Rate Limit Handling

Rate limit handling

Rate limits are a contract, and hitting them repeatedly can escalate from throttling to suspension. Handling them well means staying under proactively rather than reacting to rejections.

Method

1. Read the limit headers, not just the errors. Providers report remaining quota and reset time, which allows slowing down before being rejected.
2. Honour the retry-after value. It is the provider telling you exactly when to return, and ignoring it is what turns throttling into a block.
3. Throttle client-side to stay under. A token bucket sized below the limit prevents most rejections entirely (see rate-limiting).
4. Back off exponentially with jitter. Synchronised retries from many workers reproduce the burst that caused the limit (see timeouts-and-retries).
5. Queue rather than drop where the work matters. Deferring work to stay within quota is usually better than failing it, provided the queue is bounded.
6. Batch where the API supports it. One request for fifty records uses one unit of quota rather than fifty, which is often the whole solution.
7. Monitor quota consumption as a metric. Approaching the limit is a capacity signal that needs action before it becomes errors (see alerting-design).

Boundaries

Limits vary by endpoint, plan, and time, and are sometimes undocumented. Client-side throttling requires coordination across instances to be accurate. Persistent limit pressure is a capacity problem needing a plan change or an architectural one.