamp_1:/home/jiminny# php artisan crm:sync-opportunity --teamId=2 --from='2026-05-01 00:00:00*Syncing opportunity for HubspotYour HubSpotaccount has become disconnected. Please login to Jiminny to reconnect. skipping...root@docker_lamp_1:/home/jiminny# php artisan jiminny:token-info -A 1499 -RDEVaccess_tokenCFPAsBNZxoDp5kAcRyeB1QoE5SM7DSgNuYTFSAFoAYABo3tj9DHAAeAACNeR-JHgMxIZQLNQMl8kQEwrAgwACAkUAhIJBB4BAQEDBxiCiYwCIN7Y_Qwo0qwCMhTnG549n-YtNuc1jgj-2AsLPSmw3DoyQLNQM18kQEwrAiUACBkGawEFThwBARIBAQEEATEEAQEBAQEBAQEBAQUBEggBAQEBAY1access_token_expires_at= 2026-05-07 11:41:20refresh_token => d5ab04e2-2109-4c0b-b513-8cba1dd54371refresh_token_expires_at =root@docker_lamp_1:/home/jiminny#...
|
2550
|
NULL
|
NULL
|
NULL
|
|
2553
|
107
|
10
|
2026-05-07T11:25:28.000852+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153128000_m1.jpg...
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Claude
|
Claude
|
True
|
NULL
|
monitor_1
|
NULL
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NULL
|
NULL
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NULL
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More options for HubSpot rate limit handling with executeRequest
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
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hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
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php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?...
|
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The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. 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What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). Example of such a error Client error:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST https://api.hubapi.com/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"resulted in a","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"429 Too Many Requests","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"response: {\"status\":\"error\",\"message\":\"You have reached your secondly limit.\",\"errorType\":\"RATE_LIMIT\",\"correlationId\":\"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. 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This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. 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Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Edit
Copy
Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
Copy
Give positive feedback
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?...
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|
/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153158711_m1.jpg...
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Claude
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Claude
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
Retry
Edit
Copy
Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
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┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
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php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
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lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
....
|
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The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating activity (engagement, meeting, call, note)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"searching for a company or contact","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"updating deal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"patching IDs\nReview what the limit is at the moment in the HubSpot documentation and then think of the solution:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":25,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). 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Think carefully about the implementation and potential issue and bottlenecks.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Show more","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"10:42","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Current HubSpot limits (Apr 2026)","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Current HubSpot limits (Apr 2026)","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Current HubSpot limits (Apr 2026)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The burst window is per app; the daily quota is per portal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". That's the limit the 429 in your example is hitting (","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"secondly limit","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/crm/v3/objects/contact/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). It's a separate bucket from the 190/10s, and critically, search responses do not include the","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-*","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"headers","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— you can't read remaining capacity off the response, you have to track it yourself.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search endpoints return","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". The daily headers are not returned for OAuth-authenticated calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— that's enforced for marketplace listing, but it's also a sane operational target.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"hubspot","depth":26,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"So you have","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"four buckets","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Where to store it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Where to store it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"EXPIRE","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"plus Lua scripting for true CAS semantics.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Key layout I'd use:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:search:{portalId} ZSET (sliding 1s)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId} HASH (last seen headers)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The two short-window buckets are sliding-window-log (Redis ZSET, score =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"microtime","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The daily bucket is a plain","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"INCR","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with TTL set to seconds-until-midnight in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubSpot's account timezone","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to read it","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to read it","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two-phase: optimistic pre-check, authoritative post-update.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Before a call, run the Lua acquire script. If it returns \"denied,\" sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"After the call, parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and store them in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId}","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"┌──────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search request ──→ │ Search: 5/sec │ ──┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"├──→ ┌─────────────────┐","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"┌──────────────────┐ │ │ Daily: 250k–1M │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"└──────────────────┘ └─────────────────┘","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What this means practically","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What this means practically","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting search secondly limit (5/s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only further","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/search","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting burst limit (190/10s):","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Hitting daily limit:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"So can one type of request block the other?","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"So can one type of request block the other?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search → Burst:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Burst → Search:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"No.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Saturating burst leaves Search's 5/s untouched.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Either → Daily:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but only by contributing to the same daily counter. It's volume that kills you here, not the type.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In theory you can sustain ~50 search + ~190 other =","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"~240 calls per 10 seconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"indefinitely (until daily runs out), because the two buckets bill independently.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Implementation consequence","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Implementation consequence","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"php","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'search'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for search endpoints only","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'burst'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// for everything else","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$limiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"->","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"'daily'","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"$weight","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"=","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":")","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":";","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"// every call, both kinds","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('search')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". A batch update calls","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('burst')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"+","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"acquire('daily')","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"One subtle pitfall: when you backoff on a 429,","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inspect","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in the response body","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to know which bucket actually fired. If you see","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SECONDLY","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other subtlety: the burst response gives you","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: Ok, so what will happen each time I make a request?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: Ok, so what will happen each time I make a request?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:44","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed per-request overhead concerns and quantified Redis performance impact","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"What \"two buckets per request\" actually costs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"What \"two buckets per request\" actually costs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each request makes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"one round trip to Redis","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy to clipboard","depth":27,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"lua","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[1] = burst bucket key (or search)","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- KEYS[2] = daily bucket key","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[1] = now (ms) ARGV[2] = window_ms","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[3] = bucket_max ARGV[4] = daily_max","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- ARGV[5] = request_id ARGV[6] = daily_ttl","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- Trim sliding window","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":27,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits
Copy to clipboard
┌──────────────────┐
Search request ──→ │ Search: 5/sec │ ──┐
└──────────────────┘ │
├──→ ┌─────────────────┐
┌──────────────────┐ │ │ Daily: 250k–1M │
Non-search call ──→ │ Burst: 190/10s │ ──┘ │ (per portal) │
└──────────────────┘ └─────────────────┘
A search call is only metered against the search bucket and the daily bucket. A non-search call (batch read/update, single PATCH, associations, etc.) is only metered against the burst bucket and the daily bucket. The two short-window buckets do not share counters.
What this means practically
What this means practically
Hitting search secondly limit (5/s):
Only further
/search
calls 429. Your batch reads, batch updates, single PATCHes, association calls — all keep working at full burst speed. This is actually useful: if your sync is bottlenecked on Search, you can pivot to using
lastmodifieddate
filters via batch endpoints, or use the IDs you already have to do batch reads, while Search cools off.
Hitting burst limit (190/10s):
Only non-search calls 429. You can still issue Search calls at 5/s. Useful for: continuing to identify deltas for queueing while in-flight updates drain, or refreshing a small set of records via Search even though your write pipeline is paused.
Hitting daily limit:
Everything stops. Search and non-search alike. Doesn't unblock until midnight in your portal's configured timezone — and remember this is shared across every private app in the portal, plus n8n flows, marketing tools, anything else hitting the API with that account.
So can one type of request block the other?
So can one type of request block the other?
Search → Burst:
No.
Saturating Search at 50 calls per 10s leaves your full 190/10s burst untouched.
Burst → Search:
No.
Saturating burst leaves Search's 5/s untouched.
Either → Daily:
Yes
, but only by contributing to the same daily counter. It's volume that kills you here, not the type.
In theory you can sustain ~50 search + ~190 other =
~240 calls per 10 seconds
indefinitely (until daily runs out), because the two buckets bill independently.
Implementation consequence
Implementation consequence
Your rate limiter needs to know which bucket a request hits before it acquires. Cleanest pattern:
Copy to clipboard
php
$limiter
->
acquire
(
'search'
,
$weight
=
1
)
;
// for search endpoints only
$limiter
->
acquire
(
'burst'
,
$weight
=
1
)
;
// for everything else
$limiter
->
acquire
(
'daily'
,
$weight
=
1
)
;
// every call, both kinds
In Redis: three separate keys, three separate Lua acquire scripts (or one script with a bucket parameter). A search call calls
acquire('search')
+
acquire('daily')
. A batch update calls
acquire('burst')
+
acquire('daily')
.
One subtle pitfall: when you backoff on a 429,
inspect
policyName
in the response body
to know which bucket actually fired. If you see
SECONDLY
from a search endpoint, you only need to delay search-bound jobs — burst-bound jobs in the queue can keep running. If you blanket-pause everything on any 429, you waste capacity on the bucket that's still healthy. Two queues (or two throttle keys) make this clean; one global pause is the lazy version.
The other subtlety: the burst response gives you
X-HubSpot-RateLimit-Remaining
to clamp local state against, but search doesn't return those headers. So your search counter is unverified — be slightly more conservative there (e.g., budget 4/s instead of 5) to absorb the unaccounted-for calls.
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You said: Ok, so what will happen each time I make a request?
You said: Ok, so what will happen each time I make a request?
Ok, so what will happen each time I make a request? Let's say I have 100,000 requests to make that are instant. Do I need to increment each request based on the type? For example, if there is a search request, I need to increment both the search bucket and also the daily bucket. If it's a burst, then I can go to the daily and burst buckets. If I need to check if it can make a call, do I need to see both the daily and search, or burst, respectively? Isn't that too heavy for the infrastructure, adding additional load to each request?
13:44
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Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Claude responded: Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out.
Analyzed per-request overhead concerns and quantified Redis performance impact
Analyzed per-request overhead concerns and quantified Redis performance impact
Yes, your understanding is correct — every request must check and reserve from each bucket it applies to, atomically, before the call goes out. But the overhead is much smaller than it sounds, and importantly, it's nowhere near your bottleneck.
What "two buckets per request" actually costs
What "two buckets per request" actually costs
Each request makes
one round trip to Redis
— not two — because you fold both bucket checks into a single Lua script that runs atomically server-side:
Copy to clipboard
lua
-- KEYS[1] = burst bucket key (or search)
-- KEYS[2] = daily bucket key
-- ARGV[1] = now (ms) ARGV[2] = window_ms
-- ARGV[3] = bucket_max ARGV[4] = daily_max
-- ARGV[5] = request_id ARGV[6] = daily_ttl
-- Trim sliding window
redis
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/Users/lukas/.screenpipe/data/data/2026-05-07/1778 /Users/lukas/.screenpipe/data/data/2026-05-07/1778153168260_m1.jpg...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
Show more
10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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Give positive feedback
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Retry
You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
Retry
Edit
Copy
Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits...
|
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Don't busy-loop.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"After the call, parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"X-HubSpot-RateLimit-Remaining","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Max","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-Interval-Milliseconds","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and store them in","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot:rl:meta:{portalId}","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"For search specifically, since headers don't come back, the local counter","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"not","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"on 429 (you really did make that request).","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with multiple jobs","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with multiple jobs","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Concurrency cap","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"via","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Queue::throttle()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Per-tenant fairness","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Priority lanes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-priority","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hubspot-bulk","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Backoff on 429","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— respect the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"header. If absent, exponential with jitter (e.g.,","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"min(2^attempt * 250ms, 30s) ± 20%","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to work with paginated requests","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to work with paginated requests","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The trap is treating \"fetch all\" as one logical operation. Each page is its own API call and competes for tokens with everything else.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two practical rules:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Don't hold the worker idle while paginating.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"processing","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"of page N as a separate job, and queue a \"fetch page N+1\" job with a delay equal to the wait time. Each page becomes its own atomic unit.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Always batch where HubSpot offers it.","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/{type}/batch/{read|update|create}","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"accepts up to 100 IDs per call. For your \"patching IDs\" flow this is the difference between 600 calls and 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Walkthrough: 600 opportunities","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Walkthrough: 600 opportunities","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Sane flow:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Identify deltas","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— if you can avoid Search at all, do. Use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"current state —","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/read","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 IDs per call → 6 calls. Burst weight 6.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Compute diff","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"in your code (no API).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Batch update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v3/objects/deals/batch/update","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with 100 per call → 6 calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Associations","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"—","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /crm/v4/associations/{from}/{to}/batch/create","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"if needed → another few batch calls.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Recognition: pre-check denies if","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<weight>","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"slots aren't free; on 429 the response surfaces","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"policyName","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(DAILY/SECONDLY) — log it, push the job back with","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry-After","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"delay, increment a metric so you can alarm on sustained 429 rate.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Pitfalls & bottlenecks worth pre-empting","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Pitfalls & bottlenecks worth pre-empting","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Daily quota is shared across the whole portal","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search is uniquely fragile","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"hs_object_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ranges or by","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lastmodifieddate","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"windows.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Retry storms after HubSpot incidents","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Webhook → sync → webhook loops","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"jy_last_sync_id","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":") and ignore webhooks where it just changed.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Token refresh","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"expires_in - 60s","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", single-flight the refresh (only one worker refreshes; others wait on a lock).","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search latency for fresh writes","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Clock skew","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— Redis is authoritative. Don't use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"time()","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"from each worker for window scoring; use","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"redis.call('TIME')","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"inside the Lua script.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Dead workers with held tokens","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The 5% error rule","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Phantom contention with Laravel","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimited","depth":28,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"middleware","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":": it's per-job-class by default, not per-portal. If your","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SyncDealJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"UpdateActivityJob","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"HubspotRateLimiter","depth":27,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"service that everything routes through.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give positive feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Give negative feedback","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"You said: What will happen if there are two different types of rate limits?","depth":20,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"You said: What will happen if there are two different types of rate limits?","depth":21,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"What will happen if there are two different types of rate limits?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Search requests that have 5 requests per second","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13:40","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Retry","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Edit","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Copy","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":21,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Claude responded: They're independent buckets — with one shared bucket on top.","depth":22,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Analyzed independent rate limit buckets and their practical interactions","depth":22,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Analyzed independent rate limit buckets and their practical interactions","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"They're independent buckets — with one shared bucket on top.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"The three buckets and what each call hits","depth":24,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"The three buckets and what each call hits","depth":25,"on_screen":false,"role_description":"text"}]...
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Claude finished the response
You said: So just a solution for rate limit implementation.
You said: So just a solution for rate limit implementation.
So just a solution for rate limit implementation. The situation currently is that there are some daily and secondary limits for HubSpot. I would like to make sure I never reach a 429 error rate limit. The requests can come from any flow. It can be:
updating activity (engagement, meeting, call, note)
searching for a company or contact
updating deal
patching IDs
Review what the limit is at the moment in the HubSpot documentation and then think of the solution:
where to store it
how to read it
how to work with multiple jobs
how to work with paginated requests Let's consider a situation when there are 600 opportunities to sync. What would be the flow? How would the rate limit be recognized? How would it be handled? What are the potential issues? [API usage guidelines and limits - HubSpot docs](
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
https://developers.hubspot.com/docs/developer-tooling/platform/usage-guidelines
). Example of such a error Client error:
POST https://api.hubapi.com/crm/v3/objects/contact/search
resulted in a
429 Too Many Requests
response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT","correlationId":"019dffc4-4 (truncated...). Think carefully about the implementation and potential issue and bottlenecks.
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10:42
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Claude responded: Current HubSpot limits (Apr 2026)
Claude responded: Current HubSpot limits (Apr 2026)
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Synthesized HubSpot rate limit architecture with Redis storage and sliding window algorithms
Current HubSpot limits (Apr 2026)
Current HubSpot limits (Apr 2026)
For privately distributed apps (which is what Jiminny presumably uses with HubSpot), the limits are layered: a per-app burst window of 100/10s on Free/Starter, 190/10s on Pro/Enterprise, or 250/10s with the API Limit Increase add-on
, plus a per-account daily cap of 250k / 625k / 1M depending on tier — shared across all private apps in the account
. The burst window is per app; the daily quota is per portal.
hubspot
hubspot
hubspot
hubspot
The Search API is special: five requests per second per account, capped at 200 records per page, with a hard 10,000-result ceiling per query
. That's the limit the 429 in your example is hitting (
secondly limit
on
/crm/v3/objects/contact/search
). It's a separate bucket from the 190/10s, and critically, search responses do not include the
X-HubSpot-RateLimit-*
headers
— you can't read remaining capacity off the response, you have to track it yourself.
hubspot
hubspot
hubspot
hubspot
Non-search endpoints return
X-HubSpot-RateLimit-Remaining
,
-Max
, and
-Interval-Milliseconds
. The daily headers are not returned for OAuth-authenticated calls
, so for those you check the account-info endpoint or maintain your own counter. There's also a soft rule: errors should stay under 5% of total daily requests
— that's enforced for marketplace listing, but it's also a sane operational target.
hubspot
hubspot
hubspot
hubspot
So you have
four buckets
to track at minimum: app-burst (10s sliding), search-secondly (1s sliding), account-daily (24h fixed, midnight in HubSpot's TZ), and per-app daily share (your own budgeting on top of the account cap).
Where to store it
Where to store it
Redis. It's the only realistic option once you have multiple queue workers — DB-backed counters serialize too much, and in-process state can't coordinate across workers. Laravel already speaks Redis natively, and you get atomic
INCR
/
EXPIRE
plus Lua scripting for true CAS semantics.
Key layout I'd use:
Copy to clipboard
hubspot:rl:burst:{portalId}:{appId} ZSET (sliding 10s)
hubspot:rl:search:{portalId} ZSET (sliding 1s)
hubspot:rl:daily:{portalId} STRING + TTL to midnight TZ
hubspot:rl:meta:{portalId} HASH (last seen headers)
The two short-window buckets are sliding-window-log (Redis ZSET, score =
microtime
, member = unique request id). Lua script removes entries older than the window, counts remaining slots, and only adds the new one if there's room — all atomic. Fixed windows are simpler but allow 2× the limit at the boundary, which on a 5/s window is brutal.
The daily bucket is a plain
INCR
with TTL set to seconds-until-midnight in
HubSpot's account timezone
, not yours — Sofia is UTC+2/+3 but your portal might be set to US Eastern. Get this once and cache it.
How to read it
How to read it
Two-phase: optimistic pre-check, authoritative post-update.
Before a call, run the Lua acquire script. If it returns "denied," sleep until a slot frees up (the script can return ms-until-next-slot) or push the job back to the queue with a delay. Don't busy-loop.
After the call, parse
X-HubSpot-RateLimit-Remaining
/
-Max
/
-Interval-Milliseconds
and store them in
hubspot:rl:meta:{portalId}
. This is your reality check — if your local counter says 50 remaining but HubSpot's header says 5, you trust HubSpot and clamp your counter. This handles clock drift, missed accounting (e.g., crashed worker that took a token but never made the request), and other apps in the same account consuming the daily budget invisibly.
For search specifically, since headers don't come back, the local counter
is
the source of truth — meaning if you ever crash mid-flight, you've under-counted. Always release tokens on connection-level failure but
not
on 429 (you really did make that request).
How to work with multiple jobs
How to work with multiple jobs
The queue layer needs to enforce concurrency separately from the rate limiter. Both work together:
Concurrency cap
via
Queue::throttle()
or a Redis semaphore — limits how many sync workers run in parallel against HubSpot. Without this, you can have 50 workers all blocked waiting for tokens, which is wasteful and creates retry storms.
Per-tenant fairness
— if you sync many Jiminny customers into different HubSpot portals, each portal has its own bucket but you still want one slow portal not to starve others. Either separate queues per portal or a fair-share scheduler.
Priority lanes
— webhook-driven updates (user-visible latency) should outrank background batch syncs. Two queues:
hubspot-priority
and
hubspot-bulk
, with priority workers taking 70% of the burst budget and bulk taking 30% (enforce via separate sub-buckets if you really want hard separation, otherwise just pull from priority first).
Backoff on 429
— respect the
Retry-After
header. If absent, exponential with jitter (e.g.,
min(2^attempt * 250ms, 30s) ± 20%
). The jitter is non-negotiable; without it, simultaneous 429s retry in lockstep and you get thundering-herd 429s on retry.
How to work with paginated requests
How to work with paginated requests
The trap is treating "fetch all" as one logical operation. Each page is its own API call and competes for tokens with everything else.
Two practical rules:
Don't hold the worker idle while paginating.
If page N takes 500ms and page N+1 needs to wait 800ms for a token, you've burned 800ms of worker time doing nothing. Instead, fetch page N, dispatch the
processing
of page N as a separate job, and queue a "fetch page N+1" job with a delay equal to the wait time. Each page becomes its own atomic unit.
Always batch where HubSpot offers it.
POST /crm/v3/objects/{type}/batch/{read|update|create}
accepts up to 100 IDs per call. For your "patching IDs" flow this is the difference between 600 calls and 6.
Walkthrough: 600 opportunities
Walkthrough: 600 opportunities
Naive flow (one PATCH per deal): 600 calls. At 190/10s that's ~32s of API time, well under daily. You'd hit burst easily without throttling. Plus likely 1-3 search calls upfront and N association calls.
Sane flow:
Identify deltas
— if you can avoid Search at all, do. Use
lastmodifieddate
filter on a single search if you must, paginate at limit=200. For 600 deals that's 3 search calls @ 5/s = ~600ms naturally throttled.
Batch read
current state —
POST /crm/v3/objects/deals/batch/read
with 100 IDs per call → 6 calls. Burst weight 6.
Compute diff
in your code (no API).
Batch update
—
POST /crm/v3/objects/deals/batch/update
with 100 per call → 6 calls.
Associations
—
POST /crm/v4/associations/{from}/{to}/batch/create
if needed → another few batch calls.
Total: ~15-20 API calls for 600 deals. Burst budget consumed: 20/190 over ~5s. Daily impact: trivial.
Recognition: pre-check denies if
<weight>
slots aren't free; on 429 the response surfaces
policyName
(DAILY/SECONDLY) — log it, push the job back with
Retry-After
delay, increment a metric so you can alarm on sustained 429 rate.
Pitfalls & bottlenecks worth pre-empting
Pitfalls & bottlenecks worth pre-empting
Daily quota is shared across the whole portal
, including any n8n flows, other private apps, marketing automation calling APIs, etc. Budget for ~70-80% of the documented limit, not 100%. Add an internal per-app daily cap so a runaway sync can't starve other apps.
Search is uniquely fragile
: separate 5/s bucket, no headers to read, 10k-result cap per query. If you ever hit 10k+ deals matching a filter, partition by
hs_object_id
ranges or by
lastmodifieddate
windows.
Retry storms after HubSpot incidents
— always jitter, always cap total retries (e.g., 5 attempts, then dead-letter).
Webhook → sync → webhook loops
— when your update fires a HubSpot webhook that triggers another sync. Tag your own writes (e.g., a custom property
jy_last_sync_id
) and ignore webhooks where it just changed.
Token refresh
— OAuth refresh itself counts against burst. Cache the access token in Redis with TTL =
expires_in - 60s
, single-flight the refresh (only one worker refreshes; others wait on a lock).
Search latency for fresh writes
— newly created/updated objects don't appear in search instantly. Don't write-then-search; use returned IDs directly.
Clock skew
— Redis is authoritative. Don't use
time()
from each worker for window scoring; use
redis.call('TIME')
inside the Lua script.
Dead workers with held tokens
— sliding-window-log handles this naturally because tokens expire by score; token-bucket implementations need explicit release-on-crash logic.
The 5% error rule
counts every 429 toward your error budget, even successfully retried ones. If your pre-check is working well, 429s should be near zero — if they're not, your pre-check is wrong, not just slow.
Phantom contention with Laravel
RateLimited
middleware
: it's per-job-class by default, not per-portal. If your
SyncDealJob
and
UpdateActivityJob
are different classes both calling HubSpot, they don't share a Laravel-level limiter — you need a single
HubspotRateLimiter
service that everything routes through.
If you want, I can sketch the Lua script for the sliding-window acquire and the Laravel service wrapper around it.
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You said: What will happen if there are two different types of rate limits?
You said: What will happen if there are two different types of rate limits?
What will happen if there are two different types of rate limits?
Search requests that have 5 requests per second
The other rate limit that has, let's say, 100 requests per 10 seconds How do these work together? Is there some conflict? Can I reach the limit with one request and block either as well, or are these separated? Can I still continue making search requests once I hit the normal requests limits?
13:40
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Claude responded: They're independent buckets — with one shared bucket on top.
Claude responded: They're independent buckets — with one shared bucket on top.
Analyzed independent rate limit buckets and their practical interactions
Analyzed independent rate limit buckets and their practical interactions
They're independent buckets — with one shared bucket on top.
The three buckets and what each call hits
The three buckets and what each call hits...
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