Enforce distributed rate limits across serverless functions

@upstash/ratelimit implements distributed rate limiting on top of Upstash Redis. Because state lives in Redis, every instance of a serverless function or edge worker shares the same counters, enabling consistent rate limiting across distributed environments where in-memory limiters cannot provide shared state.

Use this skill when you need to enforce rate limits across multiple serverless function instances or edge workers that must share the same counters. It is ideal for distributed architectures where a single Redis-backed state ensures all instances respect the same limits for each identifier.

Do not use this when you can rely on a single-instance in-memory rate limiter, as the Redis dependency adds latency and infrastructure requirements that may be unnecessary for non-distributed scenarios.

The library supports per-identifier keys to track rate limits and ships three algorithms: fixed window, sliding window, or token bucket. It includes optional in-memory blocking of already-limited identifiers and optional analytics.

Counters are maintained in Upstash Redis and shared across all serverless or edge instances.

Upstash Redis serves as the backing store for distributed state, ensuring every serverless function instance or edge worker shares the same rate limit counters.

This library suits scenarios running multiple function instances that must enforce unified rate limits per identifier, where in-memory solutions fail because each instance maintains separate, uncoordinated state.