Designing Rate Limiting for APIs: Algorithms, Patterns, and Implementation

Pick the right rate limiting algorithm for your traffic shape, build it on shared atomic state, and ship it with the response headers, failure modes, and monitoring that keep both your API and your clients working.

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API DesignIntermediate

api-designrate-limitingbackendredisnginx

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Pick the algorithm based on your traffic shape, not by default

Critical

Avoid plain fixed window counters, they leak 2x at the boundary

Store counters in Redis, not in process memory

Critical

Make the read-check-write atomic with a Lua script

Critical

Key limits by API key or account, not by IP alone

Return 429 with Retry-After and RateLimit headers

Critical

Decide what happens when the limiter backend is down

Critical

Add a coarse limit at the edge with nginx limit_req

Charge expensive endpoints more than cheap ones

Define plan tiers with explicit burst headroom

Never rate limit health checks or orchestrator probes

Critical

Export limiter metrics and alert on throttle rate

Load test the limiter before clients do

Document the limits and ship retry guidance with jitter

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