kfaraz opened a new pull request, #20708:
URL: https://github.com/apache/druid/pull/20708

   ### Changes
   
   - Use running average metrics for Kafka poll-idle-ratio and average 
processing rate (records / second)
   - The average is taken over the entire lifecycle of a task and is not 
exponentially weighted on purpose.
   - This makes it easy to reason about the metric, and is driven by the 
dominant behavior in the task duration.
   - The poll-idle-ratio is reported by the Kafka consumer but is averaged over 
a 30s window by default. This often leads to volatile metric values and the 
metric value at the exact time of the auto-scaling decision wins. In production 
setups, this becomes a die roll scenario since even though the metric had been 
consistently reporting a certain value, a momentary spike or dip would cause 
auto-scaler to make a bad decision.
   - The avg processing rate metric is currently not used heavily as it was 
also found to be volatile. So it is also being converted to a running average 
in this patch solely for monitoring purposes so that if it is found to be 
stable, we may consider using it as an alternative to the poll-idle-ratio.
   
   <hr>
   
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   This PR has:
   
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   - [ ] added integration tests.
   - [ ] been tested in a test Druid cluster.


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