rate-limiting

Enforce two-tier API rate limits with Redis-backed sliding-window patterns.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/lgoodcode/instamolt-seeder --skill rate-limiting-lgoodcode
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rate-limiting
Source: https://github.com/lgoodcode/instamolt-seeder/tree/main/.claude/skills/rate-limiting
Command: npx skills add https://github.com/lgoodcode/instamolt-seeder --skill rate-limiting-lgoodcode

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rate limiting and traffic control for web services using Redis-backed patterns to prevent abuse and protect backend resources.

Core Features & Use Cases

  • Two-tier rate limiting: IP-based middleware and per-API-key route limits with fail-open behavior.
  • Sliding window algorithm and cache-aside patterns to balance performance and accuracy.
  • Clear observability and well-documented Redis key schemas for maintenance and auditing.

Quick Start

Integrate the Redis-backed rate limiter into your API startup and enable both global and per-endpoint throttling.

Frequently Asked Questions about rate-limiting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce API rate limits using Redis to prevent abuse?

API rate limiting with Redis is enforced through two-tier per-IP and per-API-key throttling using a sliding-window algorithm. This protects backend resources and prevents abuse on high-traffic web services.

What happens to API traffic if Redis goes down during rate limiting?

During Redis downtime, the rate limiting middleware applies fail-open behavior. This ensures API traffic remains uninterrupted by allowing requests to bypass throttling when the Redis cache is unavailable.

How does the sliding-window algorithm work for API throttling?

The sliding-window algorithm for API throttling balances performance and accuracy by tracking request timestamps within a moving time frame. Combined with cache-aside patterns, it provides precise rate limit enforcement for high-traffic web services.

Can I apply different rate limits for global IP traffic and specific API keys?

Yes, two-tier rate limiting supports both global IP-based middleware and per-API-key route limits. This allows you to apply distinct throttling policies to different API endpoints and client types simultaneously.

How do I integrate a Redis rate limiter into my API startup process?

To integrate Redis rate limiting, initialize the rate-limiter factory during your API startup to enable both global and per-endpoint throttling. This setup uses explicit Redis key schemas and observability hooks for maintenance and auditing.

Does Upstash Redis work for serverless API rate limiting and throttling?

Yes, Upstash Redis can be used for serverless API rate limiting and throttling. The rate limiter factory connects to Redis instances using explicit key schemas to enforce per-IP and per-API-key sliding-window limits.