Rate Limiting in APIs: Token Bucket vs Leaky Bucket

🚀 Backend Learning | Rate Limiting in APIs (Token Bucket vs Leaky Bucket) While working on backend systems, I recently explored how to control incoming traffic using rate limiting. 🔹 The Problem: • Too many requests overwhelming the system • Risk of API abuse and DDoS-like situations • Need to ensure fair usage 🔹 What I Learned: • Rate Limiting controls how many requests a user can make 🔹 Common Algorithms: • Token Bucket: → Allows bursts of traffic → Tokens refill over time • Leaky Bucket: → Processes requests at a fixed rate → Smooth and consistent flow 🔹 Key Insights: • Token Bucket → Flexible, allows bursts • Leaky Bucket → Strict, smooth traffic control • Choice depends on system requirements 🔹 Outcome: • Protected APIs from overload • Better traffic control • Improved system stability Controlling traffic is just as important as handling it. 🚀 #Java #SpringBoot #SystemDesign #BackendDevelopment #APIDesign #RateLimiting #LearningInPublic

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