A New Node.js library

[u/swif_dev]

https://www.npmjs.com/package/cluster-rate-limiter

When you scale a Node.js backend using node:cluster, you run into a surprisingly annoying problem:

How do you rate-limit external APIs like Stripe or OpenAI while making sure all workers share the same rate limit?

The first solution that comes to mind is usually: "Just use Redis."

But does it really make sense to introduce additional infrastructure complexity, network overhead, and an entire external dependency just to coordinate a few API calls coming from the same server?

That's exactly why I built cluster-rate-limiter.

A Node.js library that gives you coordinated rate limiting across workers, powered entirely by Node.js's native IPC messaging, with no Redis and absolutely zero external dependencies.

Rather than diving into the internals here, here's what you get out of the box:

• Zero Setup: Install it and start using it. No additional infrastructure required.
• Developer-Friendly API: The run() method accepts your fetch call or any function directly, along with all its arguments. No complicated callback patterns.
• Two Types of Limits: Supports both Semaphore-based concurrency limits and Duration-based rate limits for enforcing strict time windows, such as those imposed by Stripe APIs.
• Typed Errors: If a request times out waiting for permission, the library throws a clear, specific error that you can easily translate into an HTTP 429 Too Many Requests response.

And when it comes to performance, the core data structure for tracking request timestamps uses a zero-allocation approach built around a Float64Array ring buffer.

This eliminates the need for repeated array reallocations and significantly reduces garbage collection pressure under heavy load.

If you're interested in the low-level details, I've explained the ring buffer implementation and how it reduces memory overhead in the README.

If you're running a clustered Node.js backend and want to avoid the overhead of introducing Redis just for rate limiting, check out the links below, explore the architecture, and let me know what you think!

[u/codesbyshivam]

Nice idea, for a single box this makes a lot more sense than spinning up Redis. A couple of things I'd want to know before using it. What happens if the primary process restarts, do the workers keep going without a limit or do they wait? And it might be worth saying clearly in the readme that the limit is per machine, so if someone runs two containers or two servers they'll still go over the API limit and need something shared. Also, does it do anything when the API sends back a 429 with a Retry-After header? Stripe and OpenAI both do that, and pausing everyone for that long would be really handy.