I would like to set the value KubeletConfiguration.cpuCFSQuota = false
in the config.yaml
passed to kubeadm
when launching minikube
to turn off CPU resource checking, but I have not managed to find the options to do this through the documentation here https://minikube.sigs.k8s.io/docs/handbook/config/ . The closest solution I have found is to use the option --extra-config=kubelet.cpu-cfs-quota=false
but the --cpu-cfs-quota
option for the kubelet
has been deprecated and no longer has an effect.
Any ideas appreciated.
Environment:
Thanks, Piers.
Using the --extra-config=kubelet.
flag alongside minikube start
is a good approach but you would also need to Set Kubelet parameters via a config file .
As you already noticed the --cpu-cfs-quota
flag:
Enable CPU CFS quota enforcement for containers that specify CPU limits (DEPRECATED: This parameter should be set via the config file specified by the Kubelet's
--config
flag.
So you need to set that parameter by creating a kubelet
config file:
The configuration file must be a JSON or YAML representation of the parameters in this struct. Make sure the Kubelet has read permissions on the file.
Here is an example of what this file might look like:
apiVersion: kubelet.config.k8s.io/v1beta1 kind: KubeletConfiguration evictionHard: memory.available: "200Mi"
Now you can use that config file to set cpuCFSQuota
= false
:
// cpuCFSQuota enables CPU CFS quota enforcement for containers that
// specify CPU limits.
// Dynamic Kubelet Config (beta): If dynamically updating this field, consider that
// disabling it may reduce node stability.
// Default: true
// +optional`
CPUCFSQuota *bool `json:"cpuCFSQuota,omitempty"
and than call minikube with --extra-config=kubelet.config=/path/to/config.yaml
Alternately, you can start your minikube without the --extra-config
flag and than start the Kubelet with the --config
flag set to the path of the Kubelet's config file. The Kubelet will then load its config from this file.
I know these are a few steps more than you expected but setting the kubelet parameters via a config file is the recommended approach because it simplifies node deployment and configuration management.
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