Chapter 2. The OpenShift Data Science user interface

The Red Hat OpenShift Data Science interface is based on the OpenShift web console user interface.

The Red Hat OpenShift Data Science user interface is divided into several areas:

  • The global navigation bar, which provides access to useful controls, such as Help and Notifications.

    Figure 2.1. The global navigation bar

    The global navigation bar
  • The side navigation menu, which contains different categories of pages available in OpenShift Data Science.

    Figure 2.2. The side navigation menu

    The side navigation menu
  • The main display area, which displays the current page and shares space with any drawers currently displaying information, such as notifications or quick start guides. The main display area also displays the Notebook server control panel where you can launch Jupyter by starting and configuring a notebook server. Administrators can also use the Notebook server control panel to manage other users' notebook servers.

    Figure 2.3. The main display area

    The main display area

2.2. Side navigation

There are three main sections in the side navigation:

Applications → Enabled

The Enabled page displays applications that are enabled and ready to use on OpenShift Data Science. This page is the default landing page for OpenShift Data Science.

Click the Launch application button on an application card to open the application interface in a new tab. If an application has an associated quick start tour, click the drop-down menu on the application’s card and select Open quick start to access it. This page also displays applications and components that have been disabled by your administrator. Disabled applications are denoted with Disabled on the application’s card. Click Disabled on the application’s card to access links allowing you to remove the card itself, and to re-validate its license, if the license had previously expired.

Applications → Explore
The Explore page displays applications that are available for use with OpenShift Data Science. Click on a card for more information about the application or to access the Enable button. The Enable button is visible only if an application does not require an OpenShift Operator installation. 
Data science projects
The Data science projects page allows you to organize your data science work into a single project. From this page, you can create and manage data science projects. You can also enhance the capabilities of your data science project by adding workbenches, adding storage to your project’s cluster, adding data connections, and adding model servers.
Data Science Pipelines → Pipelines
The Pipelines page allows you to import, manage, track, and view data science pipelines. Using Red Hat OpenShift Data Science pipelines, you can standardize and automate machine learning workflows to enable you to develop and deploy your data science models.
Data Science Pipelines → Runs
The Runs page allows you to define, manage, and track executions of a data science pipeline. A pipeline run is a single execution of a data science pipeline. You can also view a record of previously executed and scheduled runs for your data science project.
Model Serving
The Model Serving page allows you to manage and view the status of your deployed models. You can use this page to deploy data science models to serve intelligent applications, or to view existing deployed models. You can also determine the inference endpoint of a deployed model.
The Resources page displays learning resources such as documentation, how-to material, and quick start tours. You can filter visible resources using the options displayed on the left, or enter terms into the search bar.
Settings → Notebook images
The Notebook image settings page allows you to configure custom notebook images that cater to your project’s specific requirements. After you have added custom notebook images to your deployment of OpenShift Data Science, they are available for selection when creating a notebook server.
Settings → Cluster settings

The Cluster settings page allows you perform the following administrative tasks on your cluster:

  • Enable or disable Red Hat’s ability to collect data about OpenShift Data Science usage on your cluster.
  • Configure how resources are claimed within your cluster by changing the default size of the cluster’s persistent volume claim (PVC).
  • Reduce resource usage in your OpenShift Data Science deployment by stopping notebook servers that have been idle.
  • Schedule notebook pods on tainted nodes by adding tolerations.
Settings → User management
The User and group settings page allows you to define OpenShift Data Science user group and admin group membership.