Distributed Rate Limiter as a Service

Why this project

Compact but deep — algorithms, Redis atomicity, and API design. Great system design interview story.

Tech stack

Skills demonstrated

• Rate limiting algorithms
• Redis atomic operations
• High-throughput API design
• Multi-tenant quotas

Interview talking points

• Token bucket vs sliding window
• Redis Lua for atomicity
• Fail-open when Redis is down
• Scaling to millions of keys

Problem statement

Standalone rate limiting microservice using token bucket or sliding window in Redis. REST/gRPC API for other services to check quotas. Per-API-key and per-IP limits with configurable tiers.