How to Implement Distributed Rate Limiting in Spring Boot | Bucket4j + Redis
In this video, we implement DISTRIBUTED rate limiting in Spring Boot using Bucket4j and Redis with Java 17.
Source Code: https://github.com/TrendyCodeBytes/Distrib...
This is a production-ready approach that works across multiple application instances and avoids common in-memory rate limiting issues.
What you’ll learn:
What rate limiting is and why it’s important
Token Bucket algorithm explained with a clear mental model
Why Redis is required for distributed rate limiting
How Bucket4j works internally
Spring Boot interceptor-based rate limiting
Redis CAS-based bucket storage
Live testing using Postman
Tech Stack:
Java 17
Spring Boot 3
Bucket4j
Redis
Lettuce Redis Client
Docker
Rate Limit Configuration:
2 requests per minute per client
Redis-backed buckets
HTTP 429 response when limit is exceeded
Prerequisites:
Java 17
Docker
Redis running before starting the application
Redis Docker Command:
docker run -d --name redis -p 6379:6379 redis
This tutorial is perfect for backend developers, Java developers, and anyone building scalable APIs with Spring Boot.
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Comment if you want advanced topics like Spring Security integration or API key rate limiting.