Node.js introduced the worker-threads module, which allows you to create threads and execute multiple JavaScript tasks in parallel.
Once a thread finishes a task, it sends a message to the main thread that contains the result of the operation so that it can be used with other parts of the code.
The advantage of using worker threads is that CPU-bound tasks don’t block the main thread and you can divide and distribute a task to multiple workers to optimize it.
We need to offload a CPU‑intensive hash calculation in a small Node script. How would you use the worker_threads API to keep the main event loop responsive?
If you spawn a child process to run a Python script from Node, what steps do you take to capture its output and handle errors?
You added a Worker to process image thumbnails, but the request latency hasn't improved. What could be causing the main thread to still block?
During a load test, a burst of requests crashes the Node service when workers are created on demand. How would you redesign the worker usage to avoid this failure?
Design a scalable component that processes video transcoding jobs using a pool of worker_threads. Explain how you would manage job queueing, back‑pressure, and graceful shutdown.
Your service runs on a Kubernetes cluster and must handle spikes of CPU‑bound work. Compare using a pool of worker_threads versus launching separate containers for each job, and justify your choice.
Our legacy monolith uses synchronous file I/O and blocks the event loop. Outline a migration plan to introduce multi‑process or worker‑thread based concurrency across multiple teams while preserving API contracts.
When introducing a system‑wide worker pool for various services, what cross‑team considerations (monitoring, logging, versioning, resource quotas) do you address to keep the architecture maintainable?