Chapter 5. Stopping basic workbenches
When you have a running workbench, you can stop the workbench to conserve cluster resources or to make configuration changes that require a restart.
5.1. Stopping a basic workbench using the Red Hat OpenShift AI dashboard Copy linkLink copied to clipboard!
You can stop a running workbench from the Red Hat OpenShift AI dashboard.
Prerequisites
- You have logged in to Red Hat OpenShift AI.
- You have created a data science project.
- You have a running workbench that you want to stop.
Procedure
From the OpenShift AI dashboard, click Projects.
The Projects page opens.
Click the name of the project that contains the workbench you want to stop.
A project details page opens.
- Click the Workbenches tab.
- Locate the running workbench you want to stop and click the Stop button in the Status column.
Verification
- The workbench status changes from Stopping to Stopped.
5.2. Stopping a basic workbench using the OpenShift CLI (oc) Copy linkLink copied to clipboard!
You can stop a running workbench by using the OpenShift CLI (oc).
Prerequisites
- You have logged in to Red Hat OpenShift AI.
- You have created a data science project.
- You have a running workbench that you want to stop.
-
You have installed the OpenShift CLI (
oc). - You have write access to the namespace where the workbench is deployed.
Procedure
In a terminal, run the following command to annotate the notebook resource with a stop timestamp:
$ oc annotate notebook <name> -n <namespace> \ "kubeflow-resource-stopped=$(date -u +%Y-%m-%dT%H:%M:%SZ)" --overwritewhere:
_<name>_- Specifies the name of the workbench.
_<namespace>_- Specifies the name of the project.
Verification
Run the following command and verify that the
kubeflow-resource-stoppedannotation is present:$ oc get notebook <name> -n <namespace> -o jsonpath={.metadata.annotations.kubeflow-resource-stopped}