Token Bucket Algorithm Explained | Rate Limiting Made Simple

Struggling to understand how rate limiting works in real-world systems? In this video, we break down the Token Bucket Algorithm—one of the most widely used techniques for controlling traffic in APIs and distributed systems. Whether you're building scalable backend systems, working with APIs, or preparing for system design interviews, this concept is a must-know. 📌 What You’ll Learn 1.What is rate limiting and why it matters 2. How the Token Bucket Algorithm works (step-by-step) 3. Real-world analogy to simplify understanding 4. Practical use cases in APIs and microservices 5. When to use Token Bucket in production systems Why This Matters Modern applications (like payment systems, login APIs, and SaaS platforms) must handle millions of requests without crashing. Rate limiting ensures: 1. System stability 2. Fair usage across users 3. Protection against abuse & DDoS attacks The Token Bucket algorithm allows controlled bursts, making it ideal for real-world systems Related Topics (Coming Next) 1. Leaky Bucket Algorithm 2.Fixed Window vs Sliding Window Rate Limiting 3.Implementing Rate Limiting in .NET Core 4.Distributed Rate Limiting with Redis 👍 Like, Share & Subscribe If you found this helpful, don’t forget to: 👍 Like the video 💬 Comment your questions 🔔 Subscribe for more deep dives into backend & system design 00:00 Introduction 01:25 What is Token Bucket Algorithm 05:32 Implementation 18:00 Testing Token Bucket Algorithm 20:15 Handling Queue Limit 22:45 Auto Replenishment of Tokens 26:00 Drawback of Token Bucket Algorithm 28:30 Rate Limit by User ID 33:00 Conclusion Watch introduction to Rate Limiting here 1.https://youtu.be/7urzuCCEW_w?si=9gMnWiIqyJ_ol7Zr #middleware #systemdesign #ratelimiting