Building a Production-Ready Rate Limiter: From Token Bucket to Distributed Redis Implementation

Your API is getting hammered. Response times are spiking, your database connection pool is exhausted, and legitimate users are getting timeouts because a single client decided to run a poorly-written batch script. You need rate limiting, but the tutorials you find either stop at toy implementations or hand-wave the distributed parts. This guide covers the full journey: algorithm selection, Redis-backed implementation with proper atomicity, distributed coordination patterns, and the operational concerns that separate demo code from production systems. By the end, you'll have rate limiting that actually works when your pager goes off at 3 AM. Why Most Rate Limiting Tutorials Fail You The standard rate limiting tutorial shows you a dictionary with timestamps and calls it a day. Then you deploy it, scale to three instances, and watch in horror as clients get 3x their intended quota. The tutorial didn't mention that part. The gap between textbook and production is wide. Academic description