API Rate Limiting Strategies
Demo Creator
@seed-creator · muallif
Why Rate Limit?
Rate limiting protects your service from abuse, accidental DDoS from misbehaving clients, and credential-stuffing attacks. It is one of the cheapest defenses with the highest ROI.
A rate limit that never triggers is a sign that your limits are too loose. One that triggers constantly is a sign they are too tight. Both are problems.
Token Bucket vs. Sliding Window
Token bucket allows bursts up to the bucket capacity. Sliding window spreads requests evenly. For user-facing APIs, token bucket is more forgiving; for scraper defenses, sliding window is tighter.
In-process rate limiting (in-memory token bucket) resets on restart and does not share state across pods. Use Redis for distributed rate limiting in multi-replica deployments.
Returning the Right Headers
Return X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset so clients can self-throttle. A 429 response without a Retry-After header leaves clients guessing when to retry.