We have an Openshift environment on our company.
We're trying to maximize the resources between our data scientists using jupyterhub.
Is there an option for assigning more resources dynamicly per demand (if there are free resources avaliable).
You can take a look at setting resource restrictions. (Quite counterintuitive, I agree).
In Kubernetes (and therefore in OpenShift) you can set resource requests and limits.
Resource requests are the minimum a pod is guaranteed from the scheduler on the node it runs on. Resource Limits on the other hand give you the capability to allow your pod to exceed its requested resources up to the specified limit.
What is the difference between not setting resource requests and limits vs setting them?
requests and limitslimits specifiedrequestsrequests and limitsrequestsrequests and limitsIn the end it should look something like this
apiVersion: v1
kind: Pod
spec:
containers:
- image: openshift/hello-openshift
name: hello-openshift
resources:
requests:
cpu: 100m
memory: 200Mi
ephemeral-storage: 1Gi
limits:
cpu: 200m
memory: 400Mi
ephemeral-storage: 2Gi Additional information can be found here