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• org/apache/kafka/connect/mirror/MirrorMetrics - new metrics templates for max, min, avg and value replication-offset-lag

  Code Block
  language java title MirrorMetrics.java
  replicationOffsetLag = new MetricNameTemplate( "replication-offset-lag", SOURCE_CONNECTOR_GROUP, "Count of records to be replicated from source to target cluster.", partitionTags); replicationOffsetLagMax = new MetricNameTemplate( "replication-offset-lag-max", SOURCE_CONNECTOR_GROUP, "Max count of records to be replicated from source to target cluster.", partitionTags); replicationOffsetLagMin = new MetricNameTemplate( "replication-offset-lag-min", SOURCE_CONNECTOR_GROUP, "Min count of records to be replicated from source to target cluster.", partitionTags); replicationOffsetLagAvg = new MetricNameTemplate( "replication-offset-lag-avg", SOURCE_CONNECTOR_GROUP, "Average count of records to be replicated from source to target cluster.", partitionTags)

  
  

• (Optional) - MirrorConnectorConfig - a configuration to control the poll interval for the Consumer.endOffsets() call at LEO acquisition mentioned below.

  [below|# changeSteps]
  

Proposed Changes

This proposal aims to enhance Kafka's monitoring capabilities by introducing a new metric to track the replication offset lag for a given topic-partition. The metric will be calculated by taking the difference between the LEO of a partition, which will be periodically updated by calling Consumer.endOffsets(), and the LRO of a partition, which will be stored in an in-memory "cache" and updated during the task's producer callback.

The proposed changes involve the following steps:

{anchor: chageStepschangeSteps}

1. LRO Tracking Mechanism:

   • Introduce a new in-memory "cache" to store the LRO for each topic-partition.
   • Update the producer callback logic to keep this LRO cache up-to-date.

2. LEO Acquisition during Poll Loop: 

   • Introduce a periodic poll mechanism to keep a fresh set of end offsets for all partitions
     • An alternative is to call Consumer.endOffsets() at each poll, which would be inefficient and expensive.
3. Calculate the replication offset lag as LEO - LRO 

4. Expose Replication Offset Lag Metric:

   • Introduce a new MirrorMaker metric, named "replication_offset_lag", which represents the calculated replication offset lag.

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