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What does "Does not have minimum availability" mean?

A GitHub discussion was found, but it is not clear to me what the error message means.

  • 1
    Not enough cpu share or memory exhausted... – Tensibai Apr 27 '18 at 13:32
  • Hi @030, how you have fixed this issue? please! – Abdul Rehman Jul 5 '18 at 6:25
  • @AbdulRehman Please check the accepted answer – 030 Jul 5 '18 at 16:36

As @Tensibai indicated in one the comments, this could be caused as there is unsufficient CPU or memory, but that is not always the case.

For example, a helm chart was just deployed, it failed and the workload in GCP indicated that:

Pod errors: CrashLoopBackOff

Based on the comment of @Tensibai the first impression was that there were insufficient resources, but further analysis using kubectl describe pod <pod-name> indicated that in this case the livenessProbe check failed:

Liveness probe failed: Get dial 
tcp getsockopt: connection refused

In summary, the Does not have minimum availability message is generic. Multiple issues could trigger this and more in dept analysis is required to find the actual error.

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  • Hi @030, what is the solution? – Abdul Rehman Jul 5 '18 at 5:37
  • 1
    @AbdulRehman the livenessProbe failed – 030 Jul 5 '18 at 16:47
  • Does not have minimum availability simply means that not enough pods are running to meet the required replicasets then? – Alexej Magura Oct 3 '19 at 17:59

Just want to throw out an example of it not being the CPU / mem.

I remade a cluster, which included a new node pool, nodes, etc. Then tried re-deploying some of the pods that were on the previous cluster. 3 of them were working, and one kept showing "Does not have minimum availability".

It turns out, the pod in question's deployment file had spec.template.spec.nodeName hard-coded to one of the nodes from the previous cluster. In the new cluster, that node does not exist, so it failed.

Review your k8s deployment file (.yaml or .json) if you are running into this issue and the other solutions don't work. Maybe even service files as well.

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If your persistent volumes aren't creating, it'll cause this error. So add DISK to CPU/Mem/NodeSpec requirements.

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