Closed schwesig closed 1 year ago
Issues go stale after 90d of inactivity.
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Stale issues rot after an additional 30d of inactivity and eventually close.
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/lifecycle stale
Stale issues rot after 30d of inactivity.
Mark the issue as fresh with /remove-lifecycle rotten
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Rotten issues close after an additional 30d of inactivity.
If this issue is safe to close now please do so with /close
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/lifecycle rotten
Rotten issues close after 30d of inactivity.
Reopen the issue with /reopen
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Mark the issue as fresh with /remove-lifecycle rotten
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/close
@sesheta: Closing this issue.
please add anybody you think could contribute here with ideas E.g. converting the mail thread into a JupyterBook seems straight forward, it already has concrete examples and we could link it with dynamic proof points e.g. the JupyterHub profile analysis by @Shreyanand
maybe we can start by identifying what sort of issues/prs we consider contributing to "adding value", and then whether we have existing labels for that also did we ever figure out a way to identify issues outside the org that are linked back to the operate-first org on github?
I think this is something @hemajv
and obviously this is an additional ask, so it would be a user story to be put on one of the scrum boards I guess O2KR2? @schwesig
"Can you provide any stats about my service? Can you give me trends on users, outages, issues, consumption?" https://grafana.operate-first.cloud/d/fuJBFErMz/jupyterhub-user-perspective?orgId=1&var-datasource=moc-smaug&var-log_datasource=app-logs&var-namespace=opf-jupyterhub&var-account=alivaster121&var-account_substring= Is he looking for an even higher level analysis of the service operations data? (maybe trends isn't captured here)
....