Measure pending and outstanding Remote Segment operations

https://cwiki.apache.org/confluence/display/KAFKA/KIP-963%3A+Upload+and+delete+lag+metrics+in+Tiered+Storage

KAFKA-15833: RemoteCopyLagBytes

KAFKA-16002: RemoteCopyLagSegments, RemoteDeleteLagBytes, RemoteDeleteLagSegments

KAFKA-16013: ExpiresPerSec

KAFKA-16014: RemoteLogSizeComputationTime, RemoteLogSizeBytes, RemoteLogMetadataCount

KAFKA-15158: RemoteDeleteRequestsPerSec, RemoteDeleteErrorsPerSec, BuildRemoteLogAuxStateRequestsPerSec, BuildRemoteLogAuxStateErrorsPerSec

====

Remote Log Segment operations (copy/delete) are executed by the Remote Storage Manager, and recorded by Remote Log Metadata Manager (e.g. default TopicBasedRLMM writes to the internal Kafka topic state changes on remote log segments).

As executions run, fail, and retry; it will be important to know how many operations are pending and outstanding over time to alert operators.

Pending operations are not enough to alert, as values can oscillate closer to zero. An additional condition needs to apply (running time > threshold) to consider an operation outstanding.

Proposal:

RemoteLogManager could be extended with 2 concurrent maps (pendingSegmentCopies, pendingSegmentDeletes) `Map[Uuid, Long]` to measure segmentId time when operation started, and based on this expose 2 metrics per operation:

• pendingSegmentCopies: gauge of pendingSegmentCopies map
• outstandingSegmentCopies: loop over pending ops, and if now - startedTime > timeout, then outstanding++ (maybe on debug level?)

Is this a valuable metric to add to Tiered Storage? or better to solve on a custom RLMM implementation?

Also, does it require a KIP?

Thanks!