API Rate Limiting
Protect APIs from abuse using rate limiting algorithms with per-user and per-endpoint strategies.
Algorithms
| Algorithm |
Pros |
Cons |
| Token Bucket |
Handles bursts, smooth |
Memory per user |
| Sliding Window |
Accurate |
Memory intensive |
| Fixed Window |
Simple |
Boundary spikes |
Token Bucket (Node.js)
class TokenBucket {
constructor(capacity, refillRate) {
this.capacity = capacity;
this.tokens = capacity;
this.refillRate = refillRate; // tokens per second
this.lastRefill = Date.now();
}
consume() {
this.refill();
if (this.tokens >= 1) {
this.tokens--;
return true;
}
return false;
}
refill() {
const now = Date.now();
const elapsed = (now - this.lastRefill) / 1000;
this.tokens = Math.min(this.capacity, this.tokens + elapsed * this.refillRate);
this.lastRefill = now;
}
}
Express Middleware
const rateLimit = require('express-rate-limit');
const limiter = rateLimit({
windowMs: 15 * 60 * 1000, // 15 minutes
max: 100,
standardHeaders: true,
message: { error: 'Too many requests, try again later' }
});
app.use('/api/', limiter);
Response Headers
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 45
X-RateLimit-Reset: 1705320000
Retry-After: 60
Tiered Limits
| Tier |
Requests/Hour |
| Free |
100 |
| Pro |
1,000 |
| Enterprise |
10,000 |
Best Practices
- Use Redis for distributed rate limiting
- Include proper headers in responses
- Return 429 status with Retry-After
- Implement tiered limits for different plans
- Monitor rate limit metrics
- Test under load