API Rate Limiting Implementation Guide

Complete Guide to Implementing Effective Rate Limiting

Rate limiting is essential for protecting APIs from abuse, ensuring fair usage, and maintaining service availability. This comprehensive guide covers rate limiting algorithms, implementation patterns, distributed rate limiting, and best practices for building robust rate limiting systems.

More accurate than fixed window

Prevents bursts at window boundaries

class SlidingWindowLog {

live demo · related simulation● LIVE

const ttl = await client.ttl(key);

remaining: Math.max(0, limit - current),

reset: Date.now() + (ttl * 1000)

Frequently asked questions

What is the purpose of creating a Redis pipeline in this context?

const pipeline = this.redis.pipeline();

How does removing old entries contribute to effective rate limiting?

// Remove old entries

What is the role of `pipeline.zremrangebyscore` in managing request rates?

pipeline.zremrangebyscore(key, 0, now - window);

How can we track the number of current requests being processed?

// Count current requests

▶ Try it live

Everything above runs in your browser — open Earthquake Wave Propagation Simulation and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Earthquake Wave Propagation Simulation simulation