Rate limiting prevents abuse, ensures fair resource usage, and protects against attacks.
Common strategies
- Fixed window: X requests per Y time period (simple but has burst issues).
- Sliding window: Rolling time window (more accurate).
- Token bucket: Accumulate tokens, spend on requests (allows bursts).
- Leaky bucket: Fixed rate processing (smooths traffic).
Where applied
- APIs: Prevent excessive calls (e.g., 1000/hour).
- Login forms: Prevent brute force (e.g., 5/minute).
- Public endpoints: Protect against DDoS.
- Email sending: Prevent spam (e.g., 100/day).
Implementation
- Store counters in Redis/Memcached.
- Return 429 (Too Many Requests) status.
- Include Retry-After header.
- Provide rate limit headers (X-RateLimit-*).
User experience
- Communicate limits clearly in documentation.
- Provide feedback when limits are approached.
- Offer higher tiers for legitimate high-volume users.
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