Node.js Cluster Module
Here’s a detailed guide on the Node.js Cluster Module, including its purpose, usage, examples, and best practices.
🏭 Node.js Cluster Module
The cluster module allows you to create child processes (workers) that share the same server port, enabling multi-core scaling of your Node.js applications.
Node.js runs on a single thread, so CPU-intensive tasks can block the event loop. The Cluster Module solves this by distributing requests across multiple processes.
1️⃣ Importing the Cluster Module
2️⃣ Basic Usage
✅ Features:
-
Automatically use all CPU cores
-
Workers share a single port (e.g., HTTP 3000)
-
Master process manages worker lifecycle
3️⃣ Cluster Events
| Event | Description |
|---|---|
online |
Worker is forked and ready |
exit |
Worker exits (used to restart workers) |
listening |
Worker is listening on a server port |
disconnect |
Worker disconnects from master |
message |
Master-worker communication |
Example:
4️⃣ Master-Worker Communication
You can send messages between master and worker:
5️⃣ Advantages of Cluster Module
-
Multi-core utilization → Node.js single-threaded by default
-
Automatic worker restart → Fault-tolerant
-
Shared port → No need for load balancer
-
Easy IPC → Master communicates with workers
6️⃣ Use Cases
-
CPU-intensive tasks like image processing or encryption
-
High-concurrency HTTP servers
-
Background jobs and parallel processing
7️⃣ Best Practices
-
Fork based on CPU cores (
os.cpus().length) -
Monitor worker crashes and auto-restart (
exitevent) -
Use IPC for worker communication if needed
-
Avoid memory leaks in workers; restart periodically if necessary
-
Combine with PM2 for easier process management in production
-
Do not share state directly between workers; use Redis or database for shared state
8️⃣ Combining Cluster with Express.js
9️⃣ Summary
-
The Cluster Module allows Node.js to scale across CPU cores
-
Master process forks workers that share the same port
-
Supports automatic restarts and IPC communication
-
Ideal for high-load HTTP servers or CPU-intensive tasks
-
Combine with PM2 for production deployment
