Open Joseph-Goergen opened 3 years ago
Issues go stale after 90d of inactivity.
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Stale issues rot after 30d of inactivity.
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@fejta-bot: Closing this issue.
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@Joseph-Goergen: Reopened this issue.
/remove-lifecycle rotten
The Kubernetes project currently lacks enough contributors to adequately respond to all issues and PRs.
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Please send feedback to sig-contributor-experience at kubernetes/community.
/lifecycle stale
/remove-lifecycle stale
The Kubernetes project currently lacks enough contributors to adequately respond to all issues and PRs.
This bot triages issues and PRs according to the following rules:
lifecycle/stale
is appliedlifecycle/stale
was applied, lifecycle/rotten
is appliedlifecycle/rotten
was applied, the issue is closedYou can:
/remove-lifecycle stale
/lifecycle rotten
/close
Please send feedback to sig-contributor-experience at kubernetes/community.
/lifecycle stale
/remove-lifecycle stale
The Kubernetes project currently lacks enough contributors to adequately respond to all issues and PRs.
This bot triages issues and PRs according to the following rules:
lifecycle/stale
is appliedlifecycle/stale
was applied, lifecycle/rotten
is appliedlifecycle/rotten
was applied, the issue is closedYou can:
/remove-lifecycle stale
/lifecycle rotten
/close
Please send feedback to sig-contributor-experience at kubernetes/community.
/lifecycle stale
The Kubernetes project currently lacks enough active contributors to adequately respond to all issues and PRs.
This bot triages issues and PRs according to the following rules:
lifecycle/stale
is appliedlifecycle/stale
was applied, lifecycle/rotten
is appliedlifecycle/rotten
was applied, the issue is closedYou can:
/remove-lifecycle rotten
/close
Please send feedback to sig-contributor-experience at kubernetes/community.
/lifecycle rotten
/lifecycle frozen
We have a cluster here that has 34 nodes and 2497 pod. The metrics scraper seemed to reach 5000m of cpu and 6.7G of memory before eventually crashing.
v2.0.5
v1.0.6
The metrics scraper produces roughly 500000 log lines per hour and look like this
It seems like it's handling the requests like it should, it's just getting overloaded and can't handle that very well. I think adding a cpu and memory limit wouldn't help very much because I think that also causes the pod to keep crashing once it hits it. This is about as much info as I have about it on this cluster. The user did delete the pod and it came back and overloaded and crashed again.