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API endpoints exposed to the public internet are constantly scanned by malicious scrapers and botnets. Implementing sliding window rate limiters at the edge protects server resources from denial-of-service attempts.
Implementing Sliding Window Limits
Rather than using fixed hourly caps, we evaluate requests in moving windows to mitigate burst-rate attacks. Redis stores the timestamps of user requests dynamically.
Redis Rate Limiting Code
Below is a typical rate-limiter middleware algorithm written in JavaScript:
// Express Rate Limiting Middleware
const requests = await redis.lrange(userId, 0, -1);
if (requests.length >= 100) {
return res.status(429).send("Too Many Requests");
}
await redis.rpush(userId, Date.now());
Conclusion
Shielding API gateways at the network layer prevents backend crashes, ensuring your operations stay responsive to genuine business clients.