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Node.jsframework~20 mins

Load balancing between workers in Node.js - Practice Problems & Coding Challenges

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Challenge - 5 Problems
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Load Balancing Mastery
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component_behavior
intermediate
2:00remaining
How does Node.js cluster module distribute incoming connections by default?
Consider a Node.js server using the cluster module with multiple worker processes. How are incoming connections distributed among workers by default?
AThe master process distributes connections in a round-robin fashion to workers.
BEach worker listens on the same port and the OS distributes connections in a round-robin fashion.
CThe master process sends all connections to the first worker until it is busy, then moves to the next.
DWorkers compete to accept connections and the fastest worker gets the connection.
Attempts:
2 left
💡 Hint
Think about how the cluster module balances load to avoid overloading a single worker.
📝 Syntax
intermediate
1:30remaining
Identify the correct way to create a worker in Node.js cluster
Which code snippet correctly creates a worker process using Node.js cluster module?
Node.js
const cluster = require('cluster');
if (cluster.isMaster) {
  // create worker
}
Acluster.newWorker();
Bcluster.createWorker();
Ccluster.fork();
Dcluster.spawn();
Attempts:
2 left
💡 Hint
Check the official cluster module API for the method to create a worker.
🔧 Debug
advanced
2:30remaining
Why does this cluster setup cause uneven load distribution?
Given the code below, why might the load not be balanced evenly across workers? const cluster = require('cluster'); const http = require('http'); if (cluster.isMaster) { for (let i = 0; i < 4; i++) { cluster.fork(); } } else { http.createServer((req, res) => { // simulate heavy work const start = Date.now(); while (Date.now() - start < 100) {} res.end('done'); }).listen(8000); }
AWorkers handle requests independently, but the OS assigns connections randomly, causing uneven load.
BThe blocking while loop in workers causes some workers to be busy longer, leading to uneven load.
CThe master process does not distribute connections; workers compete causing uneven load.
DThe cluster.fork() method is called incorrectly, so only one worker handles all requests.
Attempts:
2 left
💡 Hint
Consider how blocking code affects worker availability and load distribution.
state_output
advanced
1:30remaining
What is the output of this cluster worker count code?
What will be printed when running this code? const cluster = require('cluster'); if (cluster.isMaster) { cluster.fork(); cluster.fork(); console.log(Object.keys(cluster.workers).length); } else { console.log('worker running'); }
Aworker running
B0
Cundefined
D2
Attempts:
2 left
💡 Hint
Remember that cluster.workers is an object with worker IDs as keys.
🧠 Conceptual
expert
3:00remaining
Why might you choose a custom load balancing strategy over Node.js default cluster behavior?
Which reason best explains why a developer might implement a custom load balancing strategy instead of relying on Node.js cluster's default round-robin distribution?
ATo optimize resource usage by directing requests based on worker CPU load or memory usage.
BBecause the default cluster module does not support multiple workers.
CTo avoid using the cluster module entirely and handle all requests in a single process.
DBecause the default cluster module only works on Windows systems.
Attempts:
2 left
💡 Hint
Think about real-world scenarios where some workers might be busier or slower than others.

Practice

(1/5)
1. What is the main purpose of using the cluster module in Node.js for load balancing?
easy
A. To spread incoming requests across multiple CPU cores using worker processes
B. To create a single-threaded server that handles all requests
C. To manage database connections efficiently
D. To optimize memory usage by compressing data

Solution

  1. Step 1: Understand the role of the cluster module

    The cluster module allows Node.js to create multiple worker processes that share the same server port.
  2. Step 2: Identify the purpose of load balancing

    Load balancing means distributing incoming requests evenly across workers to use CPU cores efficiently.
  3. Final Answer:

    To spread incoming requests across multiple CPU cores using worker processes -> Option A
  4. Quick Check:

    Load balancing = spreading requests across workers [OK]
Hint: Cluster module creates workers to share server load [OK]
Common Mistakes:
  • Thinking cluster creates a single-threaded server
  • Confusing load balancing with database management
  • Assuming cluster compresses data for memory optimization
2. Which of the following is the correct way to check if the current process is the master in a Node.js cluster?
easy
A. if (cluster.isWorker) { /* master code */ }
B. if (cluster.master) { /* master code */ }
C. if (cluster.isMaster) { /* master code */ }
D. if (cluster.worker) { /* master code */ }

Solution

  1. Step 1: Recall the cluster API properties

    Node.js cluster module provides isMaster and isWorker boolean properties to identify process roles.
  2. Step 2: Identify the correct property for master check

    cluster.isMaster is true if the process is the master, so the condition should use this.
  3. Final Answer:

    if (cluster.isMaster) { /* master code */ } -> Option C
  4. Quick Check:

    Master check uses cluster.isMaster [OK]
Hint: Use cluster.isMaster to detect master process [OK]
Common Mistakes:
  • Using cluster.isWorker to check for master
  • Using non-existent properties like cluster.master
  • Confusing cluster.worker with cluster.isWorker
3. Consider this Node.js cluster code snippet:
const cluster = require('cluster');
const http = require('http');

if (cluster.isMaster) {
  cluster.fork();
  cluster.fork();
} else {
  http.createServer((req, res) => {
    res.end(`Worker ${process.pid} handled request`);
  }).listen(8000);
}
What will happen when you send multiple requests to port 8000?
medium
A. Requests will be handled by both worker processes, distributing load
B. Only the first worker will handle all requests, the second is idle
C. The master process will handle requests directly
D. The server will crash because multiple workers listen on the same port

Solution

  1. Step 1: Understand cluster.fork() behavior

    Calling cluster.fork() creates worker processes that share the same server port.
  2. Step 2: Analyze request handling in workers

    Both workers listen on port 8000 and Node.js load balances requests between them automatically.
  3. Final Answer:

    Requests will be handled by both worker processes, distributing load -> Option A
  4. Quick Check:

    Multiple workers share port and balance requests [OK]
Hint: Multiple forks share port and balance requests [OK]
Common Mistakes:
  • Thinking only one worker handles all requests
  • Assuming master handles requests directly
  • Believing server crashes due to port sharing
4. Given this cluster code snippet, what is the main issue causing the worker to never restart after crashing?
const cluster = require('cluster');

if (cluster.isMaster) {
  cluster.fork();
  cluster.on('exit', (worker, code, signal) => {
    console.log(`Worker ${worker.process.pid} died`);
  });
} else {
  throw new Error('Crash');
}
medium
A. The exit event listener is attached to the wrong object
B. The worker code does not handle errors properly
C. The cluster module is not imported correctly
D. The master does not fork a new worker after exit event

Solution

  1. Step 1: Check the exit event handler

    The master listens for 'exit' but only logs the death, it does not fork a new worker.
  2. Step 2: Identify missing restart logic

    To restart workers after crash, the master must call cluster.fork() inside the exit event handler.
  3. Final Answer:

    The master does not fork a new worker after exit event -> Option D
  4. Quick Check:

    Restart requires forking new worker on exit [OK]
Hint: Fork new worker inside exit event to restart [OK]
Common Mistakes:
  • Assuming worker error handling restarts process
  • Thinking cluster import affects restart
  • Believing exit event is attached incorrectly
5. You want to implement a Node.js cluster that balances load across all CPU cores and automatically restarts workers if they crash. Which code snippet correctly achieves this?
hard
A. if (cluster.isMaster) { cluster.fork(); cluster.on('exit', () => { console.log('Worker died'); }); } else { require('http').createServer((req, res) => { res.end('Hello'); }).listen(3000); }
B. if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); }); } else { require('http').createServer((req, res) => { res.end(`Handled by worker ${process.pid}`); }).listen(3000); }
C. if (cluster.isWorker) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } } else { require('http').createServer((req, res) => { res.end('Worker running'); }).listen(3000); }
D. if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } } else { require('http').createServer((req, res) => { res.end('Worker running'); }).listen(3000); cluster.on('exit', () => { cluster.fork(); }); }

Solution

  1. Step 1: Fork workers equal to CPU cores in master

    if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); }); } else { require('http').createServer((req, res) => { res.end(`Handled by worker ${process.pid}`); }).listen(3000); } correctly uses os.cpus().length to fork that many workers in the master process.
  2. Step 2: Restart workers on exit event in master

    if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); }); } else { require('http').createServer((req, res) => { res.end(`Handled by worker ${process.pid}`); }).listen(3000); } listens to the 'exit' event on cluster and forks a new worker to replace the dead one.
  3. Step 3: Worker creates HTTP server listening on port 3000

    if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); }); } else { require('http').createServer((req, res) => { res.end(`Handled by worker ${process.pid}`); }).listen(3000); }'s else block creates the server in workers, which is correct for load balancing.
  4. Final Answer:

    Forks workers across all CPU cores and automatically restarts workers if they crash -> Option B
  5. Quick Check:

    Fork all CPUs + restart on exit = if (cluster.isMaster) { const cpuCount = require('os').cpus().length; for (let i = 0; i < cpuCount; i++) { cluster.fork(); } cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); }); } else { require('http').createServer((req, res) => { res.end(`Handled by worker ${process.pid}`); }).listen(3000); } [OK]
Hint: Fork all CPUs in master and restart on exit event [OK]
Common Mistakes:
  • Not forking all CPU cores
  • Not restarting workers after crash
  • Forking workers inside worker process
  • Attaching exit listener inside worker instead of master