How do consumer groups and offset commits work in an event streaming system?

Explain consumer groups and offset commits

Explains how consumer groups share event-stream work and how offset commits affect duplicate or lost processing.

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A consumer group is a set of consumer instances that share partitions from a stream. Each group tracks offsets so it knows how far it has processed. If a consumer commits an offset after processing, a crash before the commit can replay that event. If it commits before processing, a crash can lose work. I would usually commit after successful processing and make the handler idempotent.

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Consumer groups, offsets, commits, partitions, replay, duplicate processing, and failure windows.

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Offsets are the event-stream version of message acknowledgement. The timing of a commit decides whether failures cause replay, duplicates, or lost work.
A consumer group is a set of consumer instances that share partitions from a stream. Each group tracks offsets so it knows how far it has processed. If a consumer commits an offset after processing, a crash before the commit can replay that event. If it commits before processing, a crash can lose work. I would usually commit after successful processing and make the handler idempotent.
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I would separate reading from successful side effects. If processing writes to a database, I need a clear boundary between database commit and offset commit. There is usually a failure window where the database write succeeds but offset commit fails, so the event is processed again. That is why idempotency or an inbox table matters. Rebalancing can also move partitions to another consumer, so handlers need to tolerate restarts.

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Committing offsets before processing important side effects.
Assuming offset commit and database write are atomic.
No idempotency for replayed events.
Ignoring rebalances and consumer restarts.

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