Chaoran Yu created YUNIKORN-829:
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Summary: Produce metrics on queue-level resource utilization
Key: YUNIKORN-829
URL: https://issues.apache.org/jira/browse/YUNIKORN-829
Project: Apache YuniKorn
Issue Type: New Feature
Components: core - scheduler, shim - kubernetes
Reporter: Chaoran Yu
YuniKorn already has metrics on the resources requested/allocated for each
queue. But we have no visibility into how much of the allocated resources are
actually being used. Take Spark as an example, an under-optimized job may
request 1 TB of total executor memory but the actual processing logic only uses
100 GB. This has the consequence that other jobs might not be able to fit in
the queue. Having a metric that shows the real utilization will help members of
a queue better understand their job characteristics and optimize the jobs.
K8s metrics server has metrics on real utilization. YK may be able to perform
some aggregations to arrive at the stats at the queue level. This is a
k8s-specific solution though.
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