# Rate Limiting & Algorithms

Quick Reference: Load Balancing | Proxy

# Quick Reference

# Clear Definition

Rate Limiting controls the rate of requests from clients to prevent abuse, ensure fair usage, and protect system resources.

💡 Key Insight: Choose algorithm based on whether you need burst handling, accuracy, or simplicity.

# Core Concepts

# Token Bucket

• Tokens added at fixed rate
• Request consumes token
• Allows bursts (if tokens available)
• Example: API rate limiting

# Sliding Window

• Track requests in time window
• More accurate than fixed window
• Memory intensive
• Example: Distributed rate limiting

# Use Cases

1. API Protection: Prevent abuse
2. DDoS Mitigation: Limit attack traffic
3. Fair Usage: Ensure equal access
4. Cost Control: Limit expensive operations

# Best Practices

1. Choose Right Algorithm: Token bucket for bursts, sliding window for accuracy
2. Distributed Systems: Use Redis for shared state
3. Headers: Return rate limit headers (X-RateLimit-*)
4. Graceful Handling: Return 429 Too Many Requests

# Quick Reference Summary

Rate Limiting: Control request rate to prevent abuse.

Algorithms: Token bucket (bursts), Sliding window (accurate), Fixed window (simple).

Key: Implement at API gateway or reverse proxy level.

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