How to Stop Getting Rate Limited by Your Own Vendors

Every vendor publishes some form of rate limit, usually requests per minute per API key, sometimes a shared ceiling across your whole account. That published number is rarely what actually breaks you. What breaks you is your own code opening more concurrent calls than you intended, often because an autoscaler added instances or a batch job and a user-facing request happened to overlap.

Before you touch retry logic, separate the two questions: what does the vendor actually allow, and what does your system actually attempt at peak. If your peak concurrency is well under the documented limit and you're still getting throttled, you're likely hitting an undocumented per-second burst limit rather than the per-minute number in the docs.

A 429 response is not one thing. Check for a Retry-After header first; if the vendor tells you exactly how long to wait, honor that instead of guessing. If there's no header, exponential backoff with jitter avoids every failed caller retrying at the same instant and reproducing the same spike a second later.

Also distinguish a hard quota rejection, you've used your entire monthly allotment, from a transient throttle, you sent too many requests in one second. The first needs a business conversation with the vendor or your own usage; the second just needs better pacing.

When more than one team or job calls the same vendor, an unmanaged shared quota turns into a race: whichever job runs first that hour eats the budget. A token bucket per consumer, with a priority tier for user-facing requests over a nightly batch job, keeps one team's backfill from starving another team's live traffic.

Have batch jobs back off automatically during business hours and take the leftover quota overnight. That single rule fixes more vendor throttling incidents than any amount of retry tuning.

If your steady-state usage is regularly close to the documented limit and the traffic driving it is genuine user activity, that's a real case for asking the vendor for a limit increase, and bring usage data to that conversation. If the pressure only shows up during a nightly batch window, redesigning the batch job to spread its calls over a longer window usually solves it for free, without waiting on a vendor's account team.

• Confirm the published per-key and per-account limits, and whether they're shared across your whole organization or scoped to one API key.
• Build backoff and jitter into the integration before its first production call, not after the first outage.
• Set an internal alert at a share of the documented limit so you see the trend coming instead of finding out from a 429.
• Decide up front which of your own jobs are allowed to be delayed if quota gets tight, and which are not.

A limit increase request lands very differently with real numbers attached than as a vague complaint about getting throttled. Pull your actual peak requests per minute over the last month, the growth trend behind it, and which endpoints are driving the volume, and bring that to the conversation instead of asking for a round number that sounds safe.

That same data tells you something a vendor's response time never will: whether the growth is coming from genuine usage you want to keep serving, or from an inefficient integration calling the same endpoint repeatedly when it could cache the result or batch several lookups into one request. Fixing the inefficient call is usually cheaper than negotiating a bigger limit, and it's worth ruling out first.