Rate Limiting Implementation Patterns

Calendar February 22, 2026
Microservices
Intermediate, Advanced
Rate-Limiter-Implementation, Distributed-Rate-Limiting, Api-Protection, Traffic-Management
Rate-Limiting, Token-Bucket, Sliding-Window, Redis, Api-Gateway, Throttling, Backpressure, Rate-Limit-Headers, Distributed-Systems
Redis, Kong, Nginx, Envoy, Express, Go, Python

Rate Limiting Implementation Patterns#

Rate limiting controls how many requests a client can make within a time period. It protects services from overload, ensures fair usage across clients, prevents abuse, and provides a mechanism for graceful degradation under load. Every production API needs rate limiting at some layer.

Algorithm Comparison#

Fixed Window#

The simplest algorithm. Divide time into fixed windows (e.g., 1-minute intervals) and count requests per window. When the count exceeds the limit, reject requests until the next window starts.