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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.
Show more
10:42
Edit
Copy
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 hav
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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.
Show more
10:42
Edit
Copy
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 (slidi
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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.
Show more
10:42
Edit
Copy
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 t
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
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HubSpot rate limit implementation strategy, rename chat
HubSpot rate limit implementation strategy
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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
Edit
Copy
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
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
|
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|
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HubSpot rate limit implementation strategy, rename chat
HubSpot rate limit implementation strategy
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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
Edit
Copy
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
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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
Edit
Copy
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 me
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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
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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
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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
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
|
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|
Claude
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Share chat
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
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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
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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
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Switch to Claude Code and let Claude work directly in your repo, running and testing as it goes.
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
|
Claude
|
Claude
|
NULL
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|
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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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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
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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
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Retry
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Switch to Claude Code and let Claude work directly in your repo, running and testing as it goes.
Open Claude Code
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Model: Opus 4.7 Adaptive
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Settings
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
|
Claude
|
Claude
|
NULL
|
|
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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.
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
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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
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Share chat
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
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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
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|
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|
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Share chat
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
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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
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Claude is AI and can make mistakes. Please double-check responses....
|
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|
Claude
|
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Share chat
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
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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
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Claude is AI and can make mistakes. Please double-check responses....
|
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|
Claude
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HubSpot rate limit implementation strategy, rename chat
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More options for HubSpot rate limit implementation strategy
Share chat
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
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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
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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
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Claude is AI and can make mistakes. Please double-check responses.
Claude is AI and can make mistakes. Please double-check responses....
|
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|
Claude
|
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More options for HubSpot rate limit implementation strategy
Share chat
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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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
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelp(ahlSupport Daily - in 4h 11 m100%8APP (-zsh)DOCKERDEV (-zsh)₴2APP (-zsh)*3-zshcreatemode100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreatemode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_.createmode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.jscreatemode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreatemode100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.jscreat~1AAGAA GuantcreCrecreCreCr€PS3creCrecreCr€Slackcrea-createmode 100644resources/viens/emails/reports/rsport-noty.eneratse.0irde. phlade- phecreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644 tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phplukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll1es om ecofd ngoutcona aerteo ertet .pho• ₴4screenpipe"Thu 7 May 10:49:56181• ₴5|APP31...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev8 Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)suppont Dally• In4h 11m100% 12Inu / May 10.49:0/+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 6425vner id THEN ' (owner)' ELSE !I END) AS user id11d='salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
Channel
HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi...6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev8 Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗузползвали този за QAIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)• suppont Dally • In 4h 10m100% 12Inu / May 10:00-20+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 042vner id THEN ' (owner)' ELSE !I END) AS user id11d= 'salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
Channel
iTerm2ShellEditViewSessionScriptsProfilesWindowHelp> 0all= Support Daily - in 4 h 10 m100% <478APP (-zsh)DOCKER• ₴1DEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:50:29T₴1• *5APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)• suppont Dally • In 4h 10m100% 12Inu / May 10:00:0%+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 6425vner id THEN ' (owner)' ELSE !I END) AS user id11d='salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelp> 0all= Support Daily - in 4 h 10 m100% <478APP (-zsh)DOCKER• ₴1DEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:50:59T₴1• *5APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil Vasilev8 James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)suppont Dally• In4n gm100% 12Thu 7 May 10:51:30+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 6425vner id THEN ' (owner)' ELSE !I END) AS user id11d='salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Nikolay Yankov
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Ves
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Nikolay Ivanov
Lukas Kovalik
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelp• Support Daily - in 4 h 9 m100% <478APP (-zsh)DOCKER• ₴1DEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:51:30T₴1• 85APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)suppont Dally • In4n om100% 12Inu / May 10:02-01+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 6425vner id THEN ' (owner)' ELSE !I END) AS user id11d='salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
React with white_check_mark
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
Channel
iTerm2ShellEditViewSessionScriptsProfilesWindowHelp• Support Daily - in 4 h 8 m100% <478APP (-zsh)DOCKER• ₴1DEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:52:01T₴1• 85APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
React with white_check_mark
React with eyes
React with raised_hands
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya Dimitrovaf Aneliya AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)suppont Dally • In4n om100% 12Inu / May 10:02-3%+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 042vner id THEN ' (owner)' ELSE !I END) AS user id11d= 'salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelp• Support Daily - in 4 h 8 m100% <78APP (-zsh)DOCKER• ₴1DEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:52:32T₴1• 85APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya Dimitrovaf Aneliya AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)supoont Dally • In4h /m100% 12Inu / May 10:03.04+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 042vner id THEN ' (owner)' ELSE !I END) AS user id11d= 'salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Nikolay Yankov
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Ves
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Nikolay Ivanov
Lukas Kovalik
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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iTerm2ShellEditViewSessionScriptsProfilesWindowHelplihlSupport Daily - in 4 h 7 m100% <78APP (-zsh)DOCKERDEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmle-rtsPormo. s-reports-promo.output.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644create mode 100644public/pdf/exec-reports/eu/loss-report.pdfpublic/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:53:03T₴1• 85APP...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil VasilevS James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)supoont Dally • In4h /m100% 12Inu / May 10:03.38+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 6425vner id THEN ' (owner)' ELSE !I END) AS user id11d='salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
React with white_check_mark
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
Also send as direct message
Channel
iTerm2ShellEditViewSessionScriptsProfilesWindowHelplihlSupport Daily - in 4 h 7 m100% <78APP (-zsh)DOCKERDEV (-zsh)₴2APP (-zsh)*3-zshcreatemode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.phpcreatemode100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.jscreate mode100644 front-end/src/apps/ai-reports-promo.jscreatemode100644 front-end/src/components/AiReports/AiReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vuecreatemode100644front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vuecreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests_./AutomatedReportsPromo.spec.jscreatemode100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.htmle/tsPromoes-reports-promo.utput.htmlcreatemode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vuecreate mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.jscreatemode 100644front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.htmlcreate mode 100644front-end/src/components/Settings/Kiosk/modals/EditTeamModal/.__tests__/EditTeamModal.spec.jscreate mode 100644front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/__tests_/HelpMenu.spec.jscreate mode100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.jscreate mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.jscreate mode100644 front-end/src/store/modules/platform/__tests_/getters.spec.jscreate mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdfcreate mode100644 public/pdf/exec-reports/com/exec-summary.pdfcreate mode100644 public/pdf/exec-reports/com/loss-report.pdfcreate mode100644 public/pdf/exec-reports/com/product-feedback.pdfcreate mode100644 public/pdf/exec-reports/eu/coaching-profiles.pdfcreate mode 100644public/pdf/exec-reports/eu/exec-summary.pdfcreate mode 100644public/pdf/exec-reports/eu/loss-report.pdfcreate mode 100644public/pdf/exec-reports/eu/product-feedback.pdfcreate mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.phpcreate mode 100644 resources/views/emails/reports/report-not-generated.blade.phpcreate mode100644tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.phpcreate mode100644tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.phpcreate mode100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/EndedTest.phpcreate mode100644tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.phpcreate mode100644 tests/Unit/Events/Activities/Softphone/StartedTest.phpcreate mode100644tests/Unit/Http/Transformers/PartnerTransformerTest.phpcreate mode100644tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.phpcreate mode 100644tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.phpcreate mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.phpcreate mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.phpcreate mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.phpcreate mode 100644 tests/Unit/Models/PartnerTest.phpcreate mode 100644 tests/Unit/Services/ActivityServiceTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/Recording0utcomeTextResolverTest.phpcreate mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.phpLukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pulll• ₴4screenpipe"Thu 7 May 10:53:34T₴1• *5APP...
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Ves (DM) - Jiminny Inc - 3 new items - Slack
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Aneliya Angelova
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Nikolay Yankov
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Steliyan Georgiev
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Nikolay Ivanov
Lukas Kovalik
you
Toast
Jira Cloud
Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
React with white_check_mark
React with eyes
React with raised_hands
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
Also send as direct message
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HomeActivityFilesLaterMoreSlackcalVIewJiminny ...i contusion-clinic# curiosity_lab# engineering# general#jiminny-bgic olattorm-nckets# product launches*random# releases# sofia-officei suoport# thank-yous# the people of iimi..6 Direct messages3 Aneliva Angelova, ...2o Stoyan Tanev& Stefka Stovanovao VesGalya DimitrovaAneliva AngelovaVasil Vasilev8 James GrahamNikolay Ivanove Lukas Kovali.::: Apps8 ToastSii lira CloudmistonWindowHelp< Describe wnat you are looking foru geratouie inck / cxrike pius cua seripung ortrueThread Vesами не знам тогава, не оаботи на одтpostmark и видях че няма добавен serverлобавих го, но може ои беше направенопрез staging, ще го видя още ведньжZSET (sliding 10s)Ves Aor 28th at 6:48 PMвиля ли в Circle env? (edited)ZSET (sliding 1s)STRING + TTL to midnight TZHASH (last seen headers)nage.ongyxxxxb62biding-window-log (kedis zsbl, score = microtime,ript removes entries older than the window, countsw one if there's room - all atomic. Fixed windows areoundary, which on a 5/s window is brutal.Lukas Kovalik' Apr 28th at 6:52 PMами то изглежла е ОдUuur serto seconas-unu-mianicoun hudsdorsage.png +is UTC+2+3 but your portal might be set to US Eastern.nonrauve pos ruddare.pt. If it returns "denied," sleep until a slot frees up (theor push the job back to the queue with a delay. Don'tVes Aor 28th at 6•54 PMизглежла е нямало OAi nostmark и смеЗизполавали този за ОДIimit-Remainino -Max -Interval -Miliaseconds{portalld}. This is vour reality check - if vour locaсмени го в crсe с enу на новия токенкойто си напоавил editedpot's header says 5, you trust Hubspot and clamp yoursed accounting (e.g. crashed worker that took a token butReplv.ops in the same account consuming the daily budget(E1Also send as direct messageAadon't come back. the local counter is the source of truthht, vou've under-counted. Always release tokens onD9 (vou reallv did make that request).How to work with multiple jodsThe queue laver needs to enforce concurrency senarately from the rate limiter. Both worktooether.Keep going in Claude CodeSwitch to Claude Code and let Claude work directiv in vour reno..running and testing as it goes.Write a message…Opus 4.7 Adaptive vClaude ic Aland can mako mistakes Plesce double-chock racnoncac)suppont Dally • In4n om100% 12Thu 7 May 10:54:04+0 ..& ho local uiminny@localnost« console [PROD] XA console [EU]dojiminnyWHERE id = 1919;037 A1 A35 V63 ^WHERE report id = 54;= 7594349:6Les%': # 711, 692, [EMAIL]= 711; # event 226147RE playbook id = 5515:1taguracion 10 = o%2 ano obnect cype ='evencn26147:irm T1eld 10 = 22614/*P10 = 042vner id THEN ' (owner)' ELSE !I END) AS user id11d= 'salesforce';ans u 1.n<->1: on u.id = co.user id WHERE u.team 1d = 711÷brovider id, '@', -1)) AS calendar domaint.idAND c.status = 'active' AND c.calendar provider id LIKE '%0%'VDEX(c.calendar_provider_id. '@'. -1))c1<->l.n: on c.user id e u.id049485: # team 563 crm 537272382• # toam 563 com 537CascadeHubspot Rate Limite1. Contiquration already implements RateLimited and already has rateLimits morph - works for Hubspot contia rows the moment we seed2. Hubspot's quotas are a pertect tit: a secondly burst + a dally limit. The RateLimited contract returns a collection of limits, so multiple tiers perstep 1 - Inect the limier into huos pot culentMirror Salesforce Client:Mohdpublic functionProviderRateLimiter SrateLimiter,SocialAccountService SsocialAccountService.Sthis->rateLimiter = SrateLimiter:The Configuration is already available on Client via $this->configStep 2 - Centralize the HTTP gateHubspot calls today go through several places: the SDK (getinstance), getPaqinatedDataGenerator, makeRequest, raw Guzzle in searchCallByRecordingURLToken, and the batchApi SDK in bulkAddPlaybackURLToDescriptionRequest. A rate limiter is only useful if every outbound call passesRecommended: add a single private executeRequest(callable $apiCall) on Client that does:private function executeRequest(callable $apiCall)sthis-sensureValidToken/)if(isthis-srateLimiter->canMakeRequest(sthis->confio))<SwaitSeconds = Sthis->rateLimiter->requestAvailableIn(Sthis->config):→ schis→>contig->ceam 10,throw new RateLimitException("HubSpot rate limit hit; retry in {SwaitSeconds}s", SwaitSeconds):sthis->rateLimiter->incrementRequestcount(sthis->cont1a=try {} catch (ApiException se) {if (Se->getCode() === 429) ^CretrvAfter = Cthic-snarceRetrvAfter(se): // X_HubSoot_Patel imit-* / RetrvcAfterthrow se:Ask anvthina (*4L)...
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Lukas Kovalik
Apr 28th at 5:36:08 PM
Apr 28th at 5:36 PM
исках да те питам credentials на AWS. Направих server на постмарк за QAI но не знам как да добавя key, май вече не е през env. Има ли някакви инструкции?
12 replies
Ves
Apr 28th at 6:33:30 PM
Apr 28th at 6:33 PM
в circle ci има такъв ключ
Apr 28th at 6:33:31 PM
6:33
[URL_WITH_CREDENTIALS] cat .env | grep POST
[ENV_SECRET]
Apr 28th at 6:45:40 PM
6:45
ето и стойността в момента на QAi
Lukas Kovalik
Apr 28th at 6:46:38 PM
Apr 28th at 6:46 PM
ами не знам тогава, не работи на QAI postmark и видях че няма добавен server
Apr 28th at 6:47:18 PM
6:47
добавих го, но може би беше направено през staging, ще го видя още веднъж
Ves
Apr 28th at 6:48:41 PM
Apr 28th at 6:48 PM
видя ли в Circle env?
(edited)
Apr 28th at 6:50:17 PM
6:50
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Lukas Kovalik
Apr 28th at 6:52:54 PM
Apr 28th at 6:52 PM
ами то изглежда е QA
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Ves
Apr 28th at 6:54:23 PM
Apr 28th at 6:54 PM
изглежда е нямало QAi postmark и сме използвали този за QA
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Apr 28th at 6:54:26 PM
6:54
смени го в Circle CI env на новия токен който си направил
(edited)
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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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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
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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
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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
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Share chat
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:
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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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<?php
namespace Jiminny\Http\Controllers\API;
use Carbon\Carbon;
use ChaseConey\LaravelDatadogHelper\Datadog;
use Exception;
use Illuminate\Auth\Access\AuthorizationException;
use Illuminate\Database\Eloquent\Builder;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Illuminate\Support\Collection;
use Illuminate\Support\Facades\Log;
use Illuminate\Validation\Rule;
use Illuminate\Validation\Rules\In;
use Illuminate\Validation\ValidationException;
use InvalidArgumentException;
use Jiminny\Component\ActivityAnalytics;
use Jiminny\Component\ActivitySearch;
use Jiminny\Component\ActivitySearch\FilterDefinitionCollection;
use Jiminny\Component\PlaybackPage\Comments\Services\ActivityCommentService;
use Jiminny\Component\Queue\Constants;
use Jiminny\Contracts\ES\Events\UpdateSingleEntity;
use Jiminny\Contracts\ES\UpdateTargetEnum;
use Jiminny\Contracts\Nudge\NudgeFactoryInterface;
use Jiminny\Contracts\Playlist\PlaylistTrackFactoryInterface;
use Jiminny\Contracts\Repositories\PlaylistActivityRepository;
use Jiminny\Contracts\Services\Crm\ServiceInterface;
use Jiminny\Enums\TeamSetting;
use Jiminny\Events\Activities\AiAutomation\ActivityProspectAdded;
use Jiminny\Events\Activities\Coaching\Coached;
use Jiminny\Contracts\Services\Crm\SupportsObjectTypeParseInterface;
use Jiminny\Exceptions\LogicException;
use Jiminny\Exceptions\SocialAccountTokenInvalidException;
use Jiminny\Http\Controllers\API\BaseController as Controller;
use Jiminny\Http\Controllers\CommentContextInterface;
use Jiminny\Http\Responses\Api\AbstractResponse;
use Jiminny\Http\Responses\Api\Response;
use Jiminny\Http\Serializers\JsonSerializer;
use Jiminny\Http\Transformers\ActivityCommentTransformer;
use Jiminny\Http\Transformers\ActivityTopicTriggerTransformer;
use Jiminny\Http\Transformers\ActivityTransformer;
use Jiminny\Http\Transformers\AvailabilityNotificationTransformer;
use Jiminny\Http\Transformers\CoachingFeedbackTransformer;
use Jiminny\Http\Transformers\CoachingSectionsTransformer;
use Jiminny\Http\Transformers\SearchTransformer;
use Jiminny\Http\Transformers\StatsTransformer;
use Jiminny\Jobs\Crm\SaveActivity;
use Jiminny\Jobs\Crm\UpdateStage;
use Jiminny\Jobs\Telephony\StartRecording;
use Jiminny\Jobs\Telephony\StopRecording;
use Jiminny\Jobs\Telephony\ToggleRecording;
use Jiminny\Models\Account;
use Jiminny\Models\Activity;
use Jiminny\Models\Activity\CoachRequest;
use Jiminny\Models\Activity\Comment;
use Jiminny\Models\Activity\Search;
use Jiminny\Models\Activity\SearchFilter;
use Jiminny\Models\Activity\Share;
use Jiminny\Models\CoachingFeedback;
use Jiminny\Models\CoachingSection;
use Jiminny\Models\CoachingSectionCriterion;
use Jiminny\Models\CoachingSectionFeedback;
use Jiminny\Models\Contact;
use Jiminny\Models\Crm\Field;
use Jiminny\Models\Crm\FieldData;
use Jiminny\Models\Crm\Layout;
use Jiminny\Models\Crm\LayoutEntity;
use Jiminny\Models\Feature\FeatureEnum;
use Jiminny\Models\LanguageDialect;
use Jiminny\Models\Lead;
use Jiminny\Models\Nudge;
use Jiminny\Models\PlaybookCategory;
use Jiminny\Models\Playlist;
use Jiminny\Models\Stage;
use Jiminny\Models\Team;
use Jiminny\Models\Track;
use Jiminny\Models\User;
use Jiminny\Repositories\CoachingFeedbackRepository;
use Jiminny\Repositories\ElasticActivityRepository;
use Jiminny\Repositories\TeamRepository;
use Jiminny\Rules\CrmReference;
use Jiminny\Rules\MultidimensionalArrayMaxCharRule;
use Jiminny\Services\ActivityService;
use Jiminny\Services\Crm\ProviderRegistry;
use Jiminny\Services\PlaybackService;
use Jiminny\Services\UserService;
use Jiminny\VO\Repository\OnDemandActivitySearch\Criteria;
use Psr\Log\LoggerInterface;
use Ramsey\Uuid\Uuid;
use Sentry;
use Symfony\Component\HttpFoundation;
final class ActivityController extends Controller implements CommentContextInterface
{
// Number of minutes to look back on activities. i.e. a timeout on activity duration.
private const int LOOK_BACK = 180;
public function __construct(
private ProviderRegistry $providerRegistry,
private ActivityService $activityService,
Response $response,
private UserService $userService,
private ActivitySearch\Service\ActivitySearch $activitySearch,
private NudgeFactoryInterface $nudgeFactory,
private ActivityCommentService $activityCommentService,
private LoggerInterface $logger,
private readonly CoachingFeedbackRepository $coachingFeedbackRepository,
private readonly TeamRepository $teamRepository,
) {
parent::__construct($response);
}
public static function getCommentImplementation(): string
{
return Comment::class;
}
public function delete()
{
$this->request->validate([
'*' => 'uuid:activities',
]);
$deletedIds = [];
foreach ($this->request->all() as $activityId) {
$activity = Activity::idOrUuId($activityId);
try {
if ($this->authorize('delete', $activity)) {
$activity->delete();
$deletedIds[] = $activityId;
\Log::info('Soft deleted activity ' . $activity->id_string . ' by user ' . $this->getUser()->id);
}
} catch (AuthorizationException $authorizationException) {
// They didn't have permission.
}
}
return $this->response->withArray($deletedIds);
}
public function update(Request $request, Activity $activity)
{
$this->authorize('updateMetadata', $activity);
$request->validate([
'title' => 'string|max:250',
'category_id' => 'uuid:playbook_categories',
'language' => [
new In(
LanguageDialect::query()
->with('language')
->cursor()
->map(static function (LanguageDialect $languageDialect): string {
return $languageDialect->getLanguageLocale();
})
->all()
),
],
]);
if ($request->has('title')) {
$activity->title = $request->input('title');
}
if ($request->has('category_id')) {
$category = PlaybookCategory::uuid($request->input('category_id'));
if ($category->playbook->team_id !== $request->user()->team_id) {
return $this->response->errorNotFound('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
if ($request->has('language')) {
if (! $activity->isInProgress()) {
return $this->response->withError(
'Activity language can only be set while the meeting is in progress.',
400
);
}
$activity->setLanguageCode($request->input('language'));
}
$activity->save();
return $this->response->withOk();
}
// XXX: This should be merged with the update method.
/**
* @param Activity $activity
*
* @throws AuthorizationException
* @throws SocialAccountTokenInvalidException
*
* @return mixed
*/
public function summarize(Activity $activity): mixed
{
$this->logger->info('[Log Activity] Summarizing activity ', [
'activityId' => $activity->getUuid(),
'payload' => $this->request->all(),
]);
$this->authorize('update', $activity);
$this->logger->info('[Log Activity] Validating summary');
// Validate the payload.
$this->validateSummary($activity);
// All objects must belong to this team.
/** @var User $user */
$user = $this->request->user();
$team = $user->getTeam();
$crmService = $this->providerRegistry->get($team->crm->provider);
try {
$crmUser = $user;
if ($user->isCrmRequired() === false) {
$crmUser = $team->owner;
}
$crmService->setUser($crmUser);
} catch (SocialAccountTokenInvalidException $accountTokenInvalidException) {
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($accountTokenInvalidException->getMessage());
}
$rawEntities = $this->request->input('entities');
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid(
$this->request->input('layout_id')
);
// Delay execution of CRM jobs to avoid locking issues.
$jobDelay = 0;
// If we have arrived from a notification, mark it as read.
$notificationId = $this->request->input('nId');
if ($notificationId) {
$notification = $user->unreadNotifications->where('id', $notificationId)->first();
if ($notification) {
$notification->markAsRead();
}
}
$title = $this->request->input('title');
$prospects = $this->request->input('prospects');
$opportunityId = $this->request->input('opportunity_id');
$stageId = $this->request->input('stage_id');
$categoryId = $this->request->input('category_id');
$summary = $this->request->input('summary');
$crmProviderId = $this->request->input('crm_id');
$isInternal = $this->request->input('is_internal') ?? false;
$lead = null;
$category = null;
$account = null;
$contact = null;
$opportunity = null;
$stage = null;
$callStage = null;
foreach ($prospects as $prospectData) {
$objectId = $prospectData['id'];
if ($objectId === null) {
continue;
}
$objectType = $prospectData['type'];
$this->logger->info('debug', ['prospect_data' => $prospectData]);
try {
if ($objectType === null) {
$this->logger->info('no object type');
if ($crmService instanceof SupportsObjectTypeParseInterface) {
$objectType = $crmService->parseObjectType($objectId);
}
}
switch ($objectType) {
case 'lead':
$this->logger->info('Processing lead');
/** @var Lead|null $lead */
$lead = $team->crm->leads()->where('crm_provider_id', $objectId)->first();
// Lead does not exist locally, import it.
if ($lead === null) {
$this->logger->info('Lead does not exist locally');
/** @var Lead $lead */
$lead = $crmService->syncLead($objectId);
}
$this->logger->info('Lead found', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
if ($stageId === null) {
$this->logger->info('Stage ID is null');
// If it was not provided, just assume it is the current stage.
$callStage = $lead->stage;
break;
}
$this->logger->info('Looking for stage');
// Determine if they have changed the stage.
/** @var Stage $stage */
$stage = $team->crm->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_LEAD)
->firstOrFail();
$this->logger->info('Stage found', ['stageId' => $stage->id, 'lead_stage' => $lead->stage_id]);
if ($lead->stage_id && $lead->stage_id !== $stage->id) {
$this->logger->info('Stage has changed');
// Storage current stage on activity.
$callStage = $lead->stage;
// The stage has changed, update in remote CRM.
dispatch(new UpdateStage($activity, $lead, $callStage, $stage));
$this->logger->info(
sprintf(
'[%s] User changing lead stage from %s to %s',
$crmService->getDisplayName(),
$callStage->getName(),
$stage->getName()
),
[
'user' => $user->getUuid(),
'lead' => $lead->getUuid(),
]
);
} else {
$this->logger->info('Stage has not changed');
// Stage remains as current.
$callStage = $stage;
}
break;
case 'account':
$this->logger->info('Processing account');
// If the object is not a lead, it should be an account.
$account = $team->crm->accounts()->where('crm_provider_id', $objectId)->first();
// Account does not exist locally, import it.
if ($account === null) {
$this->logger->info('Account does not exist locally');
$account = $crmService->syncAccount($objectId);
}
$this->logger->info('Account found', ['accountId' => $account->id]);
break;
case 'contact':
$this->logger->info('processing contact');
$contact = $team->crm->contacts()->where('crm_provider_id', $objectId)->first();
// Contact does not exist locally, import it.
if (! $contact instanceof Contact) {
$this->logger->info('contact does not exist locally');
$contact = $crmService->syncContact($objectId);
}
$this->logger->info('resolving account');
$account = $this->resolveAccount($team, $contact, $crmService, $prospects);
break;
}
// If they have specified an opportunity, retrieve this with stage.
if ($opportunityId) {
$this->logger->info('opportunity id is set');
$opportunity = $team->crm->opportunities()->where('crm_provider_id', $opportunityId)->first();
// Opportunity does not exist locally, import it.
if ($opportunity === null) {
$this->logger->info('opportunity does not exist locally');
$opportunity = $crmService->syncOpportunity($opportunityId);
}
if ($stageId === null) {
$this->logger->info('stage id is null');
// If it was not provided, just assume it is the current stage.
$callStage = $opportunity->stage ?? null;
} else {
$this->logger->info('looking for stage');
/** @var ?Stage $opportunityStage */
$opportunityStage = $team->crm
->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_OPPORTUNITY)
->first();
// There is a chance we still cannot import this opportunity.
if ($opportunityStage !== null && $opportunity !== null && $opportunity->stage_id !== $opportunityStage->id) {
$this->logger->info('opportunity stage has changed');
// Storage current stage on activity.
$callStage = $opportunity->stage;
dispatch(new UpdateStage($activity, $opportunity, $callStage, $opportunityStage));
$this->logger->info(
sprintf(
'[%s] User changing opportunity stage from %s to %s',
$crmService->getDisplayName(),
$callStage->name,
$opportunityStage->name
),
[
'userId' => $user->id_string,
'opportunityId' => $opportunity->id_string,
]
);
} else {
$this->logger->info('opportunity stage has not changed');
// Stage remains as current.
$callStage = $opportunityStage;
}
}
}
if ($crmProviderId) {
// Cast $crmProviderId to string otherwise it won't use database index for some records
$linkedActivity = Activity::where('crm_provider_id', (string) $crmProviderId)->first();
// Check if this activity has already been assigned to a different activity.
if ($linkedActivity && $linkedActivity->id !== $activity->id) {
throw new InvalidArgumentException(
'Sorry, the linked task has already been logged under a different call. '
. 'Please choose another linked task.'
);
}
}
} catch (InvalidArgumentException $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($exception->getMessage());
} catch (Exception $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorInternalError(
'Sorry, an error occurred. Please try again or reach out to support if the problem continues.'
);
}
}
if ($categoryId) {
$category = PlaybookCategory::uuid($categoryId);
if ($category->playbook->team_id !== $team->id) {
throw new InvalidArgumentException('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
$this->logger->info('Prospect data', [
'lead_id' => $lead?->getId(),
'account_id' => $account?->getId(),
'contact_id' => $contact?->getId(),
'opportunity_id' => $opportunity?->getId(),
'stage_id' => $stage?->getId(),
]);
if ($title) {
$activity->title = $title;
}
if ($summary) {
$activity->summary = $summary;
}
if ($crmProviderId) {
$activity->crm_provider_id = $crmProviderId;
}
if ($callStage) {
$this->logger->info('Setting stage id', ['stageId' => $callStage->id]);
$activity->stage_id = $callStage->id;
}
if ($lead) {
$this->logger->info('Setting lead id', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
// If we are changed from an account > lead, unset the account data.
$this->logger->info('Unsetting account id, opportunity id, contact id, value');
$activity->account_id = null;
$activity->opportunity_id = null;
$activity->contact_id = null;
$activity->value = null;
}
if ($account) {
$this->logger->info('Setting account id', ['accountId' => $account->id]);
$activity->account_id = $account->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('unsetting lead id');
$activity->lead_id = null;
// Unset the contact if switching different accounts. Will be set up below if still applicable.
if (! $team->hasFeature(FeatureEnum::LINK_ACTIVITY_TO_MULTIPLE_PROSPECTS) || empty($contact)) {
$this->logger->info('Unsetting contact id');
$activity->contact_id = null;
}
}
if ($opportunity) {
$this->logger->info('setting opportunity id', ['opportunityId' => $opportunity->id]);
$this->logger->info('unsetting lead id');
$activity->opportunity_id = $opportunity->id;
$activity->value = $opportunity->value;
// If we are changed from an lead > account, unset the lead data.
$activity->lead_id = null;
}
if ($contact) {
$this->logger->info('setting contact id', ['contactId' => $contact->id]);
$activity->contact_id = $contact->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('Unsetting lead id');
$activity->lead_id = null;
}
$activity->is_internal = $isInternal;
$activity->save();
$activity->refresh();
$this->logger->notice('Activity saved', [
'activity_id' => $activity->getId(),
'lead_id' => $activity->lead_id,
'account_id' => $activity->account_id,
'contact_id' => $activity->contact_id,
'opportunity_id' => $activity->opportunity_id,
'stage_id' => $activity->stage_id,
'crm_provider_id' => $activity->getCrmProviderId(),
]);
// Store entities as field data on the activity.
$updatedData = $this->storeEntities($crmService, $activity, $layout, $rawEntities);
if ($activity->isLoggable()) {
// Follow-up Task or Event data.
$followupData = $this->fetchFollowupEntities($crmService, $layout, $rawEntities);
$this->logger->info('CRM LOG manual log triggered', [
'activityId' => $activity->getUuid(),
'followupData' => $followupData,
'userId' => $user->getUuid(),
]);
// Store data in the CRM.
// ++add check for crm_required
$job = new SaveActivity($activity, $followupData);
if ($updatedData) {
$job->delay(Carbon::now()->addMinutes($jobDelay));
}
dispatch($job);
// Manually dispatch log for Opportunity or Prospect added
if ($activity->hasOpportunity() || $activity->hasProspect()) {
event(new ActivityProspectAdded(
activity: $activity,
eventSource: 'manually-log-crm-data'
));
}
}
return $this->response->withOk();
}
/**
* Extract any activity data to be upserted in the Lead/Opportunity/Task etc in the CRM.
*
* @param ServiceInterface $service
* @param Activity $activity
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function storeEntities(ServiceInterface $service, Activity $activity, Layout $layout, array $entities): array
{
$updatedData = [];
$existingData = $activity->data()->get();
// We need to delete any existing data to overwrite with latest values.
$activity->data()->delete();
$layoutEntities = $layout->entities()
->with('field', 'parent')
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->get();
/** @var LayoutEntity $entity */
foreach ($layoutEntities as $entity) {
// If the user has provided a value for this entity
if (array_key_exists($entity->id_string, $entities)) {
$value = $entities[$entity->id_string];
// Convert raw data into values that the CRM can consume.
if ($value) {
$value = $service->normalizeValue($entity->field->type, $value);
}
// Check the field is part of the activity-summary section.
if ($entity->parent && $entity->parent->label === 'activity-summary' && $value) {
// This is the internal database ID, not the external CRM ID.
$objectId = null;
switch ($entity->field->object_type) {
case Field::OBJECT_ACCOUNT:
$objectId = $activity->account_id;
break;
case Field::OBJECT_CONTACT:
$objectId = $activity->contact_id;
break;
case Field::OBJECT_OPPORTUNITY:
$objectId = $activity->opportunity_id;
break;
case Field::OBJECT_LEAD:
$objectId = $activity->lead_id;
break;
case Field::OBJECT_TASK:
case Field::OBJECT_EVENT:
$objectId = $activity->id;
break;
}
if ($objectId) {
/** @var FieldData $data */
$data = $activity->data()->create([
'crm_layout_entity_id' => $entity->id,
'crm_field_id' => $entity->crm_field_id,
'object_type' => $entity->field->object_type,
'object_id' => $objectId,
'value' => $value,
]);
// Never send read-only field data to the CRM.
if ($entity->read_only === false && $entity->is_visible) {
$existingValue = $existingData
->where('crm_layout_entity_id', $entity->id)
->where('crm_field_id', $entity->crm_field_id)
->where('object_type', $entity->field->object_type)
->where('object_id', $objectId)
->first();
// If the field was actually changed, we need to reflect this in the CRM too.
if ($existingValue === null || $existingValue->value !== $value) {
$updatedData[] = $data->id;
}
}
}
}
}
}
return $updatedData;
}
/**
* Extract any followup data to be dispatched in a job to create a new Task/Event in the CRM.
*
* @param ServiceInterface $crmService
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function fetchFollowupEntities(ServiceInterface $crmService, Layout $layout, array $entities): array
{
$fieldData = [];
foreach ($entities as $entityId => $value) {
// Only bother with fields that have a value.
if ($value) {
// Extract the entity from the UUID. Check the field is valid and part of the follow-up section.
$entity = $layout->entities()
->uuid($entityId, false)
->whereHas('parent', function ($query) {
$query->where('label', 'follow-up');
})
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->first();
if ($entity) {
// Convert raw data into values that the CRM can consume.
$value = $crmService->normalizeValue($entity->field->type, $value);
// Add the field and value to the payload.
$fieldData += [
$entity->field->crm_provider_id => $value,
];
}
}
}
return $fieldData;
}
/**
* @param Activity $activity
*/
private function validateSummary(Activity $activity): void
{
$team = $activity->user->team;
$crmProvider = $team->crm->provider;
$attributes = [];
$rules = [
'layout_id' => 'required|uuid:crm_layouts,crm_configuration_id,' . $team->crm_id,
'title' => 'string|max:250',
'prospects' => 'required|array',
'opportunity_id' => new CrmReference($crmProvider),
'category_id' => 'uuid:playbook_categories|required_unless:is_internal,true',
'stage_id' => 'uuid:stages,team_id,' . $team->id, // Todo: move to proper validator
'summary' => 'max:50000',
'nId' => 'exists:notifications,id',
'crm_id' => new CrmReference($crmProvider),
'entities' => 'array',
'is_internal' => 'boolean',
];
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid($this->request->input('layout_id'));
// Only validate fields, not headers etc. If not loggable, we don't care about follow-up section.
$entities = $layout->entities()
->where('read_only', 0)
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->whereHas('parent', function ($query) use ($activity) {
if ($activity->isLoggable() === false) {
$query->where('label', '<>', 'follow-up');
}
});
$isInternal = $this->request->input('is_internal', false);
foreach ($entities->get() as $entity) {
$rules += $this->buildFieldValidator($entity, $isInternal);
$attributes += $this->buildFieldMessage($entity);
}
$this->request->validate($rules, [], $attributes);
}
private function buildFieldValidator(LayoutEntity $entity, bool $isInternal): array
{
return [
'entities.' . $entity->id_string => $entity->getValidator($isInternal),
];
}
/**
* @param LayoutEntity $entity
*
* @return array
*/
private function buildFieldMessage(LayoutEntity $entity): array
{
$label = $entity->label;
if ($label === null) {
$label = $entity->field->label;
}
return [
'entities.' . $entity->id_string => $label,
];
}
public function search(Request $request, ElasticActivityRepository $repository): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->debugLog(
$user,
'User extracted from request',
['user' => $user->getId(), 'tz' => $user->getTimezone()]
);
$searchCriteria = Criteria::createFromRequest($request->all(), $user->getTimezone());
$this->debugLog(
$user,
'ActivitySearch criteria built',
['searchCriteria' => $searchCriteria]
);
$filterSet = $this->activitySearch->getHomepageFilterSet($searchCriteria, $user);
$this->debugLog($user, 'FilterSet built', ['filterSet' => $filterSet]);
$this->validateSearch($request, $filterSet);
$this->debugLog($user, 'Request validated');
$searchResponse = $repository->onDemandSearch($user, $searchCriteria, $filterSet);
/** @var Collection<Activity> $activities */
$activities = $searchResponse['results'];
$this->debugLog($user, 'Activities ES response extracted');
$hideInternalMeetingsSetting = $this->teamRepository->getTeamSettingByTeamId(
$user->getTeamId(),
TeamSetting::HIDE_INTERNAL_SCHEDULED_MEETINGS->name(),
);
if ($hideInternalMeetingsSetting?->getValue() === '1') {
$activities = $activities->filter(function (Activity $activity) {
if ($activity->is_internal && empty($activity->actual_start_time)) {
return false;
}
return true;
});
}
$this->debugLog($user, 'Internal meetings (?!) filtered');
$this->response->getManager()
->parseIncludes([
'category',
'organizer.group',
'prospect',
'stage',
'opportunity',
'stats',
'scorecards',
'masterTrack',
'activeParticipants',
'notification',
])
->setSerializer(new JsonSerializer());
$transformerExcludes = $this->request->input('exclude');
if ($transformerExcludes) {
$this->response->getManager()->parseExcludes($transformerExcludes);
}
$this->debugLog($user, 'Response Manager (?!) applied');
$transformer = new ActivityTransformer();
$transformer->setConsumer($user);
$this->debugLog($user, 'Activity Transformer added');
$resource = new \League\Fractal\Resource\Collection($activities, $transformer);
$page = $searchCriteria->getPageNumber();
$this->debugLog($user, 'Search criteria page number called', ['page' => $page]);
$histogram = array_pluck(array_get($searchResponse, 'histogram.buckets', []), 'doc_count', 'key_as_string');
$this->debugLog($user, 'Histogram generated. Response is ready.', ['histogram' => $histogram]);
return $this->response->withArray([
'pagination' => [
'total' => $searchResponse['totalHits'],
'current' => $page,
'prev' => max($page - 1, 1),
'next' => $page + 1,
],
'results' => $this->response->getManager()->createData($resource)->toArray(),
'histogram' => $histogram,
]);
}
private function debugLog(User $user, string $logMessage, ?array $context = []): void
{
// Debug for Learning People Only
if ($user->getTeamId() !== 260) {
return;
}
Log::notice(
sprintf('[activity-search-controller] %s', $logMessage),
$context
);
}
/** @throws ValidationException */
private function validateSearch(Request $request, FilterDefinitionCollection $filterSet, ?string $prefix = null): void
{
$rules = [
'exclude' => 'array',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
];
if ($prefix !== null && mb_strpos($prefix, '.') !== false) {
$rules[rtrim($prefix, '.')] = sprintf(
'required|array|max:%d',
$filterSet->count()
);
}
$validationRules = $filterSet->getValidationRules($prefix)
->merge($rules)
->all();
$request->validate($validationRules);
}
public function createActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$search = $this->updateOrCreateActivitySearch($request);
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function updateActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('update', $search);
$this->updateOrCreateActivitySearch($request, $search);
return $this->response->withOk();
}
private function storeNamedSearchFilters(
Collection $request,
Search $search,
FilterDefinitionCollection $filterSet,
?string $prefix = null,
): self {
$arrayTypeProperties = $filterSet
->getPropertyTypes([
FilterDefinitionCollection::PROPERTY_TYPE_ARRAY,
])
->all();
$supportedRequestProperties = $filterSet->getSupportedRequestProperties($prefix);
foreach ($supportedRequestProperties as $requestPropertyName) {
if (! array_has($request, $requestPropertyName)) {
continue;
}
/** @var string|string[] $propertyValue */
$propertyValue = array_get($request, $requestPropertyName);
$propertyName = $prefix === null
? $requestPropertyName
: mb_substr($requestPropertyName, mb_strlen($prefix));
$isArrayType = array_has($arrayTypeProperties, $propertyName);
if (! $isArrayType) {
/** @var string $requestPropertyValue */
$search->filters()->updateOrCreate(
[
'filter' => $propertyName,
],
[
'value' => $propertyValue,
]
);
continue;
}
/** @var string[] $requestPropertyValue */
/** @var SearchFilter[]|Collection $existingFilterValues */
$existingFilterValuesKeyed = $search->filters()
->where('filter', $propertyName)
->get()
->keyBy('id');
// Iterate over values provided as request parameters
foreach ($propertyValue as $value) {
/** @var SearchFilter|null $valueFilter */
$valueFilter = $search->filters()
->where(
[
'filter' => $propertyName,
'value' => $value,
]
)
->first();
if ($valueFilter !== null) {
// Remove filter value pair from list to be deleted
$existingFilterValuesKeyed->forget($valueFilter->id);
} else {
// Add new filter/value pair
$search->filters()->updateOrCreate([
'filter' => $propertyName,
'value' => $value,
]);
}
}
// Delete filter value pairs for this filter that no longer exist in request parameters
foreach ($existingFilterValuesKeyed as $existingFilter) {
$existingFilter->delete();
}
}
/** @var Collection<int, SearchFilter> $filtersKeyed */
$filtersKeyed = $search->filters()->get()->keyBy('filter');
// wipe removed filters from this search
foreach ($filtersKeyed as $filterName => $filter) {
if (array_has($request, $prefix . $filterName)) {
continue;
}
// Remove all filter values for this filter
$search->filters()->where('filter', $filterName)->delete();
}
return $this;
}
/**
* @throws AuthorizationException
*/
public function fetchActivitySearch(
Search $search,
Request $request,
SearchTransformer $searchTransformer,
): JsonResponse {
$this->authorize('view', $search);
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function listActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withCollection(
$user->searches()->get(),
$searchTransformer
->withConsumer($user)
);
}
/**
* Deletes a saved search
*
* @param Request $request
* @param Search $search
*
* @throws Exception
*
* @return JsonResponse
*/
public function deleteActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('delete', $search);
// Orphan any AutomatedReports that use this search
$search->automatedReports()->withTrashed()->update(['activity_search_id' => null]);
// Delete filters and the search itself
$search->filters()->delete();
$search->delete();
return $this->response->withOk();
}
public function live(Request $request, ElasticActivityRepository $repository): JsonResponse
{
$user = $this->getUserFromRequest($request);
$this->request->validate([
'sort_direction' => 'in:asc,desc',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
]);
$activities = $repository->getLiveCoachingEligibleActivities(
user: $user,
lookBackMinutes: self::LOOK_BACK,
limit: (int) $this->request->input('limit', 25),
page: (int) $this->request->input('page', 1),
sortBy: ['actual_start_time', 'scheduled_start_time'],
sortDirection: (string) $this->request->input('sort_direction', 'asc'),
);
$this->response
->getManager()
->parseIncludes(['organizer.group', 'prospect'])
->setSerializer(new JsonSerializer());
return $this->response->withCollection($activities, new ActivityTransformer());
}
/**
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function show(Activity $activity, ActivityService $activityService): JsonResponse
{
$this->authorize('show', $activity);
$user = $activity->getUser();
$team = $user->getTeam();
// Sync the opportunity with the latest data if possible.
if ($activity->opportunity_id) {
try {
$crmService = $this->providerRegistry->get($team->crm->provider);
if (! $user->isCrmRequired()) {
$crmService->setUser($team->getOwner());
} else {
$crmService->setUser($user);
}
$crmService->syncOpportunity($activity->opportunity->crm_provider_id);
} catch (Exception $exception) {
// Move on.
}
}
$activityData = $activityService->getActivityData($this->request->user(), $activity);
return response()->json($activityData);
}
public function createRecording(Activity $activity)
{
$this->authorize('record', $activity);
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Tell Twilio to start recording this activity.
if ($activity->recording_state === Activity::RECORDING_OFF) {
$job = (new StartRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withCreated();
}
return $this->response->errorGone('Activity is already recording.');
}
public function updateRecording(Request $request, Activity $activity)
{
$this->authorize('record', $activity);
$request->validate([
'preference' => 'boolean',
'state' => [
'string',
Rule::in([
Activity::RECORDING_IN_PROGRESS,
Activity::RECORDING_PAUSED,
]),
],
]);
if ($request->has('state')) {
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Toggle the recording state between paused and resumed.
if (! $activity->isRecordingState(Activity::RECORDING_OFF)) {
$job = (new ToggleRecording($activity, $request->input('state')))
->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Recording is not toggleable.');
}
if ($request->has('preference')) {
$activity->update([
'recording_preference' => $request->input('preference') ? 1 : 0,
]);
return $this->response->withOk();
}
return $this->response->errorWrongArgs('Something went wrong');
}
public function stopRecording(Activity $activity)
{
$this->authorize('stopRecord', $activity);
// Tell Twilio to stop recording this activity.
if ($activity->isRecordingState(Activity::RECORDING_IN_PROGRESS)) {
$job = (new StopRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Activity is not recording.');
}
/**
* Add activity to this user's favorites playlist
*
* @throws AuthorizationException
*/
public function favorite(Activity $activity, PlaylistActivityRepository $playlistActivityRepository): JsonResponse
{
$this->authorize('favorite', $activity);
$user = $this->getUserFromRequest($this->request);
$favorite = $activity->wasFavoritedBy($user);
$name = $activity->activity_title ?? '';
// It needs to check at least one record.
if (! $favorite) {
$favoritePlaylist = $user->favoritePlaylist();
$playlistActivity = $playlistActivityRepository->findByBaseActivityUserAndPlaylist(
$activity,
$user,
$favoritePlaylist
);
if ($playlistActivity !== null) {
$playlistActivity->update(
// Just update, don't sort.
['start_time' => 0, 'name' => mb_strimwidth($name, 0, 100)],
);
} else {
$playlistActivity = $activity->playlistActivities()->create([
'playlist_id' => $favoritePlaylist->getId(),
'user_id' => $user->getId(),
'start_time' => 0,
'name' => mb_strimwidth($name, 0, 100),
]);
// Sort it on top.
$playlistActivity->update(
[
'sort' => $playlistActivityRepository->calculateNewSortOrder(
null,
$playlistActivity,
),
],
);
}
$playlistActivityRepository->calculateNewSortOrder(null, $playlistActivity);
return new JsonResponse([], JsonResponse::HTTP_CREATED);
}
return new JsonResponse(
[
'error' => [
'code' => AbstractResponse::CODE_CONFLICT,
'http_code' => JsonResponse::HTTP_CONFLICT,
'message' => 'Resource Already Exists',
],
],
JsonResponse::HTTP_CONFLICT,
);
}
/**
* Remove activity from this user's favorites playlist
*
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function unfavorite(Activity $activity)
{
$user = $this...
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<?php
namespace Jiminny\Http\Controllers\API;
use Carbon\Carbon;
use ChaseConey\LaravelDatadogHelper\Datadog;
use Exception;
use Illuminate\Auth\Access\AuthorizationException;
use Illuminate\Database\Eloquent\Builder;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Illuminate\Support\Collection;
use Illuminate\Support\Facades\Log;
use Illuminate\Validation\Rule;
use Illuminate\Validation\Rules\In;
use Illuminate\Validation\ValidationException;
use InvalidArgumentException;
use Jiminny\Component\ActivityAnalytics;
use Jiminny\Component\ActivitySearch;
use Jiminny\Component\ActivitySearch\FilterDefinitionCollection;
use Jiminny\Component\PlaybackPage\Comments\Services\ActivityCommentService;
use Jiminny\Component\Queue\Constants;
use Jiminny\Contracts\ES\Events\UpdateSingleEntity;
use Jiminny\Contracts\ES\UpdateTargetEnum;
use Jiminny\Contracts\Nudge\NudgeFactoryInterface;
use Jiminny\Contracts\Playlist\PlaylistTrackFactoryInterface;
use Jiminny\Contracts\Repositories\PlaylistActivityRepository;
use Jiminny\Contracts\Services\Crm\ServiceInterface;
use Jiminny\Enums\TeamSetting;
use Jiminny\Events\Activities\AiAutomation\ActivityProspectAdded;
use Jiminny\Events\Activities\Coaching\Coached;
use Jiminny\Contracts\Services\Crm\SupportsObjectTypeParseInterface;
use Jiminny\Exceptions\LogicException;
use Jiminny\Exceptions\SocialAccountTokenInvalidException;
use Jiminny\Http\Controllers\API\BaseController as Controller;
use Jiminny\Http\Controllers\CommentContextInterface;
use Jiminny\Http\Responses\Api\AbstractResponse;
use Jiminny\Http\Responses\Api\Response;
use Jiminny\Http\Serializers\JsonSerializer;
use Jiminny\Http\Transformers\ActivityCommentTransformer;
use Jiminny\Http\Transformers\ActivityTopicTriggerTransformer;
use Jiminny\Http\Transformers\ActivityTransformer;
use Jiminny\Http\Transformers\AvailabilityNotificationTransformer;
use Jiminny\Http\Transformers\CoachingFeedbackTransformer;
use Jiminny\Http\Transformers\CoachingSectionsTransformer;
use Jiminny\Http\Transformers\SearchTransformer;
use Jiminny\Http\Transformers\StatsTransformer;
use Jiminny\Jobs\Crm\SaveActivity;
use Jiminny\Jobs\Crm\UpdateStage;
use Jiminny\Jobs\Telephony\StartRecording;
use Jiminny\Jobs\Telephony\StopRecording;
use Jiminny\Jobs\Telephony\ToggleRecording;
use Jiminny\Models\Account;
use Jiminny\Models\Activity;
use Jiminny\Models\Activity\CoachRequest;
use Jiminny\Models\Activity\Comment;
use Jiminny\Models\Activity\Search;
use Jiminny\Models\Activity\SearchFilter;
use Jiminny\Models\Activity\Share;
use Jiminny\Models\CoachingFeedback;
use Jiminny\Models\CoachingSection;
use Jiminny\Models\CoachingSectionCriterion;
use Jiminny\Models\CoachingSectionFeedback;
use Jiminny\Models\Contact;
use Jiminny\Models\Crm\Field;
use Jiminny\Models\Crm\FieldData;
use Jiminny\Models\Crm\Layout;
use Jiminny\Models\Crm\LayoutEntity;
use Jiminny\Models\Feature\FeatureEnum;
use Jiminny\Models\LanguageDialect;
use Jiminny\Models\Lead;
use Jiminny\Models\Nudge;
use Jiminny\Models\PlaybookCategory;
use Jiminny\Models\Playlist;
use Jiminny\Models\Stage;
use Jiminny\Models\Team;
use Jiminny\Models\Track;
use Jiminny\Models\User;
use Jiminny\Repositories\CoachingFeedbackRepository;
use Jiminny\Repositories\ElasticActivityRepository;
use Jiminny\Repositories\TeamRepository;
use Jiminny\Rules\CrmReference;
use Jiminny\Rules\MultidimensionalArrayMaxCharRule;
use Jiminny\Services\ActivityService;
use Jiminny\Services\Crm\ProviderRegistry;
use Jiminny\Services\PlaybackService;
use Jiminny\Services\UserService;
use Jiminny\VO\Repository\OnDemandActivitySearch\Criteria;
use Psr\Log\LoggerInterface;
use Ramsey\Uuid\Uuid;
use Sentry;
use Symfony\Component\HttpFoundation;
final class ActivityController extends Controller implements CommentContextInterface
{
// Number of minutes to look back on activities. i.e. a timeout on activity duration.
private const int LOOK_BACK = 180;
public function __construct(
private ProviderRegistry $providerRegistry,
private ActivityService $activityService,
Response $response,
private UserService $userService,
private ActivitySearch\Service\ActivitySearch $activitySearch,
private NudgeFactoryInterface $nudgeFactory,
private ActivityCommentService $activityCommentService,
private LoggerInterface $logger,
private readonly CoachingFeedbackRepository $coachingFeedbackRepository,
private readonly TeamRepository $teamRepository,
) {
parent::__construct($response);
}
public static function getCommentImplementation(): string
{
return Comment::class;
}
public function delete()
{
$this->request->validate([
'*' => 'uuid:activities',
]);
$deletedIds = [];
foreach ($this->request->all() as $activityId) {
$activity = Activity::idOrUuId($activityId);
try {
if ($this->authorize('delete', $activity)) {
$activity->delete();
$deletedIds[] = $activityId;
\Log::info('Soft deleted activity ' . $activity->id_string . ' by user ' . $this->getUser()->id);
}
} catch (AuthorizationException $authorizationException) {
// They didn't have permission.
}
}
return $this->response->withArray($deletedIds);
}
public function update(Request $request, Activity $activity)
{
$this->authorize('updateMetadata', $activity);
$request->validate([
'title' => 'string|max:250',
'category_id' => 'uuid:playbook_categories',
'language' => [
new In(
LanguageDialect::query()
->with('language')
->cursor()
->map(static function (LanguageDialect $languageDialect): string {
return $languageDialect->getLanguageLocale();
})
->all()
),
],
]);
if ($request->has('title')) {
$activity->title = $request->input('title');
}
if ($request->has('category_id')) {
$category = PlaybookCategory::uuid($request->input('category_id'));
if ($category->playbook->team_id !== $request->user()->team_id) {
return $this->response->errorNotFound('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
if ($request->has('language')) {
if (! $activity->isInProgress()) {
return $this->response->withError(
'Activity language can only be set while the meeting is in progress.',
400
);
}
$activity->setLanguageCode($request->input('language'));
}
$activity->save();
return $this->response->withOk();
}
// XXX: This should be merged with the update method.
/**
* @param Activity $activity
*
* @throws AuthorizationException
* @throws SocialAccountTokenInvalidException
*
* @return mixed
*/
public function summarize(Activity $activity): mixed
{
$this->logger->info('[Log Activity] Summarizing activity ', [
'activityId' => $activity->getUuid(),
'payload' => $this->request->all(),
]);
$this->authorize('update', $activity);
$this->logger->info('[Log Activity] Validating summary');
// Validate the payload.
$this->validateSummary($activity);
// All objects must belong to this team.
/** @var User $user */
$user = $this->request->user();
$team = $user->getTeam();
$crmService = $this->providerRegistry->get($team->crm->provider);
try {
$crmUser = $user;
if ($user->isCrmRequired() === false) {
$crmUser = $team->owner;
}
$crmService->setUser($crmUser);
} catch (SocialAccountTokenInvalidException $accountTokenInvalidException) {
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($accountTokenInvalidException->getMessage());
}
$rawEntities = $this->request->input('entities');
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid(
$this->request->input('layout_id')
);
// Delay execution of CRM jobs to avoid locking issues.
$jobDelay = 0;
// If we have arrived from a notification, mark it as read.
$notificationId = $this->request->input('nId');
if ($notificationId) {
$notification = $user->unreadNotifications->where('id', $notificationId)->first();
if ($notification) {
$notification->markAsRead();
}
}
$title = $this->request->input('title');
$prospects = $this->request->input('prospects');
$opportunityId = $this->request->input('opportunity_id');
$stageId = $this->request->input('stage_id');
$categoryId = $this->request->input('category_id');
$summary = $this->request->input('summary');
$crmProviderId = $this->request->input('crm_id');
$isInternal = $this->request->input('is_internal') ?? false;
$lead = null;
$category = null;
$account = null;
$contact = null;
$opportunity = null;
$stage = null;
$callStage = null;
foreach ($prospects as $prospectData) {
$objectId = $prospectData['id'];
if ($objectId === null) {
continue;
}
$objectType = $prospectData['type'];
$this->logger->info('debug', ['prospect_data' => $prospectData]);
try {
if ($objectType === null) {
$this->logger->info('no object type');
if ($crmService instanceof SupportsObjectTypeParseInterface) {
$objectType = $crmService->parseObjectType($objectId);
}
}
switch ($objectType) {
case 'lead':
$this->logger->info('Processing lead');
/** @var Lead|null $lead */
$lead = $team->crm->leads()->where('crm_provider_id', $objectId)->first();
// Lead does not exist locally, import it.
if ($lead === null) {
$this->logger->info('Lead does not exist locally');
/** @var Lead $lead */
$lead = $crmService->syncLead($objectId);
}
$this->logger->info('Lead found', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
if ($stageId === null) {
$this->logger->info('Stage ID is null');
// If it was not provided, just assume it is the current stage.
$callStage = $lead->stage;
break;
}
$this->logger->info('Looking for stage');
// Determine if they have changed the stage.
/** @var Stage $stage */
$stage = $team->crm->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_LEAD)
->firstOrFail();
$this->logger->info('Stage found', ['stageId' => $stage->id, 'lead_stage' => $lead->stage_id]);
if ($lead->stage_id && $lead->stage_id !== $stage->id) {
$this->logger->info('Stage has changed');
// Storage current stage on activity.
$callStage = $lead->stage;
// The stage has changed, update in remote CRM.
dispatch(new UpdateStage($activity, $lead, $callStage, $stage));
$this->logger->info(
sprintf(
'[%s] User changing lead stage from %s to %s',
$crmService->getDisplayName(),
$callStage->getName(),
$stage->getName()
),
[
'user' => $user->getUuid(),
'lead' => $lead->getUuid(),
]
);
} else {
$this->logger->info('Stage has not changed');
// Stage remains as current.
$callStage = $stage;
}
break;
case 'account':
$this->logger->info('Processing account');
// If the object is not a lead, it should be an account.
$account = $team->crm->accounts()->where('crm_provider_id', $objectId)->first();
// Account does not exist locally, import it.
if ($account === null) {
$this->logger->info('Account does not exist locally');
$account = $crmService->syncAccount($objectId);
}
$this->logger->info('Account found', ['accountId' => $account->id]);
break;
case 'contact':
$this->logger->info('processing contact');
$contact = $team->crm->contacts()->where('crm_provider_id', $objectId)->first();
// Contact does not exist locally, import it.
if (! $contact instanceof Contact) {
$this->logger->info('contact does not exist locally');
$contact = $crmService->syncContact($objectId);
}
$this->logger->info('resolving account');
$account = $this->resolveAccount($team, $contact, $crmService, $prospects);
break;
}
// If they have specified an opportunity, retrieve this with stage.
if ($opportunityId) {
$this->logger->info('opportunity id is set');
$opportunity = $team->crm->opportunities()->where('crm_provider_id', $opportunityId)->first();
// Opportunity does not exist locally, import it.
if ($opportunity === null) {
$this->logger->info('opportunity does not exist locally');
$opportunity = $crmService->syncOpportunity($opportunityId);
}
if ($stageId === null) {
$this->logger->info('stage id is null');
// If it was not provided, just assume it is the current stage.
$callStage = $opportunity->stage ?? null;
} else {
$this->logger->info('looking for stage');
/** @var ?Stage $opportunityStage */
$opportunityStage = $team->crm
->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_OPPORTUNITY)
->first();
// There is a chance we still cannot import this opportunity.
if ($opportunityStage !== null && $opportunity !== null && $opportunity->stage_id !== $opportunityStage->id) {
$this->logger->info('opportunity stage has changed');
// Storage current stage on activity.
$callStage = $opportunity->stage;
dispatch(new UpdateStage($activity, $opportunity, $callStage, $opportunityStage));
$this->logger->info(
sprintf(
'[%s] User changing opportunity stage from %s to %s',
$crmService->getDisplayName(),
$callStage->name,
$opportunityStage->name
),
[
'userId' => $user->id_string,
'opportunityId' => $opportunity->id_string,
]
);
} else {
$this->logger->info('opportunity stage has not changed');
// Stage remains as current.
$callStage = $opportunityStage;
}
}
}
if ($crmProviderId) {
// Cast $crmProviderId to string otherwise it won't use database index for some records
$linkedActivity = Activity::where('crm_provider_id', (string) $crmProviderId)->first();
// Check if this activity has already been assigned to a different activity.
if ($linkedActivity && $linkedActivity->id !== $activity->id) {
throw new InvalidArgumentException(
'Sorry, the linked task has already been logged under a different call. '
. 'Please choose another linked task.'
);
}
}
} catch (InvalidArgumentException $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($exception->getMessage());
} catch (Exception $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorInternalError(
'Sorry, an error occurred. Please try again or reach out to support if the problem continues.'
);
}
}
if ($categoryId) {
$category = PlaybookCategory::uuid($categoryId);
if ($category->playbook->team_id !== $team->id) {
throw new InvalidArgumentException('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
$this->logger->info('Prospect data', [
'lead_id' => $lead?->getId(),
'account_id' => $account?->getId(),
'contact_id' => $contact?->getId(),
'opportunity_id' => $opportunity?->getId(),
'stage_id' => $stage?->getId(),
]);
if ($title) {
$activity->title = $title;
}
if ($summary) {
$activity->summary = $summary;
}
if ($crmProviderId) {
$activity->crm_provider_id = $crmProviderId;
}
if ($callStage) {
$this->logger->info('Setting stage id', ['stageId' => $callStage->id]);
$activity->stage_id = $callStage->id;
}
if ($lead) {
$this->logger->info('Setting lead id', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
// If we are changed from an account > lead, unset the account data.
$this->logger->info('Unsetting account id, opportunity id, contact id, value');
$activity->account_id = null;
$activity->opportunity_id = null;
$activity->contact_id = null;
$activity->value = null;
}
if ($account) {
$this->logger->info('Setting account id', ['accountId' => $account->id]);
$activity->account_id = $account->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('unsetting lead id');
$activity->lead_id = null;
// Unset the contact if switching different accounts. Will be set up below if still applicable.
if (! $team->hasFeature(FeatureEnum::LINK_ACTIVITY_TO_MULTIPLE_PROSPECTS) || empty($contact)) {
$this->logger->info('Unsetting contact id');
$activity->contact_id = null;
}
}
if ($opportunity) {
$this->logger->info('setting opportunity id', ['opportunityId' => $opportunity->id]);
$this->logger->info('unsetting lead id');
$activity->opportunity_id = $opportunity->id;
$activity->value = $opportunity->value;
// If we are changed from an lead > account, unset the lead data.
$activity->lead_id = null;
}
if ($contact) {
$this->logger->info('setting contact id', ['contactId' => $contact->id]);
$activity->contact_id = $contact->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('Unsetting lead id');
$activity->lead_id = null;
}
$activity->is_internal = $isInternal;
$activity->save();
$activity->refresh();
$this->logger->notice('Activity saved', [
'activity_id' => $activity->getId(),
'lead_id' => $activity->lead_id,
'account_id' => $activity->account_id,
'contact_id' => $activity->contact_id,
'opportunity_id' => $activity->opportunity_id,
'stage_id' => $activity->stage_id,
'crm_provider_id' => $activity->getCrmProviderId(),
]);
// Store entities as field data on the activity.
$updatedData = $this->storeEntities($crmService, $activity, $layout, $rawEntities);
if ($activity->isLoggable()) {
// Follow-up Task or Event data.
$followupData = $this->fetchFollowupEntities($crmService, $layout, $rawEntities);
$this->logger->info('CRM LOG manual log triggered', [
'activityId' => $activity->getUuid(),
'followupData' => $followupData,
'userId' => $user->getUuid(),
]);
// Store data in the CRM.
// ++add check for crm_required
$job = new SaveActivity($activity, $followupData);
if ($updatedData) {
$job->delay(Carbon::now()->addMinutes($jobDelay));
}
dispatch($job);
// Manually dispatch log for Opportunity or Prospect added
if ($activity->hasOpportunity() || $activity->hasProspect()) {
event(new ActivityProspectAdded(
activity: $activity,
eventSource: 'manually-log-crm-data'
));
}
}
return $this->response->withOk();
}
/**
* Extract any activity data to be upserted in the Lead/Opportunity/Task etc in the CRM.
*
* @param ServiceInterface $service
* @param Activity $activity
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function storeEntities(ServiceInterface $service, Activity $activity, Layout $layout, array $entities): array
{
$updatedData = [];
$existingData = $activity->data()->get();
// We need to delete any existing data to overwrite with latest values.
$activity->data()->delete();
$layoutEntities = $layout->entities()
->with('field', 'parent')
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->get();
/** @var LayoutEntity $entity */
foreach ($layoutEntities as $entity) {
// If the user has provided a value for this entity
if (array_key_exists($entity->id_string, $entities)) {
$value = $entities[$entity->id_string];
// Convert raw data into values that the CRM can consume.
if ($value) {
$value = $service->normalizeValue($entity->field->type, $value);
}
// Check the field is part of the activity-summary section.
if ($entity->parent && $entity->parent->label === 'activity-summary' && $value) {
// This is the internal database ID, not the external CRM ID.
$objectId = null;
switch ($entity->field->object_type) {
case Field::OBJECT_ACCOUNT:
$objectId = $activity->account_id;
break;
case Field::OBJECT_CONTACT:
$objectId = $activity->contact_id;
break;
case Field::OBJECT_OPPORTUNITY:
$objectId = $activity->opportunity_id;
break;
case Field::OBJECT_LEAD:
$objectId = $activity->lead_id;
break;
case Field::OBJECT_TASK:
case Field::OBJECT_EVENT:
$objectId = $activity->id;
break;
}
if ($objectId) {
/** @var FieldData $data */
$data = $activity->data()->create([
'crm_layout_entity_id' => $entity->id,
'crm_field_id' => $entity->crm_field_id,
'object_type' => $entity->field->object_type,
'object_id' => $objectId,
'value' => $value,
]);
// Never send read-only field data to the CRM.
if ($entity->read_only === false && $entity->is_visible) {
$existingValue = $existingData
->where('crm_layout_entity_id', $entity->id)
->where('crm_field_id', $entity->crm_field_id)
->where('object_type', $entity->field->object_type)
->where('object_id', $objectId)
->first();
// If the field was actually changed, we need to reflect this in the CRM too.
if ($existingValue === null || $existingValue->value !== $value) {
$updatedData[] = $data->id;
}
}
}
}
}
}
return $updatedData;
}
/**
* Extract any followup data to be dispatched in a job to create a new Task/Event in the CRM.
*
* @param ServiceInterface $crmService
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function fetchFollowupEntities(ServiceInterface $crmService, Layout $layout, array $entities): array
{
$fieldData = [];
foreach ($entities as $entityId => $value) {
// Only bother with fields that have a value.
if ($value) {
// Extract the entity from the UUID. Check the field is valid and part of the follow-up section.
$entity = $layout->entities()
->uuid($entityId, false)
->whereHas('parent', function ($query) {
$query->where('label', 'follow-up');
})
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->first();
if ($entity) {
// Convert raw data into values that the CRM can consume.
$value = $crmService->normalizeValue($entity->field->type, $value);
// Add the field and value to the payload.
$fieldData += [
$entity->field->crm_provider_id => $value,
];
}
}
}
return $fieldData;
}
/**
* @param Activity $activity
*/
private function validateSummary(Activity $activity): void
{
$team = $activity->user->team;
$crmProvider = $team->crm->provider;
$attributes = [];
$rules = [
'layout_id' => 'required|uuid:crm_layouts,crm_configuration_id,' . $team->crm_id,
'title' => 'string|max:250',
'prospects' => 'required|array',
'opportunity_id' => new CrmReference($crmProvider),
'category_id' => 'uuid:playbook_categories|required_unless:is_internal,true',
'stage_id' => 'uuid:stages,team_id,' . $team->id, // Todo: move to proper validator
'summary' => 'max:50000',
'nId' => 'exists:notifications,id',
'crm_id' => new CrmReference($crmProvider),
'entities' => 'array',
'is_internal' => 'boolean',
];
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid($this->request->input('layout_id'));
// Only validate fields, not headers etc. If not loggable, we don't care about follow-up section.
$entities = $layout->entities()
->where('read_only', 0)
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->whereHas('parent', function ($query) use ($activity) {
if ($activity->isLoggable() === false) {
$query->where('label', '<>', 'follow-up');
}
});
$isInternal = $this->request->input('is_internal', false);
foreach ($entities->get() as $entity) {
$rules += $this->buildFieldValidator($entity, $isInternal);
$attributes += $this->buildFieldMessage($entity);
}
$this->request->validate($rules, [], $attributes);
}
private function buildFieldValidator(LayoutEntity $entity, bool $isInternal): array
{
return [
'entities.' . $entity->id_string => $entity->getValidator($isInternal),
];
}
/**
* @param LayoutEntity $entity
*
* @return array
*/
private function buildFieldMessage(LayoutEntity $entity): array
{
$label = $entity->label;
if ($label === null) {
$label = $entity->field->label;
}
return [
'entities.' . $entity->id_string => $label,
];
}
public function search(Request $request, ElasticActivityRepository $repository): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->debugLog(
$user,
'User extracted from request',
['user' => $user->getId(), 'tz' => $user->getTimezone()]
);
$searchCriteria = Criteria::createFromRequest($request->all(), $user->getTimezone());
$this->debugLog(
$user,
'ActivitySearch criteria built',
['searchCriteria' => $searchCriteria]
);
$filterSet = $this->activitySearch->getHomepageFilterSet($searchCriteria, $user);
$this->debugLog($user, 'FilterSet built', ['filterSet' => $filterSet]);
$this->validateSearch($request, $filterSet);
$this->debugLog($user, 'Request validated');
$searchResponse = $repository->onDemandSearch($user, $searchCriteria, $filterSet);
/** @var Collection<Activity> $activities */
$activities = $searchResponse['results'];
$this->debugLog($user, 'Activities ES response extracted');
$hideInternalMeetingsSetting = $this->teamRepository->getTeamSettingByTeamId(
$user->getTeamId(),
TeamSetting::HIDE_INTERNAL_SCHEDULED_MEETINGS->name(),
);
if ($hideInternalMeetingsSetting?->getValue() === '1') {
$activities = $activities->filter(function (Activity $activity) {
if ($activity->is_internal && empty($activity->actual_start_time)) {
return false;
}
return true;
});
}
$this->debugLog($user, 'Internal meetings (?!) filtered');
$this->response->getManager()
->parseIncludes([
'category',
'organizer.group',
'prospect',
'stage',
'opportunity',
'stats',
'scorecards',
'masterTrack',
'activeParticipants',
'notification',
])
->setSerializer(new JsonSerializer());
$transformerExcludes = $this->request->input('exclude');
if ($transformerExcludes) {
$this->response->getManager()->parseExcludes($transformerExcludes);
}
$this->debugLog($user, 'Response Manager (?!) applied');
$transformer = new ActivityTransformer();
$transformer->setConsumer($user);
$this->debugLog($user, 'Activity Transformer added');
$resource = new \League\Fractal\Resource\Collection($activities, $transformer);
$page = $searchCriteria->getPageNumber();
$this->debugLog($user, 'Search criteria page number called', ['page' => $page]);
$histogram = array_pluck(array_get($searchResponse, 'histogram.buckets', []), 'doc_count', 'key_as_string');
$this->debugLog($user, 'Histogram generated. Response is ready.', ['histogram' => $histogram]);
return $this->response->withArray([
'pagination' => [
'total' => $searchResponse['totalHits'],
'current' => $page,
'prev' => max($page - 1, 1),
'next' => $page + 1,
],
'results' => $this->response->getManager()->createData($resource)->toArray(),
'histogram' => $histogram,
]);
}
private function debugLog(User $user, string $logMessage, ?array $context = []): void
{
// Debug for Learning People Only
if ($user->getTeamId() !== 260) {
return;
}
Log::notice(
sprintf('[activity-search-controller] %s', $logMessage),
$context
);
}
/** @throws ValidationException */
private function validateSearch(Request $request, FilterDefinitionCollection $filterSet, ?string $prefix = null): void
{
$rules = [
'exclude' => 'array',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
];
if ($prefix !== null && mb_strpos($prefix, '.') !== false) {
$rules[rtrim($prefix, '.')] = sprintf(
'required|array|max:%d',
$filterSet->count()
);
}
$validationRules = $filterSet->getValidationRules($prefix)
->merge($rules)
->all();
$request->validate($validationRules);
}
public function createActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$search = $this->updateOrCreateActivitySearch($request);
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function updateActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('update', $search);
$this->updateOrCreateActivitySearch($request, $search);
return $this->response->withOk();
}
private function storeNamedSearchFilters(
Collection $request,
Search $search,
FilterDefinitionCollection $filterSet,
?string $prefix = null,
): self {
$arrayTypeProperties = $filterSet
->getPropertyTypes([
FilterDefinitionCollection::PROPERTY_TYPE_ARRAY,
])
->all();
$supportedRequestProperties = $filterSet->getSupportedRequestProperties($prefix);
foreach ($supportedRequestProperties as $requestPropertyName) {
if (! array_has($request, $requestPropertyName)) {
continue;
}
/** @var string|string[] $propertyValue */
$propertyValue = array_get($request, $requestPropertyName);
$propertyName = $prefix === null
? $requestPropertyName
: mb_substr($requestPropertyName, mb_strlen($prefix));
$isArrayType = array_has($arrayTypeProperties, $propertyName);
if (! $isArrayType) {
/** @var string $requestPropertyValue */
$search->filters()->updateOrCreate(
[
'filter' => $propertyName,
],
[
'value' => $propertyValue,
]
);
continue;
}
/** @var string[] $requestPropertyValue */
/** @var SearchFilter[]|Collection $existingFilterValues */
$existingFilterValuesKeyed = $search->filters()
->where('filter', $propertyName)
->get()
->keyBy('id');
// Iterate over values provided as request parameters
foreach ($propertyValue as $value) {
/** @var SearchFilter|null $valueFilter */
$valueFilter = $search->filters()
->where(
[
'filter' => $propertyName,
'value' => $value,
]
)
->first();
if ($valueFilter !== null) {
// Remove filter value pair from list to be deleted
$existingFilterValuesKeyed->forget($valueFilter->id);
} else {
// Add new filter/value pair
$search->filters()->updateOrCreate([
'filter' => $propertyName,
'value' => $value,
]);
}
}
// Delete filter value pairs for this filter that no longer exist in request parameters
foreach ($existingFilterValuesKeyed as $existingFilter) {
$existingFilter->delete();
}
}
/** @var Collection<int, SearchFilter> $filtersKeyed */
$filtersKeyed = $search->filters()->get()->keyBy('filter');
// wipe removed filters from this search
foreach ($filtersKeyed as $filterName => $filter) {
if (array_has($request, $prefix . $filterName)) {
continue;
}
// Remove all filter values for this filter
$search->filters()->where('filter', $filterName)->delete();
}
return $this;
}
/**
* @throws AuthorizationException
*/
public function fetchActivitySearch(
Search $search,
Request $request,
SearchTransformer $searchTransformer,
): JsonResponse {
$this->authorize('view', $search);
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function listActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withCollection(
$user->searches()->get(),
$searchTransformer
->withConsumer($user)
);
}
/**
* Deletes a saved search
*
* @param Request $request
* @param Search $search
*
* @throws Exception
*
* @return JsonResponse
*/
public function deleteActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('delete', $search);
// Orphan any AutomatedReports that use this search
$search->automatedReports()->withTrashed()->update(['activity_search_id' => null]);
// Delete filters and the search itself
$search->filters()->delete();
$search->delete();
return $this->response->withOk();
}
public function live(Request $request, ElasticActivityRepository $repository): JsonResponse
{
$user = $this->getUserFromRequest($request);
$this->request->validate([
'sort_direction' => 'in:asc,desc',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
]);
$activities = $repository->getLiveCoachingEligibleActivities(
user: $user,
lookBackMinutes: self::LOOK_BACK,
limit: (int) $this->request->input('limit', 25),
page: (int) $this->request->input('page', 1),
sortBy: ['actual_start_time', 'scheduled_start_time'],
sortDirection: (string) $this->request->input('sort_direction', 'asc'),
);
$this->response
->getManager()
->parseIncludes(['organizer.group', 'prospect'])
->setSerializer(new JsonSerializer());
return $this->response->withCollection($activities, new ActivityTransformer());
}
/**
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function show(Activity $activity, ActivityService $activityService): JsonResponse
{
$this->authorize('show', $activity);
$user = $activity->getUser();
$team = $user->getTeam();
// Sync the opportunity with the latest data if possible.
if ($activity->opportunity_id) {
try {
$crmService = $this->providerRegistry->get($team->crm->provider);
if (! $user->isCrmRequired()) {
$crmService->setUser($team->getOwner());
} else {
$crmService->setUser($user);
}
$crmService->syncOpportunity($activity->opportunity->crm_provider_id);
} catch (Exception $exception) {
// Move on.
}
}
$activityData = $activityService->getActivityData($this->request->user(), $activity);
return response()->json($activityData);
}
public function createRecording(Activity $activity)
{
$this->authorize('record', $activity);
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Tell Twilio to start recording this activity.
if ($activity->recording_state === Activity::RECORDING_OFF) {
$job = (new StartRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withCreated();
}
return $this->response->errorGone('Activity is already recording.');
}
public function updateRecording(Request $request, Activity $activity)
{
$this->authorize('record', $activity);
$request->validate([
'preference' => 'boolean',
'state' => [
'string',
Rule::in([
Activity::RECORDING_IN_PROGRESS,
Activity::RECORDING_PAUSED,
]),
],
]);
if ($request->has('state')) {
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Toggle the recording state between paused and resumed.
if (! $activity->isRecordingState(Activity::RECORDING_OFF)) {
$job = (new ToggleRecording($activity, $request->input('state')))
->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Recording is not toggleable.');
}
if ($request->has('preference')) {
$activity->update([
'recording_preference' => $request->input('preference') ? 1 : 0,
]);
return $this->response->withOk();
}
return $this->response->errorWrongArgs('Something went wrong');
}
public function stopRecording(Activity $activity)
{
$this->authorize('stopRecord', $activity);
// Tell Twilio to stop recording this activity.
if ($activity->isRecordingState(Activity::RECORDING_IN_PROGRESS)) {
$job = (new StopRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Activity is not recording.');
}
/**
* Add activity to this user's favorites playlist
*
* @throws AuthorizationException
*/
public function favorite(Activity $activity, PlaylistActivityRepository $playlistActivityRepository): JsonResponse
{
$this->authorize('favorite', $activity);
$user = $this->getUserFromRequest($this->request);
$favorite = $activity->wasFavoritedBy($user);
$name = $activity->activity_title ?? '';
// It needs to check at least one record.
if (! $favorite) {
$favoritePlaylist = $user->favoritePlaylist();
$playlistActivity = $playlistActivityRepository->findByBaseActivityUserAndPlaylist(
$activity,
$user,
$favoritePlaylist
);
if ($playlistActivity !== null) {
$playlistActivity->update(
// Just update, don't sort.
['start_time' => 0, 'name' => mb_strimwidth($name, 0, 100)],
);
} else {
$playlistActivity = $activity->playlistActivities()->create([
'playlist_id' => $favoritePlaylist->getId(),
'user_id' => $user->getId(),
'start_time' => 0,
'name' => mb_strimwidth($name, 0, 100),
]);
// Sort it on top.
$playlistActivity->update(
[
'sort' => $playlistActivityRepository->calculateNewSortOrder(
null,
$playlistActivity,
),
],
);
}
$playlistActivityRepository->calculateNewSortOrder(null, $playlistActivity);
return new JsonResponse([], JsonResponse::HTTP_CREATED);
}
return new JsonResponse(
[
'error' => [
'code' => AbstractResponse::CODE_CONFLICT,
'http_code' => JsonResponse::HTTP_CONFLICT,
'message' => 'Resource Already Exists',
],
],
JsonResponse::HTTP_CONFLICT,
);
}
/**
* Remove activity from this user's favorites playlist
*
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function unfavorite(Activity $activity)
{
$user = $this...
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<?php
namespace Jiminny\Http\Controllers\API;
use Carbon\Carbon;
use ChaseConey\LaravelDatadogHelper\Datadog;
use Exception;
use Illuminate\Auth\Access\AuthorizationException;
use Illuminate\Database\Eloquent\Builder;
use Illuminate\Http\JsonResponse;
use Illuminate\Http\Request;
use Illuminate\Support\Collection;
use Illuminate\Support\Facades\Log;
use Illuminate\Validation\Rule;
use Illuminate\Validation\Rules\In;
use Illuminate\Validation\ValidationException;
use InvalidArgumentException;
use Jiminny\Component\ActivityAnalytics;
use Jiminny\Component\ActivitySearch;
use Jiminny\Component\ActivitySearch\FilterDefinitionCollection;
use Jiminny\Component\PlaybackPage\Comments\Services\ActivityCommentService;
use Jiminny\Component\Queue\Constants;
use Jiminny\Contracts\ES\Events\UpdateSingleEntity;
use Jiminny\Contracts\ES\UpdateTargetEnum;
use Jiminny\Contracts\Nudge\NudgeFactoryInterface;
use Jiminny\Contracts\Playlist\PlaylistTrackFactoryInterface;
use Jiminny\Contracts\Repositories\PlaylistActivityRepository;
use Jiminny\Contracts\Services\Crm\ServiceInterface;
use Jiminny\Enums\TeamSetting;
use Jiminny\Events\Activities\AiAutomation\ActivityProspectAdded;
use Jiminny\Events\Activities\Coaching\Coached;
use Jiminny\Contracts\Services\Crm\SupportsObjectTypeParseInterface;
use Jiminny\Exceptions\LogicException;
use Jiminny\Exceptions\SocialAccountTokenInvalidException;
use Jiminny\Http\Controllers\API\BaseController as Controller;
use Jiminny\Http\Controllers\CommentContextInterface;
use Jiminny\Http\Responses\Api\AbstractResponse;
use Jiminny\Http\Responses\Api\Response;
use Jiminny\Http\Serializers\JsonSerializer;
use Jiminny\Http\Transformers\ActivityCommentTransformer;
use Jiminny\Http\Transformers\ActivityTopicTriggerTransformer;
use Jiminny\Http\Transformers\ActivityTransformer;
use Jiminny\Http\Transformers\AvailabilityNotificationTransformer;
use Jiminny\Http\Transformers\CoachingFeedbackTransformer;
use Jiminny\Http\Transformers\CoachingSectionsTransformer;
use Jiminny\Http\Transformers\SearchTransformer;
use Jiminny\Http\Transformers\StatsTransformer;
use Jiminny\Jobs\Crm\SaveActivity;
use Jiminny\Jobs\Crm\UpdateStage;
use Jiminny\Jobs\Telephony\StartRecording;
use Jiminny\Jobs\Telephony\StopRecording;
use Jiminny\Jobs\Telephony\ToggleRecording;
use Jiminny\Models\Account;
use Jiminny\Models\Activity;
use Jiminny\Models\Activity\CoachRequest;
use Jiminny\Models\Activity\Comment;
use Jiminny\Models\Activity\Search;
use Jiminny\Models\Activity\SearchFilter;
use Jiminny\Models\Activity\Share;
use Jiminny\Models\CoachingFeedback;
use Jiminny\Models\CoachingSection;
use Jiminny\Models\CoachingSectionCriterion;
use Jiminny\Models\CoachingSectionFeedback;
use Jiminny\Models\Contact;
use Jiminny\Models\Crm\Field;
use Jiminny\Models\Crm\FieldData;
use Jiminny\Models\Crm\Layout;
use Jiminny\Models\Crm\LayoutEntity;
use Jiminny\Models\Feature\FeatureEnum;
use Jiminny\Models\LanguageDialect;
use Jiminny\Models\Lead;
use Jiminny\Models\Nudge;
use Jiminny\Models\PlaybookCategory;
use Jiminny\Models\Playlist;
use Jiminny\Models\Stage;
use Jiminny\Models\Team;
use Jiminny\Models\Track;
use Jiminny\Models\User;
use Jiminny\Repositories\CoachingFeedbackRepository;
use Jiminny\Repositories\ElasticActivityRepository;
use Jiminny\Repositories\TeamRepository;
use Jiminny\Rules\CrmReference;
use Jiminny\Rules\MultidimensionalArrayMaxCharRule;
use Jiminny\Services\ActivityService;
use Jiminny\Services\Crm\ProviderRegistry;
use Jiminny\Services\PlaybackService;
use Jiminny\Services\UserService;
use Jiminny\VO\Repository\OnDemandActivitySearch\Criteria;
use Psr\Log\LoggerInterface;
use Ramsey\Uuid\Uuid;
use Sentry;
use Symfony\Component\HttpFoundation;
final class ActivityController extends Controller implements CommentContextInterface
{
// Number of minutes to look back on activities. i.e. a timeout on activity duration.
private const int LOOK_BACK = 180;
public function __construct(
private ProviderRegistry $providerRegistry,
private ActivityService $activityService,
Response $response,
private UserService $userService,
private ActivitySearch\Service\ActivitySearch $activitySearch,
private NudgeFactoryInterface $nudgeFactory,
private ActivityCommentService $activityCommentService,
private LoggerInterface $logger,
private readonly CoachingFeedbackRepository $coachingFeedbackRepository,
private readonly TeamRepository $teamRepository,
) {
parent::__construct($response);
}
public static function getCommentImplementation(): string
{
return Comment::class;
}
public function delete()
{
$this->request->validate([
'*' => 'uuid:activities',
]);
$deletedIds = [];
foreach ($this->request->all() as $activityId) {
$activity = Activity::idOrUuId($activityId);
try {
if ($this->authorize('delete', $activity)) {
$activity->delete();
$deletedIds[] = $activityId;
\Log::info('Soft deleted activity ' . $activity->id_string . ' by user ' . $this->getUser()->id);
}
} catch (AuthorizationException $authorizationException) {
// They didn't have permission.
}
}
return $this->response->withArray($deletedIds);
}
public function update(Request $request, Activity $activity)
{
$this->authorize('updateMetadata', $activity);
$request->validate([
'title' => 'string|max:250',
'category_id' => 'uuid:playbook_categories',
'language' => [
new In(
LanguageDialect::query()
->with('language')
->cursor()
->map(static function (LanguageDialect $languageDialect): string {
return $languageDialect->getLanguageLocale();
})
->all()
),
],
]);
if ($request->has('title')) {
$activity->title = $request->input('title');
}
if ($request->has('category_id')) {
$category = PlaybookCategory::uuid($request->input('category_id'));
if ($category->playbook->team_id !== $request->user()->team_id) {
return $this->response->errorNotFound('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
if ($request->has('language')) {
if (! $activity->isInProgress()) {
return $this->response->withError(
'Activity language can only be set while the meeting is in progress.',
400
);
}
$activity->setLanguageCode($request->input('language'));
}
$activity->save();
return $this->response->withOk();
}
// XXX: This should be merged with the update method.
/**
* @param Activity $activity
*
* @throws AuthorizationException
* @throws SocialAccountTokenInvalidException
*
* @return mixed
*/
public function summarize(Activity $activity): mixed
{
$this->logger->info('[Log Activity] Summarizing activity ', [
'activityId' => $activity->getUuid(),
'payload' => $this->request->all(),
]);
$this->authorize('update', $activity);
$this->logger->info('[Log Activity] Validating summary');
// Validate the payload.
$this->validateSummary($activity);
// All objects must belong to this team.
/** @var User $user */
$user = $this->request->user();
$team = $user->getTeam();
$crmService = $this->providerRegistry->get($team->crm->provider);
try {
$crmUser = $user;
if ($user->isCrmRequired() === false) {
$crmUser = $team->owner;
}
$crmService->setUser($crmUser);
} catch (SocialAccountTokenInvalidException $accountTokenInvalidException) {
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($accountTokenInvalidException->getMessage());
}
$rawEntities = $this->request->input('entities');
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid(
$this->request->input('layout_id')
);
// Delay execution of CRM jobs to avoid locking issues.
$jobDelay = 0;
// If we have arrived from a notification, mark it as read.
$notificationId = $this->request->input('nId');
if ($notificationId) {
$notification = $user->unreadNotifications->where('id', $notificationId)->first();
if ($notification) {
$notification->markAsRead();
}
}
$title = $this->request->input('title');
$prospects = $this->request->input('prospects');
$opportunityId = $this->request->input('opportunity_id');
$stageId = $this->request->input('stage_id');
$categoryId = $this->request->input('category_id');
$summary = $this->request->input('summary');
$crmProviderId = $this->request->input('crm_id');
$isInternal = $this->request->input('is_internal') ?? false;
$lead = null;
$category = null;
$account = null;
$contact = null;
$opportunity = null;
$stage = null;
$callStage = null;
foreach ($prospects as $prospectData) {
$objectId = $prospectData['id'];
if ($objectId === null) {
continue;
}
$objectType = $prospectData['type'];
$this->logger->info('debug', ['prospect_data' => $prospectData]);
try {
if ($objectType === null) {
$this->logger->info('no object type');
if ($crmService instanceof SupportsObjectTypeParseInterface) {
$objectType = $crmService->parseObjectType($objectId);
}
}
switch ($objectType) {
case 'lead':
$this->logger->info('Processing lead');
/** @var Lead|null $lead */
$lead = $team->crm->leads()->where('crm_provider_id', $objectId)->first();
// Lead does not exist locally, import it.
if ($lead === null) {
$this->logger->info('Lead does not exist locally');
/** @var Lead $lead */
$lead = $crmService->syncLead($objectId);
}
$this->logger->info('Lead found', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
if ($stageId === null) {
$this->logger->info('Stage ID is null');
// If it was not provided, just assume it is the current stage.
$callStage = $lead->stage;
break;
}
$this->logger->info('Looking for stage');
// Determine if they have changed the stage.
/** @var Stage $stage */
$stage = $team->crm->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_LEAD)
->firstOrFail();
$this->logger->info('Stage found', ['stageId' => $stage->id, 'lead_stage' => $lead->stage_id]);
if ($lead->stage_id && $lead->stage_id !== $stage->id) {
$this->logger->info('Stage has changed');
// Storage current stage on activity.
$callStage = $lead->stage;
// The stage has changed, update in remote CRM.
dispatch(new UpdateStage($activity, $lead, $callStage, $stage));
$this->logger->info(
sprintf(
'[%s] User changing lead stage from %s to %s',
$crmService->getDisplayName(),
$callStage->getName(),
$stage->getName()
),
[
'user' => $user->getUuid(),
'lead' => $lead->getUuid(),
]
);
} else {
$this->logger->info('Stage has not changed');
// Stage remains as current.
$callStage = $stage;
}
break;
case 'account':
$this->logger->info('Processing account');
// If the object is not a lead, it should be an account.
$account = $team->crm->accounts()->where('crm_provider_id', $objectId)->first();
// Account does not exist locally, import it.
if ($account === null) {
$this->logger->info('Account does not exist locally');
$account = $crmService->syncAccount($objectId);
}
$this->logger->info('Account found', ['accountId' => $account->id]);
break;
case 'contact':
$this->logger->info('processing contact');
$contact = $team->crm->contacts()->where('crm_provider_id', $objectId)->first();
// Contact does not exist locally, import it.
if (! $contact instanceof Contact) {
$this->logger->info('contact does not exist locally');
$contact = $crmService->syncContact($objectId);
}
$this->logger->info('resolving account');
$account = $this->resolveAccount($team, $contact, $crmService, $prospects);
break;
}
// If they have specified an opportunity, retrieve this with stage.
if ($opportunityId) {
$this->logger->info('opportunity id is set');
$opportunity = $team->crm->opportunities()->where('crm_provider_id', $opportunityId)->first();
// Opportunity does not exist locally, import it.
if ($opportunity === null) {
$this->logger->info('opportunity does not exist locally');
$opportunity = $crmService->syncOpportunity($opportunityId);
}
if ($stageId === null) {
$this->logger->info('stage id is null');
// If it was not provided, just assume it is the current stage.
$callStage = $opportunity->stage ?? null;
} else {
$this->logger->info('looking for stage');
/** @var ?Stage $opportunityStage */
$opportunityStage = $team->crm
->stages()
->uuid($stageId, false)
->where('type', Stage::TYPE_OPPORTUNITY)
->first();
// There is a chance we still cannot import this opportunity.
if ($opportunityStage !== null && $opportunity !== null && $opportunity->stage_id !== $opportunityStage->id) {
$this->logger->info('opportunity stage has changed');
// Storage current stage on activity.
$callStage = $opportunity->stage;
dispatch(new UpdateStage($activity, $opportunity, $callStage, $opportunityStage));
$this->logger->info(
sprintf(
'[%s] User changing opportunity stage from %s to %s',
$crmService->getDisplayName(),
$callStage->name,
$opportunityStage->name
),
[
'userId' => $user->id_string,
'opportunityId' => $opportunity->id_string,
]
);
} else {
$this->logger->info('opportunity stage has not changed');
// Stage remains as current.
$callStage = $opportunityStage;
}
}
}
if ($crmProviderId) {
// Cast $crmProviderId to string otherwise it won't use database index for some records
$linkedActivity = Activity::where('crm_provider_id', (string) $crmProviderId)->first();
// Check if this activity has already been assigned to a different activity.
if ($linkedActivity && $linkedActivity->id !== $activity->id) {
throw new InvalidArgumentException(
'Sorry, the linked task has already been logged under a different call. '
. 'Please choose another linked task.'
);
}
}
} catch (InvalidArgumentException $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorWrongArgs($exception->getMessage());
} catch (Exception $exception) {
$this->logger->error('Failed to process prospect', [
'prospect_data' => $prospectData,
'reason' => $exception->getMessage(),
]);
// Return a JSON response with the response array and status code.
return $this->response->errorInternalError(
'Sorry, an error occurred. Please try again or reach out to support if the problem continues.'
);
}
}
if ($categoryId) {
$category = PlaybookCategory::uuid($categoryId);
if ($category->playbook->team_id !== $team->id) {
throw new InvalidArgumentException('Sorry, this category does not belong to your playbook.');
}
$activity->playbook_category_id = $category->id;
}
$this->logger->info('Prospect data', [
'lead_id' => $lead?->getId(),
'account_id' => $account?->getId(),
'contact_id' => $contact?->getId(),
'opportunity_id' => $opportunity?->getId(),
'stage_id' => $stage?->getId(),
]);
if ($title) {
$activity->title = $title;
}
if ($summary) {
$activity->summary = $summary;
}
if ($crmProviderId) {
$activity->crm_provider_id = $crmProviderId;
}
if ($callStage) {
$this->logger->info('Setting stage id', ['stageId' => $callStage->id]);
$activity->stage_id = $callStage->id;
}
if ($lead) {
$this->logger->info('Setting lead id', ['leadId' => $lead->id]);
$activity->lead_id = $lead->id;
// If we are changed from an account > lead, unset the account data.
$this->logger->info('Unsetting account id, opportunity id, contact id, value');
$activity->account_id = null;
$activity->opportunity_id = null;
$activity->contact_id = null;
$activity->value = null;
}
if ($account) {
$this->logger->info('Setting account id', ['accountId' => $account->id]);
$activity->account_id = $account->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('unsetting lead id');
$activity->lead_id = null;
// Unset the contact if switching different accounts. Will be set up below if still applicable.
if (! $team->hasFeature(FeatureEnum::LINK_ACTIVITY_TO_MULTIPLE_PROSPECTS) || empty($contact)) {
$this->logger->info('Unsetting contact id');
$activity->contact_id = null;
}
}
if ($opportunity) {
$this->logger->info('setting opportunity id', ['opportunityId' => $opportunity->id]);
$this->logger->info('unsetting lead id');
$activity->opportunity_id = $opportunity->id;
$activity->value = $opportunity->value;
// If we are changed from an lead > account, unset the lead data.
$activity->lead_id = null;
}
if ($contact) {
$this->logger->info('setting contact id', ['contactId' => $contact->id]);
$activity->contact_id = $contact->id;
// If we are changed from an lead > account, unset the lead data.
$this->logger->info('Unsetting lead id');
$activity->lead_id = null;
}
$activity->is_internal = $isInternal;
$activity->save();
$activity->refresh();
$this->logger->notice('Activity saved', [
'activity_id' => $activity->getId(),
'lead_id' => $activity->lead_id,
'account_id' => $activity->account_id,
'contact_id' => $activity->contact_id,
'opportunity_id' => $activity->opportunity_id,
'stage_id' => $activity->stage_id,
'crm_provider_id' => $activity->getCrmProviderId(),
]);
// Store entities as field data on the activity.
$updatedData = $this->storeEntities($crmService, $activity, $layout, $rawEntities);
if ($activity->isLoggable()) {
// Follow-up Task or Event data.
$followupData = $this->fetchFollowupEntities($crmService, $layout, $rawEntities);
$this->logger->info('CRM LOG manual log triggered', [
'activityId' => $activity->getUuid(),
'followupData' => $followupData,
'userId' => $user->getUuid(),
]);
// Store data in the CRM.
// ++add check for crm_required
$job = new SaveActivity($activity, $followupData);
if ($updatedData) {
$job->delay(Carbon::now()->addMinutes($jobDelay));
}
dispatch($job);
// Manually dispatch log for Opportunity or Prospect added
if ($activity->hasOpportunity() || $activity->hasProspect()) {
event(new ActivityProspectAdded(
activity: $activity,
eventSource: 'manually-log-crm-data'
));
}
}
return $this->response->withOk();
}
/**
* Extract any activity data to be upserted in the Lead/Opportunity/Task etc in the CRM.
*
* @param ServiceInterface $service
* @param Activity $activity
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function storeEntities(ServiceInterface $service, Activity $activity, Layout $layout, array $entities): array
{
$updatedData = [];
$existingData = $activity->data()->get();
// We need to delete any existing data to overwrite with latest values.
$activity->data()->delete();
$layoutEntities = $layout->entities()
->with('field', 'parent')
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->get();
/** @var LayoutEntity $entity */
foreach ($layoutEntities as $entity) {
// If the user has provided a value for this entity
if (array_key_exists($entity->id_string, $entities)) {
$value = $entities[$entity->id_string];
// Convert raw data into values that the CRM can consume.
if ($value) {
$value = $service->normalizeValue($entity->field->type, $value);
}
// Check the field is part of the activity-summary section.
if ($entity->parent && $entity->parent->label === 'activity-summary' && $value) {
// This is the internal database ID, not the external CRM ID.
$objectId = null;
switch ($entity->field->object_type) {
case Field::OBJECT_ACCOUNT:
$objectId = $activity->account_id;
break;
case Field::OBJECT_CONTACT:
$objectId = $activity->contact_id;
break;
case Field::OBJECT_OPPORTUNITY:
$objectId = $activity->opportunity_id;
break;
case Field::OBJECT_LEAD:
$objectId = $activity->lead_id;
break;
case Field::OBJECT_TASK:
case Field::OBJECT_EVENT:
$objectId = $activity->id;
break;
}
if ($objectId) {
/** @var FieldData $data */
$data = $activity->data()->create([
'crm_layout_entity_id' => $entity->id,
'crm_field_id' => $entity->crm_field_id,
'object_type' => $entity->field->object_type,
'object_id' => $objectId,
'value' => $value,
]);
// Never send read-only field data to the CRM.
if ($entity->read_only === false && $entity->is_visible) {
$existingValue = $existingData
->where('crm_layout_entity_id', $entity->id)
->where('crm_field_id', $entity->crm_field_id)
->where('object_type', $entity->field->object_type)
->where('object_id', $objectId)
->first();
// If the field was actually changed, we need to reflect this in the CRM too.
if ($existingValue === null || $existingValue->value !== $value) {
$updatedData[] = $data->id;
}
}
}
}
}
}
return $updatedData;
}
/**
* Extract any followup data to be dispatched in a job to create a new Task/Event in the CRM.
*
* @param ServiceInterface $crmService
* @param Layout $layout
* @param array $entities The raw entity data from user
*
* @return array
*/
private function fetchFollowupEntities(ServiceInterface $crmService, Layout $layout, array $entities): array
{
$fieldData = [];
foreach ($entities as $entityId => $value) {
// Only bother with fields that have a value.
if ($value) {
// Extract the entity from the UUID. Check the field is valid and part of the follow-up section.
$entity = $layout->entities()
->uuid($entityId, false)
->whereHas('parent', function ($query) {
$query->where('label', 'follow-up');
})
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->first();
if ($entity) {
// Convert raw data into values that the CRM can consume.
$value = $crmService->normalizeValue($entity->field->type, $value);
// Add the field and value to the payload.
$fieldData += [
$entity->field->crm_provider_id => $value,
];
}
}
}
return $fieldData;
}
/**
* @param Activity $activity
*/
private function validateSummary(Activity $activity): void
{
$team = $activity->user->team;
$crmProvider = $team->crm->provider;
$attributes = [];
$rules = [
'layout_id' => 'required|uuid:crm_layouts,crm_configuration_id,' . $team->crm_id,
'title' => 'string|max:250',
'prospects' => 'required|array',
'opportunity_id' => new CrmReference($crmProvider),
'category_id' => 'uuid:playbook_categories|required_unless:is_internal,true',
'stage_id' => 'uuid:stages,team_id,' . $team->id, // Todo: move to proper validator
'summary' => 'max:50000',
'nId' => 'exists:notifications,id',
'crm_id' => new CrmReference($crmProvider),
'entities' => 'array',
'is_internal' => 'boolean',
];
/** @var Layout $layout */
$layout = $team->crm->layouts()->uuid($this->request->input('layout_id'));
// Only validate fields, not headers etc. If not loggable, we don't care about follow-up section.
$entities = $layout->entities()
->where('read_only', 0)
->whereHas('field', function ($query) {
$query->where('is_selectable', 1);
})
->whereHas('parent', function ($query) use ($activity) {
if ($activity->isLoggable() === false) {
$query->where('label', '<>', 'follow-up');
}
});
$isInternal = $this->request->input('is_internal', false);
foreach ($entities->get() as $entity) {
$rules += $this->buildFieldValidator($entity, $isInternal);
$attributes += $this->buildFieldMessage($entity);
}
$this->request->validate($rules, [], $attributes);
}
private function buildFieldValidator(LayoutEntity $entity, bool $isInternal): array
{
return [
'entities.' . $entity->id_string => $entity->getValidator($isInternal),
];
}
/**
* @param LayoutEntity $entity
*
* @return array
*/
private function buildFieldMessage(LayoutEntity $entity): array
{
$label = $entity->label;
if ($label === null) {
$label = $entity->field->label;
}
return [
'entities.' . $entity->id_string => $label,
];
}
public function search(Request $request, ElasticActivityRepository $repository): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->debugLog(
$user,
'User extracted from request',
['user' => $user->getId(), 'tz' => $user->getTimezone()]
);
$searchCriteria = Criteria::createFromRequest($request->all(), $user->getTimezone());
$this->debugLog(
$user,
'ActivitySearch criteria built',
['searchCriteria' => $searchCriteria]
);
$filterSet = $this->activitySearch->getHomepageFilterSet($searchCriteria, $user);
$this->debugLog($user, 'FilterSet built', ['filterSet' => $filterSet]);
$this->validateSearch($request, $filterSet);
$this->debugLog($user, 'Request validated');
$searchResponse = $repository->onDemandSearch($user, $searchCriteria, $filterSet);
/** @var Collection<Activity> $activities */
$activities = $searchResponse['results'];
$this->debugLog($user, 'Activities ES response extracted');
$hideInternalMeetingsSetting = $this->teamRepository->getTeamSettingByTeamId(
$user->getTeamId(),
TeamSetting::HIDE_INTERNAL_SCHEDULED_MEETINGS->name(),
);
if ($hideInternalMeetingsSetting?->getValue() === '1') {
$activities = $activities->filter(function (Activity $activity) {
if ($activity->is_internal && empty($activity->actual_start_time)) {
return false;
}
return true;
});
}
$this->debugLog($user, 'Internal meetings (?!) filtered');
$this->response->getManager()
->parseIncludes([
'category',
'organizer.group',
'prospect',
'stage',
'opportunity',
'stats',
'scorecards',
'masterTrack',
'activeParticipants',
'notification',
])
->setSerializer(new JsonSerializer());
$transformerExcludes = $this->request->input('exclude');
if ($transformerExcludes) {
$this->response->getManager()->parseExcludes($transformerExcludes);
}
$this->debugLog($user, 'Response Manager (?!) applied');
$transformer = new ActivityTransformer();
$transformer->setConsumer($user);
$this->debugLog($user, 'Activity Transformer added');
$resource = new \League\Fractal\Resource\Collection($activities, $transformer);
$page = $searchCriteria->getPageNumber();
$this->debugLog($user, 'Search criteria page number called', ['page' => $page]);
$histogram = array_pluck(array_get($searchResponse, 'histogram.buckets', []), 'doc_count', 'key_as_string');
$this->debugLog($user, 'Histogram generated. Response is ready.', ['histogram' => $histogram]);
return $this->response->withArray([
'pagination' => [
'total' => $searchResponse['totalHits'],
'current' => $page,
'prev' => max($page - 1, 1),
'next' => $page + 1,
],
'results' => $this->response->getManager()->createData($resource)->toArray(),
'histogram' => $histogram,
]);
}
private function debugLog(User $user, string $logMessage, ?array $context = []): void
{
// Debug for Learning People Only
if ($user->getTeamId() !== 260) {
return;
}
Log::notice(
sprintf('[activity-search-controller] %s', $logMessage),
$context
);
}
/** @throws ValidationException */
private function validateSearch(Request $request, FilterDefinitionCollection $filterSet, ?string $prefix = null): void
{
$rules = [
'exclude' => 'array',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
];
if ($prefix !== null && mb_strpos($prefix, '.') !== false) {
$rules[rtrim($prefix, '.')] = sprintf(
'required|array|max:%d',
$filterSet->count()
);
}
$validationRules = $filterSet->getValidationRules($prefix)
->merge($rules)
->all();
$request->validate($validationRules);
}
public function createActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$search = $this->updateOrCreateActivitySearch($request);
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function updateActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('update', $search);
$this->updateOrCreateActivitySearch($request, $search);
return $this->response->withOk();
}
private function storeNamedSearchFilters(
Collection $request,
Search $search,
FilterDefinitionCollection $filterSet,
?string $prefix = null,
): self {
$arrayTypeProperties = $filterSet
->getPropertyTypes([
FilterDefinitionCollection::PROPERTY_TYPE_ARRAY,
])
->all();
$supportedRequestProperties = $filterSet->getSupportedRequestProperties($prefix);
foreach ($supportedRequestProperties as $requestPropertyName) {
if (! array_has($request, $requestPropertyName)) {
continue;
}
/** @var string|string[] $propertyValue */
$propertyValue = array_get($request, $requestPropertyName);
$propertyName = $prefix === null
? $requestPropertyName
: mb_substr($requestPropertyName, mb_strlen($prefix));
$isArrayType = array_has($arrayTypeProperties, $propertyName);
if (! $isArrayType) {
/** @var string $requestPropertyValue */
$search->filters()->updateOrCreate(
[
'filter' => $propertyName,
],
[
'value' => $propertyValue,
]
);
continue;
}
/** @var string[] $requestPropertyValue */
/** @var SearchFilter[]|Collection $existingFilterValues */
$existingFilterValuesKeyed = $search->filters()
->where('filter', $propertyName)
->get()
->keyBy('id');
// Iterate over values provided as request parameters
foreach ($propertyValue as $value) {
/** @var SearchFilter|null $valueFilter */
$valueFilter = $search->filters()
->where(
[
'filter' => $propertyName,
'value' => $value,
]
)
->first();
if ($valueFilter !== null) {
// Remove filter value pair from list to be deleted
$existingFilterValuesKeyed->forget($valueFilter->id);
} else {
// Add new filter/value pair
$search->filters()->updateOrCreate([
'filter' => $propertyName,
'value' => $value,
]);
}
}
// Delete filter value pairs for this filter that no longer exist in request parameters
foreach ($existingFilterValuesKeyed as $existingFilter) {
$existingFilter->delete();
}
}
/** @var Collection<int, SearchFilter> $filtersKeyed */
$filtersKeyed = $search->filters()->get()->keyBy('filter');
// wipe removed filters from this search
foreach ($filtersKeyed as $filterName => $filter) {
if (array_has($request, $prefix . $filterName)) {
continue;
}
// Remove all filter values for this filter
$search->filters()->where('filter', $filterName)->delete();
}
return $this;
}
/**
* @throws AuthorizationException
*/
public function fetchActivitySearch(
Search $search,
Request $request,
SearchTransformer $searchTransformer,
): JsonResponse {
$this->authorize('view', $search);
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withItem(
$search,
$searchTransformer
->withConsumer($user)
);
}
public function listActivitySearch(Request $request, SearchTransformer $searchTransformer): JsonResponse
{
/** @var User $user */
$user = $request->user();
$this->response
->getManager()
->setSerializer(new JsonSerializer());
return $this->response->withCollection(
$user->searches()->get(),
$searchTransformer
->withConsumer($user)
);
}
/**
* Deletes a saved search
*
* @param Request $request
* @param Search $search
*
* @throws Exception
*
* @return JsonResponse
*/
public function deleteActivitySearch(Request $request, Search $search): JsonResponse
{
$this->authorize('delete', $search);
// Orphan any AutomatedReports that use this search
$search->automatedReports()->withTrashed()->update(['activity_search_id' => null]);
// Delete filters and the search itself
$search->filters()->delete();
$search->delete();
return $this->response->withOk();
}
public function live(Request $request, ElasticActivityRepository $repository): JsonResponse
{
$user = $this->getUserFromRequest($request);
$this->request->validate([
'sort_direction' => 'in:asc,desc',
'limit' => 'integer|min:1|max:50',
'page' => 'integer|min:1',
]);
$activities = $repository->getLiveCoachingEligibleActivities(
user: $user,
lookBackMinutes: self::LOOK_BACK,
limit: (int) $this->request->input('limit', 25),
page: (int) $this->request->input('page', 1),
sortBy: ['actual_start_time', 'scheduled_start_time'],
sortDirection: (string) $this->request->input('sort_direction', 'asc'),
);
$this->response
->getManager()
->parseIncludes(['organizer.group', 'prospect'])
->setSerializer(new JsonSerializer());
return $this->response->withCollection($activities, new ActivityTransformer());
}
/**
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function show(Activity $activity, ActivityService $activityService): JsonResponse
{
$this->authorize('show', $activity);
$user = $activity->getUser();
$team = $user->getTeam();
// Sync the opportunity with the latest data if possible.
if ($activity->opportunity_id) {
try {
$crmService = $this->providerRegistry->get($team->crm->provider);
if (! $user->isCrmRequired()) {
$crmService->setUser($team->getOwner());
} else {
$crmService->setUser($user);
}
$crmService->syncOpportunity($activity->opportunity->crm_provider_id);
} catch (Exception $exception) {
// Move on.
}
}
$activityData = $activityService->getActivityData($this->request->user(), $activity);
return response()->json($activityData);
}
public function createRecording(Activity $activity)
{
$this->authorize('record', $activity);
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Tell Twilio to start recording this activity.
if ($activity->recording_state === Activity::RECORDING_OFF) {
$job = (new StartRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withCreated();
}
return $this->response->errorGone('Activity is already recording.');
}
public function updateRecording(Request $request, Activity $activity)
{
$this->authorize('record', $activity);
$request->validate([
'preference' => 'boolean',
'state' => [
'string',
Rule::in([
Activity::RECORDING_IN_PROGRESS,
Activity::RECORDING_PAUSED,
]),
],
]);
if ($request->has('state')) {
if ($activity->hasRecordingReasonComplianceRestricted()) {
return $this->response->errorGone('Recording this number has been disabled by your organization.');
}
// Toggle the recording state between paused and resumed.
if (! $activity->isRecordingState(Activity::RECORDING_OFF)) {
$job = (new ToggleRecording($activity, $request->input('state')))
->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Recording is not toggleable.');
}
if ($request->has('preference')) {
$activity->update([
'recording_preference' => $request->input('preference') ? 1 : 0,
]);
return $this->response->withOk();
}
return $this->response->errorWrongArgs('Something went wrong');
}
public function stopRecording(Activity $activity)
{
$this->authorize('stopRecord', $activity);
// Tell Twilio to stop recording this activity.
if ($activity->isRecordingState(Activity::RECORDING_IN_PROGRESS)) {
$job = (new StopRecording($activity))->onQueue(Constants::QUEUE_CONFERENCES);
dispatch($job);
return $this->response->withOk();
}
return $this->response->errorGone('Activity is not recording.');
}
/**
* Add activity to this user's favorites playlist
*
* @throws AuthorizationException
*/
public function favorite(Activity $activity, PlaylistActivityRepository $playlistActivityRepository): JsonResponse
{
$this->authorize('favorite', $activity);
$user = $this->getUserFromRequest($this->request);
$favorite = $activity->wasFavoritedBy($user);
$name = $activity->activity_title ?? '';
// It needs to check at least one record.
if (! $favorite) {
$favoritePlaylist = $user->favoritePlaylist();
$playlistActivity = $playlistActivityRepository->findByBaseActivityUserAndPlaylist(
$activity,
$user,
$favoritePlaylist
);
if ($playlistActivity !== null) {
$playlistActivity->update(
// Just update, don't sort.
['start_time' => 0, 'name' => mb_strimwidth($name, 0, 100)],
);
} else {
$playlistActivity = $activity->playlistActivities()->create([
'playlist_id' => $favoritePlaylist->getId(),
'user_id' => $user->getId(),
'start_time' => 0,
'name' => mb_strimwidth($name, 0, 100),
]);
// Sort it on top.
$playlistActivity->update(
[
'sort' => $playlistActivityRepository->calculateNewSortOrder(
null,
$playlistActivity,
),
],
);
}
$playlistActivityRepository->calculateNewSortOrder(null, $playlistActivity);
return new JsonResponse([], JsonResponse::HTTP_CREATED);
}
return new JsonResponse(
[
'error' => [
'code' => AbstractResponse::CODE_CONFLICT,
'http_code' => JsonResponse::HTTP_CONFLICT,
'message' => 'Resource Already Exists',
],
],
JsonResponse::HTTP_CONFLICT,
);
}
/**
* Remove activity from this user's favorites playlist
*
* @param Activity $activity
*
* @throws AuthorizationException
*
* @return mixed
*/
public function unfavorite(Activity $activity)
{
$user = $this...
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faVsco.js – console [PROD]
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