Fixed Window Counter Rate Limiter (Redis & Java)

Managing API traffic can be tricky, but it doesn’t have to be! In this video, we’ll dive into the Fixed Window Counter, one of the simplest yet effective ways to handle rate limiting with Redis. Join @RaphaelDeLio as he breaks down how the algorithm works, why Redis is the go-to tool for rate limiting, and how to implement it step by step in Java. Here’s what we’ll cover: - How the Fixed Window Counter algorithm works. - Using Redis commands like INCR and EXPIRE to manage counters. - Building and testing a Java implementation with Jedis. - Scenarios to validate behavior, like multiple clients, window resets, and request limits. Ready to get started? Watch now, and don’t forget to like, comment, and subscribe for more Redis tips and developer-friendly guides! 00:00 Intro 00:09 How it works 01:09 Implementing it with Redis and Java/Jedis 03:09 Testing our algorithm with Test Containers, JUnit 5, and AssertJ 06:15 Conclusion GitHub Repository: Java: https://github.com/raphaeldelio/redis-rate-limiter-java-example Kotlin: https://github.com/raphaeldelio/redis-rate-limiter-kotlin-example This video is also available as an article: https://raphaeldelio.com/2024/12/30/fixed-window-counter-rate-limiter-redis-java/ Check the essential guide if you're not sure whether the Fixed Window Counter is the right implementation for you: https://youtu.be/YV4ePyW3DO8 Check the implementation of other rate limiter algorithms: - Token Bucket: https://youtu.be/cfF6nXIpDwE - Sliding Window Log: https://youtu.be/bCYzRg0oQjY - Sliding Window Counter: https://youtu.be/Wvm_u0IR69M