Marouane Souda
Rate Limiting & Throttling: Why Your API Desperately Needs Them

Rate Limiting & Throttling: Why Your API Desperately Needs Them

Imagine this: You’ve spent hours building your shiny new API. You test it. It works. You deploy it. People start using it — awesome! But then suddenly… 🚨 boom! Your API slows down, crashes, or worse: you get slapped with a massive bill from your cloud provider.

Yep — one script, one bot, or even one poorly-written frontend can trigger thousands of requests... and you pay for all of them.

This is where two behind-the-scenes heroes step in: Rate Limiting and Throttling. They’re like the gatekeepers of your API — keeping things fast, fair, and affordable.

Let’s talk about what they are, how they’re different, why you really need both, and how you can add them without stress.

🧠 What Is Rate Limiting?

Rate limiting is your API's way of saying:

"You can only ask me X times every Y seconds."

It sets a hard rule for how many requests someone can make in a given window of time. Once they hit that limit — boom — no more requests until the timer resets.

Example:

“Each user can only make 100 requests per minute.”

If they try the 101st request? Your API responds with a friendly:

429 Too Many Requests – please try again later.

✅ Key idea: It’s a cap — when you hit it, you’re done.

⏳ What About Throttling?

Throttling, on the other hand, is more about managing the flow of traffic, even if users are technically under the rate limit.

Think of it like this:

“Whoa there! You’re sending a lot of requests really fast. Let’s slow things down so my servers don’t get overwhelmed.”

Rather than outright blocking the request, throttling might:

  • - Introduce a short delay
  • - Queue the request
  • - Or allow it, but slower

✅ Key idea: It’s about pacing — not blocking.

💥 Why You (Seriously) Need This

1. 🚫 To Stop Abuse

If your API is public or even semi-public, someone will try to spam it — bots scraping data, poorly coded apps hammering endpoints, or bad actors trying to overload it.

Rate limiting gives you control. Without it, you're asking for trouble.

2. ⚖️ To Keep Things Fair

Without limits, one greedy client could hog all your server resources while others get left hanging. This makes your app feel slow or unresponsive — and nobody sticks around for that.

3. 💻 To Protect Your Server

Each API request uses CPU, memory, or database access. Multiply that by thousands and your server could start crawling... or crash entirely. Rate limiting keeps things sustainable, especially under load.

4. 💸 To Avoid Surprise Cloud Bills

Here’s the part most developers don’t think about: cloud costs.

If you're using something like AWS Lambda, Firebase, Vercel Functions, or any usage-based cloud service — you’re paying for every request.

Without rate limiting, a buggy app or attack could trigger millions of requests in a day. Your API doesn’t just slow down — you could wake up to a $500+ bill.

Real example: A dev once left a test script running in production that looped an API call. Overnight it generated 1.2 million requests. Guess what? The cloud bill came with it.

Rate limiting acts like a cost firewall. It prevents surprise bills by blocking traffic before it becomes expensive.

🧰 How to Set It Up (In Node.js)

If you’re building with Express, you can set this up in just a couple of steps using express-rate-limit:

1. Install the package

npm install express-rate-limit

2. Create a simple limiter

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

const limiter = rateLimit({
  windowMs: 1 * 60 * 1000, // 1 minute
  max: 100, // Limit each IP to 100 requests per minute
  message: "Slow down! You're making too many requests. Try again in a bit.",
});

3. Plug it into your app

const express = require('express');
const app = express();

app.use(limiter);

app.get('/', (req, res) => {
  res.send('Hello from your rate-limited API!');
});

app.listen(3000, () => console.log('Server running on port 3000'));

That’s it — you’ve now got basic protection in place.

🧪 Some Real-World Examples

  • GitHub API: 60 requests/hour for anonymous users; 5,000/hour when authenticated.
  • Stripe: Limits based on API category (e.g. payments vs. billing).
  • Twitter/X: Strict tiered limits depending on user level.
  • OpenAI API: Model-based request caps and usage tiers.

If the big guys do it, you probably should too.

💡 Helpful Tips

  • 🔁 Use a shared store like Redis if your API runs on multiple servers (to track limits across all instances).
  • 🛎 Return user-friendly messages when users hit their limit.
  • 📈 Use headers like X-RateLimit-Remaining to let users monitor their usage.
  • 🧑‍💻 Make limits configurable — free users get less, premium users get more.

🏁 Final Thoughts

Rate limiting and throttling aren’t just about keeping your API alive — they’re about:

  • Giving everyone a fair experience
  • Avoiding outages and abuse
  • And yes, saving your wallet from surprise cloud bills

If you’re building an API — even just for a hobby project — think of these features as the seatbelt your backend deserves. Easy to forget, but absolutely essential when things go wrong.