When to use workers vs cluster in Node.js - Hands-On Comparison

When to Use Workers vs Cluster in Node.js

📖 Scenario: You are building a Node.js server that needs to handle multiple tasks efficiently. Some tasks are CPU-heavy, and others involve handling many client requests. You want to learn when to use worker_threads and when to use the cluster module to improve your server's performance.

🎯 Goal: Build a simple Node.js setup that demonstrates creating a worker thread for CPU-intensive work and a cluster to handle multiple server processes. This will help you understand when to use each approach.

📋 What You'll Learn

Create a worker thread to perform a CPU-heavy calculation

Create a cluster to spawn multiple server processes

Use exact variable and function names as instructed

Follow Node.js modern syntax with ES modules

💡 Why This Matters

🌍 Real World

Node.js servers often need to handle CPU-heavy tasks and many client requests simultaneously. Using workers and clusters helps improve performance and reliability.

💼 Career

Understanding workers and clusters is essential for backend developers working with Node.js to build scalable and efficient server applications.

1

Create a CPU-intensive task function

Create a function called heavyComputation that takes a number n and returns the sum of all numbers from 1 to n. Use a simple for loop inside the function.

Node.js

# Your code here
// Create function heavyComputation(n) that sums 1 to n

Need a hint?

Use a for loop from 1 to n and add each number to a sum variable.

2

Set up a worker thread to run the CPU task

Import Worker from worker_threads. Create a new Worker instance called worker that runs a file named worker.js. This file will use the heavyComputation function.

Node.js

function heavyComputation(n) {
    let sum = 0;
    for (let i = 1; i <= n; i++) {
        sum += i;
    }
    return sum;
}

// Import Worker and create worker instance
// Your code here

Need a hint?

Use import { Worker } from 'worker_threads' and create worker with new Worker(new URL('./worker.js', import.meta.url)).

3

Set up a cluster to handle multiple server processes

Import cluster and os modules. Create a variable numCPUs that stores the number of CPU cores using os.cpus().length. Use cluster.isPrimary to check if the current process is the primary. If yes, use a for loop with variable i from 0 to numCPUs to fork workers using cluster.fork().

Node.js

import { Worker } from 'worker_threads';
import cluster from 'cluster';
import os from 'os';

function heavyComputation(n) {
    let sum = 0;
    for (let i = 1; i <= n; i++) {
        sum += i;
    }
    return sum;
}

const worker = new Worker(new URL('./worker.js', import.meta.url));

// Create numCPUs and fork workers if primary
// Your code here

Need a hint?

Use os.cpus().length to get CPU count and cluster.fork() inside a for loop to create workers.

4

Complete the cluster setup with a simple server

Inside the else block of if (cluster.isPrimary), create a simple HTTP server using import http from 'http'. The server should listen on port 3000 and respond with 'Hello from worker ' + process.pid for every request.

Node.js

import { Worker } from 'worker_threads';
import cluster from 'cluster';
import os from 'os';

function heavyComputation(n) {
    let sum = 0;
    for (let i = 1; i <= n; i++) {
        sum += i;
    }
    return sum;
}

const worker = new Worker(new URL('./worker.js', import.meta.url));

const numCPUs = os.cpus().length;

if (cluster.isPrimary) {
    for (let i = 0; i < numCPUs; i++) {
        cluster.fork();
    }
} else {
    // Create HTTP server that responds with worker pid
    // Your code here
}

Need a hint?

Use http.createServer inside the else block and listen on port 3000.