What is Rate Limiting?

Rate limiting caps how many requests a client can make in a time window. It applies per IP, per user, per API key, or per other identifiers so services stay available, costs stay predictable, and abusive bursts are throttled.

How does rate limiting work?

A gateway, load balancer, or application tracks counts for each key (for example “IP + route” or “user ID + endpoint”). When the count exceeds a policy (such as 100 requests per minute), the server rejects or delays further requests, often with HTTP 429 Too Many Requests and optional retry hints.

Common algorithms include token bucket (allows short bursts while averaging a steady rate), leaky bucket (smooths traffic), and sliding or fixed windows over time. The right choice depends on fairness, memory use, and whether you need strict ceilings or burst tolerance.

Rate limits are not only for security. They also protect APIs from accidental loops, flash crowds, and runaway scripts. They are one layer among others: authentication, WAF rules, and behavioral checks. A well-tuned limit stops a naive script that fires hundreds of logins per second while still allowing a human who mistypes a password a few times.

Why does this matter for click fraud and ad fraud?

Automated bots and scripts generate clicks, form posts, and scrapes at machine speed. Sensible limits on sensitive endpoints (logins, lead forms, checkout, tracking) slow credential stuffing and spam submissions. They do not stop sophisticated distributed fraud by themselves, because attackers spread load across many IPs, but they raise cost and improve signal quality for suspicious clicks analysis.

For advertisers, cleaner site and API traffic means fewer fake leads polluting CRM data. That ties to junk leads problems and to measuring real demand. Rate limiting complements dedicated click fraud and ad fraud controls rather than replacing them.