[teiid-issues] [JBoss JIRA] (TEIID-5620) Provide flattened jmx metrics

[Steven Hawkins (Jira)]

    [ https://issues.jboss.org/browse/TEIID-5620?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13687674#comment-13687674 ] 

Steven Hawkins commented on TEIID-5620:
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Other events that could be tracked as metrics for the purpose of alerting and dynamic adjustment:
* running 3 pass sorts - if there are no other memory / queuing issues it would imply that max active plans should smaller
* requests with full output buffers - indicates that the clients are initiating large queries then lagging the server output

> Provide flattened jmx metrics
> -----------------------------
>
>                 Key: TEIID-5620
>                 URL: https://issues.jboss.org/browse/TEIID-5620
>             Project: Teiid
>          Issue Type: Quality Risk
>          Components: Server
>            Reporter: Steven Hawkins
>            Assignee: Steven Hawkins
>            Priority: Major
>             Fix For: 12.1
>
>
> Providing JMX metrics via jolokia to Prometheus does not work well with complex types.  We are providing several metric sets - engine stats, worker pool stats, requests, etc. as beans which needs to be flattened.  Simple parameters are ok to the metrics methods, but simple results are required.
> We need to make sure that at least statistics are available on:
> * number of plans waiting to be processed - this will be a primary metric for determining horizontal scale out
> * amount /%of buffer memory used - this will be a primary metric for determining if pods need to be allocated with more memory/disk
> Ideally alerting could be available on percent utilization - but we could also add a metric such as out of disk count to provide a hard count of exceptional conditions.
> It's assumed that cpu utilization will be monitored from the pod itself - which will be a primary metric for determining if pods should be allocated with more cpu resources.



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