Creating a workbench and selecting a workbench image

A workbench is an instance of your development and experimentation environment. When you create a workbench, you select a workbench image (sometimes referred to as a notebook image) that is optimized with the tools and libraries that you need for developing models.

Prerequisites
Procedure
  1. Navigate to the project detail page for the data science project that you created in Setting up your data science project.

  2. Click the Workbenches tab, and then click the Create workbench button.

    Create workbench button
  3. Fill out the name and description.

    Workbench name and description

    Red Hat provides several supported workbench images. In the Notebook image section, you can choose one of the default images or a custom image that an administrator has set up for you. The Tensorflow image has the libraries needed for this workshop.

  4. Select the latest Tensorflow image.

    Workbench image
  5. Choose a small deployment.

    Workbench size
  6. Leave the default environment variables and storage options.

    Workbench storage
  7. For Connections, click Attach existing connection.

  8. Select My Storage (the object storage that you configured previously) and then click Attach.

    Connection form
  9. Click Create workbench.

Verification

In the Workbenches tab for the project, the status of the workbench changes from Starting to Running.

Workbench list
If you made a mistake, you can edit the workbench to make changes.
Workbench list edit