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APIRate LimitingSecurityPerformance

API Rate Limiting Implementation Strategies

Protect your API from abuse. From token bucket to sliding window to distributed rate limiting techniques.

B
Bootspring Team
Engineering
January 12, 2024
5 min read

Rate limiting protects your API from abuse and ensures fair usage. Here are proven algorithms and implementation patterns for production systems.

Why Rate Limit?#

Protection against: - DDoS attacks - Brute force attempts - API abuse - Resource exhaustion - Unfair usage Business benefits: - Predictable costs - SLA enforcement - Monetization tiers - Quality of service

Token Bucket Algorithm#

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Sliding Window Algorithm#

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Redis-Based Distributed Rate Limiting#

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Express Middleware#

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Response Headers#

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Tiered Rate Limiting#

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Best Practices#

DO: ✓ Use distributed storage for multi-instance ✓ Return informative headers ✓ Implement graceful degradation ✓ Different limits for different endpoints ✓ Consider user tiers ✓ Log rate limit events DON'T: ✗ Rate limit health checks ✗ Use only IP-based limiting ✗ Set limits too low for normal usage ✗ Forget to handle edge cases ✗ Ignore legitimate high-volume users

Conclusion#

Rate limiting is essential API protection. Choose the right algorithm for your use case—token bucket for bursts, sliding window for smooth limits—and use distributed storage for scaled systems.

Always communicate limits clearly through headers and error messages.

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