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backpressure

AI, ML & GenAI interview questions tagged backpressure, across every topic.

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Concepts behind "backpressure"

The curriculum that explains the ideas these questions test.

Core
⚙️ System Design for AI in ProductionSign in
Message Queues and Event StreamingBroker queues (RabbitMQ, SQS) hand each message to one worker, wait for an ack, and delete it: built for distributing jobs. Event logs (Kafka) append events to a durable, partitioned log that many consumer groups read independently at their own offsets, with replay for free. Ordering holds only within a partition, and 'exactly-once' in practice comes down to at-least-once delivery plus idempotent consumers. AI, ML, and GenAI engineer interviews probe it because ingestion pipelines, async inference jobs, and feedback events all hang off one of these two primitives, and picking the wrong one is expensive to undo.
Core
⚙️ System Design for AI in ProductionSign in
Token Streaming: SSE, Chunking, and CancellationServer-Sent Events is the default transport for one-way token streams, and the interesting problems start after you pick it: an output guardrail that buffers the whole response destroys the time-to-first-token you paid a GPU for, you cannot send an HTTP error status after the 200 has flushed, and a client disconnect must actually cancel the GPU work or you keep generating tokens nobody will read. AI, ML, and GenAI interviews probe it because 'we stream the tokens' is one sentence and shipping it correctly is a design round.
Core
💻 Coding & Engineering CraftSign in
Streaming and BackpressureWhen data is too large to hold in memory or keeps arriving without end, you handle it as a stream, one piece at a time, with bounded memory, rather than pulling it all in. Backpressure is the mechanism that keeps a fast producer from swamping a slow consumer, by signaling 'slow down' instead of buffering without limit until memory runs out. Applied-AI interviews test it because AI pipelines chew through huge datasets and token streams, and the naive load-everything approach OOMs while unbounded buffering crashes under load.