Kafka Consumer Explained: Poll Loop, Consumer Groups, Offsets, Rebalancing (Full Tutorial)
Kafka consumers can feel confusing until you get the mental model: partitions, consumer groups, polling, heartbeats, rebalancing, and offset commits all fit together. In this tutorial, we break down how Kafka consumers fetch records, how work is distributed across a consumer group, and how to configure timeouts and commits so your consumers stay stable in production.
You’ll learn:
How the consumer poll loop works and why Kafka uses a pull model.
How consumer groups split partitions (and why “one partition → one consumer in a group”)
Heartbeats vs session timeout vs max.poll.interval.ms (failure detection vs progress)
Offset commits: auto vs manual, and commitSync vs commitAsync tradeoffs
If you’re preparing for interviews or building event-driven systems, this video will help you understand the consumer side of Kafka with practical configs and production caveats.
Tags
apache kafka, kafka consumer, kafka consumer group, kafka offsets, kafka commit, commitSync, commitAsync, kafka poll loop, max.poll.interval.ms, session.timeout.ms, heartbeat.interval.ms, kafka rebalance, kafka partitions, kafka tutorial, kafka java, spring kafka, event driven architecture, distributed systems, system design
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