Streams in Node.js are objects that allow you to read or write data continuously in chunks rather than reading or writing the entire data at once.
A stream is an abstract interface for working with streaming data in Node.js.
The node:stream module provides an API for implementing the stream interface.
All streams are instances of EventEmitter.
They are used for efficiently processing large amounts of data, making I/O operations more manageable.
How would you read a large CSV file line by line in Node without loading the whole file into memory?
If you pipe a readable stream into a writable stream and the writable stream errors, what happens to the readable stream and how would you handle it?
We need to implement a file upload endpoint that streams the incoming data directly to S3. What steps would you take, and what pitfalls might you encounter with backpressure?
During a recent deployment, a Node service that processes log files using streams started crashing with 'ERR_STREAM_WRITE_AFTER_END'. What could cause this, and how would you debug it?
Design a real-time data processing pipeline in Node that ingests events from a TCP socket, transforms them, and writes to a message queue, ensuring high throughput and graceful handling of backpressure. What components would you use and why?
Our microservice architecture streams video chunks between services. How would you mitigate latency and memory usage when chaining multiple transform streams across network boundaries?
Our legacy monolith uses callback‑based file I/O. We want to migrate to a streaming architecture across several services to improve scalability. What migration strategy would you propose, and how would you handle compatibility and testing?
When building a platform that serves millions of concurrent users with streaming APIs, what architectural patterns and Node stream configurations would you adopt to ensure reliability and observability at scale?