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https://issues.apache.org/jira/browse/GOBBLIN-2066?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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William Lo updated GOBBLIN-2066:
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Description:
Temporal workflows can have added observability metrics so that workflows can
be easily understood at-a-glance which is an improvement over the current
Gobblin system.
We want to provide the following:
1. Emit dataset-level metrics on job metadata as a GobblinTrackingEvent (to
reach feature parity with existing Gobblin)
2. Enhance return types on Temporal so that users and service operators can
easily view metadata on jobs being run, so that it becomes obvious when a job
actually commits work and to which datasets without checking the logs.
was:
Temporal workflows can have added observability metrics so that workflows can
be easily understood at-a-glance which is an improvement over the current
Gobblin system.
We want to provide the following:
1. Emit dataset-level metrics on job metadata as a GobblinTrackingEvent (to
reach feature parity with existing Gobblin)
2. Enhance return types on Temporal so that users and service operators can
easily view metadata on jobs being run, so that it becomes obvious when a job
actually commits work.
> Add Dataset level metrics in Temporal
> -------------------------------------
>
> Key: GOBBLIN-2066
> URL: https://issues.apache.org/jira/browse/GOBBLIN-2066
> Project: Apache Gobblin
> Issue Type: Improvement
> Reporter: William Lo
> Priority: Major
>
> Temporal workflows can have added observability metrics so that workflows can
> be easily understood at-a-glance which is an improvement over the current
> Gobblin system.
> We want to provide the following:
> 1. Emit dataset-level metrics on job metadata as a GobblinTrackingEvent (to
> reach feature parity with existing Gobblin)
> 2. Enhance return types on Temporal so that users and service operators can
> easily view metadata on jobs being run, so that it becomes obvious when a job
> actually commits work and to which datasets without checking the logs.
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