orchestrated-discussions/examples/voted_discussion.discussion.md

1.7 KiB

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