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Consumer lag

Consumer lag measures how much a consumer’s processing position trails the latest available data or events.

How 2 Manning books explain it

Apache Kafka in Action

A consumer lag metric reports replication lag separately for each follower, topic, and partition.

How it is used
Tracks replication delay separately for each follower, topic, and partition.
How deep it goes
Defines the metric's scope and operating expectations, but does not give a collection command or alert threshold.
Examples
Uses leader-and-follower replication as its operating case; offset tables illustrate the distinct consumer-group lag.
What you can do after
Diagnose/debug with it by locating a lagging follower, topic, and partition and watching for progressively increasing delay.

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Kafka for Architects

Lag is the amount by which processing or consumption falls behind the latest available data.

How it is used
Guides consumer scaling and operational monitoring by revealing whether a consumer group keeps pace with incoming records.
How deep it goes
Defines lag, gives JMX and offset-based calculations, and notes missing-offset inaccuracies without detailing metric implementation.
Examples
Uses a customer aggregation consumer and a partition-offset diagram to make backlog measurement concrete.
What you can do after
Diagnose processing backlogs and evaluate when consumer instances or monitoring investigation may be necessary.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.