Distributed Rate Limiting with Redis & GCRA in Golang
Prerequisite: Before reading this chapter, review Chapter 2: The 3 Caching Vulnerabilities. Chapter 3: Distributed Rate Limiting with Redis & GCRA Algorithm Answer-first: Distributed rate limiting in microservice architectures requires centralized state management in Redis to avoid load-balancer bypasses. Implementing the Generic Cell Rate Algorithm (GCRA) via atomic Lua scripts tracks Theoretical Arrival Times (TAT) using a single 64-bit integer per user key, guaranteeing sub-millisecond execution. Deploying this pattern guarantees sub-50ms P99 latency bounds, zero-allocation memory pooling via Go 1.24 string interning, and. ...