Distributed Rate Limiting with Redis
Learn to leverage Redis for building robust, scalable distributed rate limiters that work across multiple service instances.
Scaling Beyond Single Server
In previous lessons, we learned about basic rate limiting. But what happens when your application grows and runs on multiple servers?
- In-memory limits: They only track requests on a single server.
- Multiple servers: Each server has its own counter, leading to inaccurate and ineffective limits.
- The problem: Users can bypass limits by hitting different servers.
We need a way for all servers to share the same rate limit state.
Introducing Redis for Shared State
To build a distributed rate limiter, we need a centralized, fast data store accessible by all our application instances. This is where Redis shines!
- What is Redis? An open-source, in-memory data structure store.
- Why Redis? It's extremely fast, supports various data types, and is designed for concurrent access.
- Key for Rate Limiting: Its atomic operations are perfect for incrementing counters reliably across multiple services.
All lessons in this course
- In-Memory Rate Limiter Design
- Distributed Rate Limiting with Redis
- Handling Rate Limit Exceedance
- Testing and Monitoring Your Rate Limiter