Token Bucket

What is Rate Limiting?

Rate limiting is the practice of capping how many requests a client can make to a service within a given time window, protecting the system from overload and a…

How to Design a Rate Limiter?

A rate limiter is designed by choosing an algorithm (token bucket, leaky bucket, fixed window, or sliding window log) that tracks request counts per client key…

How to Design an API Rate Limiter

An API rate limiter design centers on a shared, low-latency counter store (typically Redis) that tracks per-client request counts using a sliding-window or tok…

What Are the Main Rate Limiting Algorithms?

The main rate limiting algorithms are token bucket, leaky bucket, fixed window counter, sliding window log, and sliding window counter, each trading off burst…

Token Bucket vs Leaky Bucket: What Is the Difference?

Token bucket allows bursts of traffic up to a stored capacity of accumulated tokens while enforcing a long-run average rate, whereas leaky bucket forces reques…

How Do You Implement Rate Limiting Across Multiple Servers?

Distributed rate limiting means enforcing a shared request budget for a client across many stateless application servers, which requires moving the counter or…

What Are Common API Rate Limiting Strategies?

API rate limiting caps how many requests a client can make in a given time window, most commonly implemented with token bucket, fixed window, or sliding window…

Rate Limiting in Distributed Systems

Rate limiting caps how many requests a client, service, or API key can make within a time window, protecting backend systems from overload, abuse, and cascadin…