Scenario 02.1.3 · Committing offsets

Kafka committed offsets: enable.auto.commit and restart

Consumer groups · Intermediate · about 3 min · Apache Kafka 4.3

The committed offset is the resume point. Auto-commit saves it periodically; manual commit lets the app choose when.

What you start with

The committed offset is where a group resumes after a restart or rebalance, distinct from its live read position. This scenario shows enable.auto.commit periodically saving the position, then a crash-and-restart resuming from the committed offset instead of re-reading.

Step by step

1. Consumer ready · auto-commit on t+0.000s Group g1 reads with enable.auto.commit=true. Watch the committed offset (the resume point), not just the live position. Open at this step: step 1, Consumer ready · auto-commit on
2. Read and committed up to 3 t+1.600s The consumer read O1-O3 (position 3) and auto-commit saved that as the committed offset (3). The committed offset - not the position - is what survives a restart. Open at this step: step 2, Read and committed up to 3
3. Consumer crashed t+2.400s c1 crashed and stopped polling. Its committed offset (3) is held by the group coordinator, independent of the live member. Open at this step: step 3, Consumer crashed
4. Restarted · resumes at the committed offset t+3.100s c1 restarted and resumed at the committed offset 3 - it does NOT re-read O1-O3. Manual commit uses the same mechanism but the app picks exactly when to save, trading re-processing after a crash against losing un-committed work. Open at this step: step 4, Restarted · resumes at the committed offset

The takeaway

The committed offset is a durable bookmark, not the read position - commit timing is the lever between at-least-once and at-most-once, deciding how much is reprocessed or skipped after a failure.

Configs in this scenario

• enable.auto.commit Whether the consumer commits its offsets in the background every auto.commit.interval.ms (default true); with it on, records processed between the last commit and a crash are read again.

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Further reading

Apache Kafka documentation

More in Consumer groups

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• Kafka auto.offset.reset: earliest vs latest vs none
• Replay a Kafka topic: consumed records stay in the log
• Kafka consumer group: how partitions split across members
• Kafka consumer group rebalance when a consumer joins
• Kafka partition assignors: range vs round-robin vs sticky
• Kafka eager vs cooperative rebalancing (cooperative-sticky)
• Kafka consumer crash and session.timeout.ms
• Kafka max.poll.interval.ms: evicting a stuck consumer
• Kafka static membership: group.instance.id avoids rebalances
• Kafka consumer lag: why it grows and how it drains
• Evicted Kafka consumer: how a survivor takes its partition

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