orchestrated-discussions/examples/voted_discussion.discussion.md

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<!-- DISCUSSION -->
<!-- Title: API Rate Limiting -->
<!-- Phase: consensus_vote -->
<!-- Status: OPEN -->
<!-- Created: 2025-12-08T14:00:00Z -->
<!-- Template: feature -->
<!-- Participants: architect, security, pragmatist, rob -->
# 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).
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*Discussion Summary*
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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
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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
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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
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Name: Rob
We already have Redis for caching, so no new infrastructure needed. I'm happy with this approach.
VOTE: READY