⚡ Backend Advanced
⏱️ 9 min
Distributed API Rate Limiting with NATS KV
Moving from local in-memory limits to cluster-aware NATS KV partitions for fair, durable API throttling in distributed deployments.
By Victor Robin • • Updated:
Introduction
In-memory limiters break down once traffic spans multiple pods. BlueRobin uses NATS KV-backed rate limiter components to keep enforcement consistent across instances.
Core Idea
- Prefer user-based keys when authenticated.
- Fall back to anonymized network identity when not authenticated.
- Store and update counters in distributed storage rather than pod memory.
Operational Benefits
- Consistent throttling under horizontal scale.
- Better fairness for multi-instance APIs.
- Easier reasoning during incident response.
Conclusion
Distributed rate limiting is a platform concern, not just an API concern. Centralizing limiter state makes policy behavior predictable.
Related reading:
/nats-kv-idempotent-workers-cas//error-handling-resilience-patterns-dotnet/