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[feature] delete MinIO artifacts on pipeline run deletion #10816
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So artifacts aren't necessarily tied to a specific pipeline run, for instance: Pipeline Run can produce But I'm not sure the details of imported artifacts, but I think you could also technically import So we would need to consider how to handle these cases. |
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
/remove-lifecycle stale let's keep this around, as per the post, this seems to be brought up relatively often |
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
/remove-lifecycle stale |
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
This issue has been automatically closed because it has not had recent activity. Please comment "/reopen" to reopen it. |
/reopen |
@tmvfb: Reopened this issue. In response to this:
Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. |
Feature Area
/area frontend
/area backend
/area components
What feature would you like to see?
When pipeline run gets deleted, remove associated artifacts from MinIO storage and from artifacts list/DB.
What is the use case or pain point?
Consistently running kubeflow pipelines on a production cluster produces a lot of artifacts that use up a lot of storage resources. That leads to a necessity of periodical storage clean up. This process could be made much easier if the artifacts got automatically deleted on run deletion.
I found some issues that seem to address either this or similar matter, namely #8104, #5509, #5667, #5783 (related to DB entries), #7939 (might be related).
Comment #8104 (comment) describes exactly the behaviour I would expect from kubeflow pipelines as an unexperienced user.
Is there a workaround currently?
Our solution is manual cleanup which is surely not effective. If there is currently a way to setup an automated cleanup, we'd be happy to know!
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