Child processes

Problem

What becomes confusing, fragile, or impossible without understanding child processes? This lesson answers that through explanation, a worked example, two runnable exercises, and a reference solution. No teacher-supplied worksheet is required.

Node applied JavaScript’s event-driven model to servers and command-line programs, pairing a single process with nonblocking I/O.

Concept explanation

Child processes belongs to “One process under load”. Capacity ends where CPU, memory, descriptors, event-loop delay, or dependencies saturate. This lesson turns child processes into a working part of weekly fixture.

For child processes, trace concrete input, state transition, output, and failure through a server-side runtime boundary involving process lifecycle, filesystem or network I/O, streams, and capacity.

One process owns an event loop, module graph, heap, handles, streams, signals, and explicit boundaries to the OS and network. Apply that model to supplied normal, boundary, and failure cases; each case below names its input and expected evidence.

Example bank

Compare normal, boundary, failure, and cross-layer cases. Predict each observation before revealing the explanation.

Worked example

Start from supplied server.mjs. Focus: Build child processes around this exact fixture: Load-test one-process server and record latency percentiles, throughput, handles, CPU, memory.

1. Run: node server.mjs > server.log 2>&1 & server_pid=$!; trap 'kill $server_pid' EXIT; sleep 1; curl -i http://127.0.0.1:3000/
2. Save baseline evidence. Use Node inspector, active handles, process signals, curl, CPU profiles, heap snapshots, and OS process tools.
3. Boundary case: Add child processes support for weekly boundary case: Increase concurrency until first measured knee.
4. Failure case: Make child processes surface—not hide—this failure: Send termination under load and verify graceful drain timeout.

RESULT
child processes handles baseline and boundary while preserving this observable result: Report names first bottleneck from evidence and distinguishes worker/child-process trade-offs. Starter-level baseline: Server prints its URL; curl receives 200, JSON content type, correct byte length, and a body containing topic and GET method.

Starter material

Create server.mjs, paste this exact content, then run the command below.

import { createServer } from "node:http";

const server = createServer((request, response) => {
  const body = JSON.stringify({ topic: "child processes", method: request.method });
  response.writeHead(200, { "content-type": "application/json", "content-length": Buffer.byteLength(body) });
  response.end(body);
});

server.listen(3000, "127.0.0.1", () => console.log("http://127.0.0.1:3000"));

STOP / CLEANUPSupplied command traps shell exit and stops server. If running server alone, press Ctrl+C.

Independent exercise

Add one real case: child processes

1. Create second case from blank file: Add child processes support for weekly boundary case: Increase concurrency until first measured knee.
2. Then create controlled failure: Make child processes surface—not hide—this failure: Send termination under load and verify graceful drain timeout.
3. Use Node inspector · curl · SQLite CLI · process tools to prove behavior, then repair controlled failure.
4. Compare result against supplied acceptance checks and reference approach before marking complete.

Expected result

• child processes handles baseline and boundary while preserving this observable result: Report names first bottleneck from evidence and distinguishes worker/child-process trade-offs.
• Server prints its URL; curl receives 200, JSON content type, correct byte length, and a body containing topic and GET method.
• Controlled child processes failure produces captured evidence; repair restores stated invariant without hiding error.

Hints

Solution

Attempt both exercises before opening reference approach.