Design clients for limits
Centralize rate-limit handling with token buckets and request coalescing. Shared middleware prevents every team from reinventing retry logic and accidentally DDoSing upstreams.
Surface limit headers to logs and dashboards so you can see exhaustion coming and shape traffic. Normalize limit headers across vendors for easier alerting.
Differentiate traffic by customer tier or feature; throttle non-critical work first when budgets get tight.
Retry responsibly
Use exponential backoff with jitter and cap retries based on user impact. Never retry non-idempotent calls without a compensation path.
Separate idempotent and non-idempotent calls so you do not amplify outages. Queue background work while keeping customer-facing requests responsive with cached results.
Test retry logic in staging with forced 429s and 5xx responses to confirm clients shed load instead of stampeding.
Monitor upstreams
Track vendor 429s, remaining quota, and latency with Watch.Dog and alert before customers feel it. Tag alerts with the vendor name and region for fast triage.
Test sandbox keys and production keys separately to avoid surprises. Many vendors throttle sandboxes differently or return weaker headers.
Alert customer success when throttling happens so they can preempt tickets and offer workarounds.
Plan for spikes
Pre-compute reports and heavy workflows before peak traffic. For known surges (launches, seasonal events), negotiate temporary quota increases with vendors.
Document a fail-open or fail-soft strategy per endpoint: when to serve cached data, when to queue work, and when to block to protect the platform.