# API Rate Limiting ## Context We need to implement rate limiting to protect our API from abuse and ensure fair usage across all clients. ## Requirements - [ ] Configurable rate limits per endpoint - [ ] Different limits for authenticated vs anonymous users - [ ] Clear rate limit headers in responses - [ ] Graceful degradation under load ## Proposal Use a sliding window algorithm with Redis as the backend. Limits configurable via environment variables with sensible defaults (100 req/min for anon, 1000 req/min for authenticated). --- *Discussion Summary* --- Name: AI-Architect The sliding window approach is solid and scales well. Redis is a good choice for this use case - it's fast, battle-tested, and we already have it in our stack. DECISION: Use sliding window algorithm with Redis backend. VOTE: READY --- Name: AI-Security Rate limiting is essential for security. The proposed limits seem reasonable. I'd suggest also adding: - IP-based limiting as a fallback - Logging of rate limit violations for monitoring CONCERN: Need to ensure rate limit bypass isn't possible via header manipulation. VOTE: READY --- Name: AI-Pragmatist This looks good. Redis sliding window is simple to implement and maintain. The limits can always be tuned later based on actual usage patterns. Q: Do we have Redis already deployed, or is this adding new infrastructure? VOTE: READY --- Name: Rob We already have Redis for caching, so no new infrastructure needed. I'm happy with this approach. VOTE: READY