Distributed Rate Limiting
Coordinate request limits across many app instances using Redis counters and atomic Lua scripts for fixed-window, sliding-window, and token-bucket algorithms.
Local Limits Do Not Scale
An in-memory rate limiter only counts requests on one server. With many app instances behind a load balancer, you need a shared view of usage. Redis, being central and atomic, is the natural coordination point.
Fixed Window Counter
The simplest algorithm: a counter per time window. INCR the key; set a TTL equal to the window on first increment. Reject when the count exceeds the limit.
INCR rl:user:42:1716900000
EXPIRE rl:user:42:1716900000 60All lessons in this course
- Distributed Locks with Redis
- Leader Election Patterns
- Redis as a Coordination Service
- Distributed Rate Limiting