Rate Limiting Java REST APIs
Approaches Token bucket for burst+steady control; sliding window for fairness. Enforce at edge (gateway/ingress) plus app-level for per-tenant safety. Spring implementation Use filters/interceptors with Redis/Lua for atomic buckets. Key by tenant/user/IP; return 429 with Retry-After. Expose metrics per key and rule; alert on near-capacity. Considerations Separate auth failures from rate limits; avoid blocking login endpoints too aggressively. Keep rule configs dynamic; hot-reload from config store. Combine with circuit breakers/timeouts for upstream dependencies. Checklist Edge and app-level limits defined. Redis-based atomic counters/buckets with TTL. Metrics + logs for limit decisions; alerts in place.