In this digital world, where Apps have millions of users across the world, having a responsive and sturdy backend is most important. One key tactic to make a sturdy and responsive backend is API rate limiting. It’s a method that limits how many requests a client makes to your server in a given window of time. Without it, your APIs are open to abuse, resulting in slowed performance or even total service crashes.

Why Implement Rate Limiting?

1. Preventing Abuse and Ensuring Fair Usage

Unrestricted APIs are vulnerable to malicious use, like brute force attacks or abusive scraping, that can bring down your system. Rate limiting serves as a bouncer, preventing a single user from using up all the resources and hence maintaining fair access for everyone.

2. Enhancing System Performance

By limiting the number of incoming requests, rate limiting ensures maximum server performance, resulting in quicker response times and a more seamless user experience.

3. Mitigating DDoS Attacks

Distributed Denial of Service (DDoS) attacks flood servers with huge requests, aiming to disrupt services. Applying rate limits can act as a front-line defence, redirecting unwanted high levels of requests from individual sources.

4. Cost Management

For cloud-hosted services with pay-as-you-use pricing, unchecked API calls may result in unexpected charges. Rate limiting helps in cost management by avoiding wasteful resource consumption.

Rate Limiting Algorithms

We have to understand the mechanism of rate limiting, to implement it efficiently. Some of the common algorithms are:

1. Fixed Window

In this approach, a particular number of requests can be made in a particular time period. For example, one can be allowed to do 100 requests in a minute. Once it is exceeded, requests will be rejected until the next phase.

2. Sliding Window (Rolling Window)

The sliding window keeps calculating available requests by the time of every incoming request, giving a smoother distribution.

3. Leaky Bucket

As per its name, in this process the incoming requests are put into a bucket, and they are serviced (leaked) at a steady pace. When the bucket fills up from an unexpected flood of requests, the overflow is either dropped or held up.

4. Token Bucket

Here tokens are inserted into a bucket at a constant rate. A token is consumed per request. Till the tokens are available, requests will be served; otherwise, it will be rejected or deferred until new tokens are created.

Implementing Rate Limiting in NodeJS

NodeJS can integrate rate limiting using middleware like express-rate-limit.

1. Install the Middleware

npm install express-rate-limit

2. Configure the Middleware

const rateLimit = require('express-rate-limit');

const limiter = rateLimit({
windowMs: 1 * 60 * 1000, // 1 minute
max: 100, // Limit each IP to 100 requests per windowMs
message: 'Too many requests from this IP, please try again later.',
headers: true,
});

module.exports = limiter;

3. Apply Middleware to Your NodeJS App

const express = require('express');

const rateLimit = require('express-rate-limit');

const app = express();

// Apply rate limiting to all requests
app.use(limiter);

// Define your services and other middleware
// ...

// Start the server
const port = 3030;
app.listen(port, () => {
console.log(`NodeJS app started on http://localhost:${port}`);
});

NGINX for Rate Limiting

Those who are using NGINX as a reverse proxy, rate limiting can be configured directly within its settings:

1. Define a Rate Limit Zone

In your NGINX configuration file:

http {
limit_req_zone $binary_remote_addr zone=mylimit:10m rate

This sets a limit of 5 requests per second, with states stored in a 10MB zone named 'mylimit'.

2. Apply the Limit to a Location

Within the server block:

server {
  location /api/ {
  limit_req zone=mylimit burst=10 nodelay;
  proxy_pass http

Here, up to 10 requests is allowed without delay.

Conclusion

Rate limiting for APIs is not only a technical requirement but also a strategy for long term and stable services. As you implement proper rate limiting methods, you protect your backend from potential attacks and offer a better experience. When looking at your existing backend systems, ask yourself: Are my APIs resilient enough to handle any probable abuses?

FAQs

Q. What is rate limiting and why is it necessary?
A. Rate limiting is the process of limiting the number of requests a user makes to a server within a given time frame. It's important for preventing abuse and shielding servers from overload or DDoS attack.

Q. How to enable rate limiting in an API?
A. It can be done at many levels, using middleware (such as express-rate-limit for Node.js), API gateways (such as Kong or AWS API Gateway), or even network-level with NGINX. The majority of the configurations are to count requests and apply logic to block or hold up traffic upon exceeding limits.

Q. What is the distinction between rate limiting and throttling?
A. Rate limiting is limiting the request quantity over time (e.g., 100 requests per minute), while throttling reduces request speed instead of blocking them flat out. Throttling is more user friendly, while rate limiting is stricter and better for security.