adikou commented on PR #22129:
URL: https://github.com/apache/kafka/pull/22129#issuecomment-4550001336

   > Thanks for the PR @adikou. Have you considered using metric.metricName() 
for logging, I can see the usage of same in Kafka code base for logging? I also 
do not currently see where we log KafkaMetric hence don't see the need of this 
change. However the change is minimal, I am happy to review further if you put 
this in a PR where you actually have a valid usage of same or can find 
incorrect logs printed through Kafka currently. Please let me know your 
thoughts.
   
   Hi @apoorvmittal10 thanks for the feedback.
   The main use case I'm looking at as a user is the 
`MetricsReporter#metricChange(KafkaMetric)` method. Other than update an 
internal data structure sometimes logging is common practice to trace steps 
after the fact. 
   
   I do see that in several places in the codebase, with a `KafkaMetric` 
object, we log the metricName(). In this case, I see an issue with naming and 
conventions that logging just the metricName() might be insufficient. 
   
   1. For instance, in producer-topic-metrics `compression-rate` is _an average 
of compression ratio_ : it is neither a rate, nor is it the avg according to 
the description. It has a right counterpart `compression-rate-avg` in 
producer-metrics. I'm planning on filing a follow-up KIP that fixes these two.
   2. I see another mismatch in producer, and streams: `byte-total` is a total 
(knowing CumulativeSum or WindowedSum here would be useful to know) and 
`cache-size-bytes-total` is a `Value`, so not a total.
   
   I think relying on convention and metric naming alone does not give a full 
picture. So, the underlying stat when available might be useful in logs. The 
description gets logged, but tbh I feel the MetricValueProvider classname is 
simpler than going through the description string.
   
   One thing to note, I can probably skip lambdas in the calculation because 
they might look awkward in the logs and are not really meaningful.
   
   LMK what you think.
   Best, Aditya


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