Core
Streaming and Backpressure
Streaming processes data one chunk at a time so memory stays flat no matter how big the input is. The moment a producer outruns its consumer, you need backpressure: a bounded buffer that makes the producer wait instead of piling unbounded work into memory. In Python this is generators and chunked reads for the streaming half, and a bounded queue (or a blocking put) for the backpressure half. Get it wrong and a 50 GB file or a fast upstream OOMs the box.
a free account unlocks the core curriculum tier · no card
Related course lessons
Related concepts
Practise this in questions
Coding & DSADesign a class that returns the moving average of the last N values in a stream →easy · FreeRAG & Agent System DesignYour agent workflow takes 30 seconds. Design the streaming UX, including what happens when it fails mid-stream. →medium · Free with sign-inMLOps & ML EngineeringDesign a feature store for a real-time fraud detection model. →hard · Free with sign-inLLM & GenAI FundamentalsA customer says your LLM app is too slow. Give me five levers to reduce latency, and their tradeoffs. →medium · Free with sign-inCoding & DSASessionize a support-event stream: a gap over 30 minutes starts a new session; dedupe events →medium · Free with sign-inSQL & Data EngineeringA customer says they need 'real-time dashboards.' How do you respond, batch or streaming? →medium · Premium
