Chapter 1. Customizing the dashboard
The OpenShift AI dashboard provides features that are designed to work for most scenarios. These features are configured in the OdhDashboardConfig
custom resource (CR) file.
To see a description of the options in the OpenShift AI dashboard configuration file, see Dashboard configuration options.
As an administrator, you can customize the interface of the dashboard, for example to show or hide some of the dashboard navigation menu options. To change the default settings of the dashboard, edit the OdhDashboardConfig
custom resource (CR) file as described in Editing the dashboard configuration file.
1.1. Editing the dashboard configuration file
As an administrator, you can customize the interface of the dashboard by editing the dashboard configuration file.
Prerequisites
- You have cluster administrator privileges for your OpenShift Container Platform cluster.
Procedure
- Log in to the OpenShift Container Platform console as a cluster administrator.
-
In the Administrator perspective, click Home
API Explorer. -
In the search bar, enter
OdhDashboardConfig
to filter by kind. -
Click the
OdhDashboardConfig
custom resource (CR) to open the resource details page. -
Select the
redhat-ods-applications
project from the Project list. - Click the Instances tab.
-
Click the
odh-dashboard-config
instance to open the details page. Click the YAML tab. Here is an example
OdhDashboardConfig
file showing default values:apiVersion: opendatahub.io/v1alpha kind: OdhDashboardConfig metadata: name: odh-dashboard-config spec: dashboardConfig: enablement: true disableBYONImageStream: false disableClusterManager: false disableISVBadges: false disableInfo: false disableSupport: false disableTracking: true disableProjects: true disablePipelines: true disableModelServing: true disableProjectSharing: true disableCustomServingRuntimes: false disableAcceleratorProfiles: true modelMetricsNamespace: '' disablePerformanceMetrics: false notebookController: enabled: true notebookSizes: - name: Small resources: limits: cpu: '2' memory: 2Gi requests: cpu: '1' memory: 1Gi - name: Medium resources: limits: cpu: '4' memory: 4Gi requests: cpu: '2' memory: 2Gi - name: Large resources: limits: cpu: '8' memory: 8Gi requests: cpu: '4' memory: 4Gi modelServerSizes: - name: Small resources: limits: cpu: '2' memory: 8Gi requests: cpu: '1' memory: 4Gi - name: Medium resources: limits: cpu: '8' memory: 10Gi requests: cpu: '4' memory: 8Gi - name: Large resources: limits: cpu: '10' memory: 20Gi requests: cpu: '6' memory: 16Gi groupsConfig: adminGroups: 'odh-admins' allowedGroups: 'system:authenticated' templateOrder: - 'ovms' templateDisablement: - 'ovms'
- Edit the values of the options that you want to change.
- Click Save to apply your changes and then click Reload to make sure that your changes are synced to the cluster.
Verification
Log in to OpenShift AI and verify that your dashboard configurations apply.
1.2. Dashboard configuration options
The OpenShift AI dashboard includes a set of core features enabled by default that are designed to work for most scenarios. Administrators can configure the OpenShift AI dashboard from the OdhDashboardConfig
custom resource (CR) in OpenShift Container Platform.
Feature | Default | Description |
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Enables admin users to add applications to the OpenShift AI dashboard Application |
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On the Applications |
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Shows the Support menu option when a user clicks the Help icon in the dashboard toolbar. To hide this menu option, set the value to |
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Shows the Settings |
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Allows Red Hat to collect data about OpenShift AI usage in your cluster. To enable data collection, set the value to |
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Shows the Settings |
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Shows the label on a tile that indicates whether the application is “Red Hat managed”, “Partner managed”, or “Self-managed”. To hide these labels, set the value to |
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Shows the Settings |
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Shows the Data Science Projects option in the dashboard navigation menu. To hide this menu option, set the value to |
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Shows the Data Science Pipelines option in the dashboard navigation menu. To hide this menu option, set the value to |
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Shows the Model Serving option in the dashboard navigation menu and in the list of components for the data science projects. To hide Model Serving from the dashboard navigation menu and from the list of components for data science projects, set the value to |
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Allows users to share access to their data science projects with other users. To prevent users from sharing data science projects, set the value to |
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Shows the Serving runtimes option in the dashboard navigation menu. To hide this menu option, set the value to |
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Enables the ability to select KServe as a Serving Platform. To disable this ability, set the value to |
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Enables the ability to select ModelMesh as a Serving Platform. To disable this ability, set the value to |
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Shows the Accelerator profiles option in the dashboard navigation menu. To hide this menu option, set the value to |
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| Enables the namespace in which the Model Serving Metrics' Prometheus Operator is installed. |
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Shows the Endpoint Performance tab on the Model Serving page. To hide this tab, set the value to |
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| Controls the Notebook Controller options, such as whether it is enabled in the dashboard and which parts are visible. |
| Allows you to customize names and resources for notebooks. The Kubernetes-style sizes are shown in the dropdown menu that appears when spawning notebooks with the Notebook Controller. Note: These sizes must follow conventions. For example, requests must be smaller than limits. | |
| Allows you to customize names and resources for model servers. | |
| Controls access to dashboard features, such as the spawner for allowed users and the cluster settings UI for admin users. | |
| Specifies the order of custom Serving Runtime templates. When the user creates a new template, it is added to this list. |