Grokking Rate Limiters for System Design Interviews

This blog demystifies what rate limiters are, explores their benefits for system design, and discusses where to place them in your architecture for maximum impact.

Ever had a website suddenly say, “Too many requests. Try again later”?

That wasn’t a bug—it was a bouncer doing its job.

In the world of backend systems, that bouncer is called a rate limiter.

Rate limiting is a strategy that controls the number of requests a user or service can make within a given time frame.

It quietly keeps the peace behind the scenes, making sure no one floods your servers or hogs all the bandwidth.

Whether you're building APIs or prepping for your next system design interview, understanding how rate limiters work (and where to place them) is non-negotiable.

Let’s break it down.

What is a Rate Limiter?

A rate limiter is like a strict bouncer for your application – it lets in requests at a controlled pace and turns away those that exceed the limit.

In technical terms, a rate limiter restricts the number of requests or actions allowed over a time window.

For example, an API might permit 100 requests per user per minute; any extra calls get blocked or delayed until the minute resets.

This ensures no single user (or malicious bot) can overwhelm the system.

In simple words, rate limiting controls the rate at which users or clients can access a resource, preventing excessive or abusive usage. It’s widely used in web services, APIs, and networks to keep systems stable and fair for everyone.

Under the hood, rate limiters can be implemented using algorithms like Token Bucket, Leaky Bucket, or Sliding Window counters, which efficiently track request rates and enforce limits.

The goal is always the same – to throttle excessive requests and ensure the system isn’t overwhelmed.

Benefits of Rate Limiting

Why bother adding a rate limiter to your system?

It turns out there are numerous benefits, especially in system design and scalability:

• Prevents Overload and Downtime: By capping the request rate, you avoid situations where a surge in traffic (legitimate or a Denial-of-Service attack) brings your servers down. Rate limiting acts as a safety valve, preserving system stability during unexpected spikes.

• Fair Resource Distribution: Rate limiters ensure no single user or IP monopolizes your service. Every user gets a fair share of resources, which improves the overall user experience. For instance, if one client tries to hog an API, the limiter will curb that behavior so others aren’t starved of service.

• Improved Performance: By filtering out excessive requests, the system can respond faster to normal traffic. Genuine users face fewer slowdowns because the server isn’t busy handling spam or bursty traffic. In fact, limiting request rates can reduce delays and keep your application responsive under load.

• Security Against Abuse: Malicious actors often attempt credential stuffing, brute-force logins, or web scraping by sending a flurry of requests. A strong rate limiting policy blocks such abuse by rejecting rapid-fire requests (e.g., “10 login attempts per minute” rule to stop password guessing). This adds an extra layer of security beyond authentication checks.

• Cost Control: If your system integrates with third-party APIs that charge per request, uncontrolled calls can rack up costs. Rate limiters help reduce costs by curbing excessive outgoing requests. Similarly, they prevent overuse of expensive resources (database, bandwidth), saving money on infrastructure and avoiding the need for sudden scaling.

In short, rate limiting keeps your service reliable, fair, and efficient. It’s a must-have in scalable architectures and a favorite tool in the arsenal of system designers.