Distributed Rate Limiting with Redis
Learn how to share rate limit state across multiple gateway and service instances using Redis, atomic operations, and Lua scripts to avoid race conditions.
The Multi-Instance Problem
When you run several gateway replicas, each one keeping its own in-memory counter means a client gets N x limit total — once per instance.
To enforce one global limit, every instance must read and update shared state.
Why Redis
Redis is the de facto choice for distributed rate limiting because it offers:
- Sub-millisecond in-memory reads and writes
- Atomic commands like
INCR - Built-in expiry for automatic window resets
- Lua scripting for multi-step atomic logic
All lessons in this course
- API Gateway Integration Patterns
- Global vs. Per-Service Rate Limiting
- Dynamic Rate Limit Configuration
- Distributed Rate Limiting with Redis