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creating-a-project-workbench.adoc

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Creating a workbench

When you create a workbench, you specify an image (an IDE, packages, and other dependencies). You can also configure connections, cluster storage, and add container storage.

Prerequisites

  • You have logged in to {productname-long}.

  • If you use {productname-short} groups, you are part of the user group or admin group (for example, {oai-user-group} or {oai-admin-group} ) in OpenShift.

  • You created a project.

  • If you created a Simple Storage Service (S3) account outside of {productname-long} and you want to create connections to your existing S3 storage buckets, you have the following credential information for the storage buckets:

    • Endpoint URL

    • Access key

    • Secret key

    • Region

    • Bucket name

Procedure

  1. From the {productname-short} dashboard, click Data Science Projects.

    The Data Science Projects page opens.

  2. Click the name of the project that you want to add the workbench to.

    A project details page opens.

  3. Click the Workbenches tab.

  4. Click Create workbench.

    The Create workbench page opens.

  5. In the Name field, enter a unique name for your workbench.

  6. Optional: If you want to change the default resource name for your workbench, click Edit resource name.

    The resource name is what your resource is labeled in OpenShift. Valid characters include lowercase letters, numbers, and hyphens (-). The resource name cannot exceed 30 characters, and it must start with a letter and end with a letter or number.

    Note: You cannot change the resource name after the workbench is created. You can edit only the display name and the description.

  7. Optional: In the Description field, enter a description for your workbench.

  8. In the Notebook image section, complete the fields to specify the workbench image to use with your workbench.

    From the Image selection list, select a workbench image that suits your use case. A workbench image includes an IDE and Python packages (reusable code). Optionally, click View package information to view a list of packages that are included in the image that you selected.

    If the workbench image has multiple versions available, select the workbench image version to use from the Version selection list. To use the latest package versions, Red Hat recommends that you use the most recently added image.

    Note
    		 You can change the workbench image after you create the workbench.

  9. In the Deployment size section, from the Container size list, select a container size for your server. The container size specifies the number of CPUs and the amount of memory allocated to the container, setting the guaranteed minimum (request) and maximum (limit) for both.

  10. Optional: In the Environment variables section, select and specify values for any environment variables.

    Setting environment variables during the workbench configuration helps you save time later because you do not need to define them in the body of your notebooks, or with the IDE command line interface.

    If you are using S3-compatible storage, add these recommended environment variables:

    • AWS_ACCESS_KEY_ID specifies your Access Key ID for Amazon Web Services.

    • AWS_SECRET_ACCESS_KEY specifies your Secret access key for the account specified in AWS_ACCESS_KEY_ID.

    {productname-short} stores the credentials as Kubernetes secrets in a protected namespace if you select Secret when you add the variable.

  11. In the Cluster storage section, configure the storage for your workbench. Select one of the following options:

    • Create new persistent storage to create storage that is retained after you shut down your workbench. Complete the relevant fields to define the storage:

      1. Enter a name for the cluster storage.

      2. Enter a description for the cluster storage.

      3. Select a storage class for the cluster storage.

        Note
        		 You cannot change the storage class after you add the cluster storage to the workbench.

      4. Under Persistent storage size, enter a new size in gibibytes or mebibytes.

    • Use existing persistent storage to reuse existing storage and select the storage from the Persistent storage list.

  12. Optional: You can add a connection to your workbench. A connection is a resource that contains the configuration parameters needed to connect to a data source or sink, such as an object storage bucket. You can use storage buckets for storing data, models, and pipeline artifacts. You can also use a connection to specify the location of a model that you want to deploy.

    In the Connections section, use an existing connection or create a new connection:

    • Use an existing connection as follows:

      1. Click Attach existing connections.

      2. From the Connection list, select a connection that you previously defined.

    • Create a new connection as follows:

      1. Click Create connection. The Add connection dialog appears.

      2. From the Connection type drop-down list, select the type of connection. The Connection details section appears.

      3. If you selected S3 compatible object storage in the preceding step, configure the connection details:

        1. In the Connection name field, enter a unique name for the connection.

        2. Optional: In the Description field, enter a description for the connection.

        3. In the Access key field, enter the access key ID for the S3-compatible object storage provider.

        4. In the Secret key field, enter the secret access key for the S3-compatible object storage account that you specified.

        5. In the Endpoint field, enter the endpoint of your S3-compatible object storage bucket.

        6. In the Region field, enter the default region of your S3-compatible object storage account.

        7. In the Bucket field, enter the name of your S3-compatible object storage bucket.

        8. Click Create.

      4. If you selected URI in the preceding step, configure the connection details:

        1. In the Connection name field, enter a unique name for the connection.

        2. Optional: In the Description field, enter a description for the connection.

        3. In the URI field, enter the Uniform Resource Identifier (URI).

        4. Click Create.

  13. Click Create workbench.

Verification

  • The workbench that you created appears on the Workbenches tab for the project.

  • Any cluster storage that you associated with the workbench during the creation process appears on the Cluster storage tab for the project.

  • The Status column on the Workbenches tab displays a status of Starting when the workbench server is starting, and Running when the workbench has successfully started.

  • Optional: Click the Open link to open the IDE in a new window.