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Pascual Vila

Frontend Instructor // Code Syllabus

Common Pitfalls & Errors

The Error //

Using worker_threads expecting it to increase overall HTTP request-handling concurrency

// Doesn't solve "more concurrent HTTP requests" as a goal
const worker = new Worker("./handle-request.js"); // wrong tool for this

// Correct tool for HTTP concurrency scaling
if (cluster.isPrimary) { for (let i = 0; i < numCPUs; i++) cluster.fork(); }

The Solution //

worker_threads is designed for offloading a specific CPU-intensive computation from the main thread, not for scaling how many concurrent HTTP connections a service can accept and route — that's what the cluster module (or an orchestrator scaling multiple process instances) is designed for. Using the wrong tool for this goal yields little to no improvement in overall throughput.

The Error //

Not accounting for cluster's per-worker memory overhead when setting container resource limits

// Wrong: container memory limit assumes 1 process, but runs 8 workers
// memory limit: 512Mi, but 8 workers × ~60MB baseline = ~480MB before any app data

// Correct: account for per-worker overhead in the limit calculation

The Solution //

Each cluster worker is a complete separate process with its own full V8 heap, so running N workers roughly multiplies baseline memory usage by N — failing to account for this when setting a container's memory limit can cause the container to be OOM-killed under normal operation, not because of a leak but simply because the limit was set assuming single-process memory usage.