Exposing public or enterprise API endpoints without rate limiting leaves backend services vulnerable to DDoS attacks, credential stuffing, and resource exhaustion.
1. Fixed Window vs. Sliding Window
Fixed window counters suffer from traffic spikes at window boundaries. The sliding window log algorithm provides smooth, accurate throttling across sliding time intervals.
2. Atomic Rate Limiting with Redis Lua Scripts
Executing sliding window counter increments inside atomic Redis Lua scripts guarantees thread safety and prevents race conditions under high concurrent requests.
3. HTTP Header Standards
Returning standard IETF rate limit headers (`X-RateLimit-Limit`, `X-RateLimit-Remaining`, `Retry-After`) informs client applications when to throttle back requests.