Chapter 2. Managing data science pipelines

Procedure

1. From the OpenShift AI dashboard, click Data Science Projects.

   The Data Science Projects page opens.

2. Click the name of the project that you want to configure a pipeline server for.

   A project details page opens.

3. Click the Pipelines tab.

4. Click Configure pipeline server.

   The Configure pipeline server dialog appears.

5. In the Object storage connection section, provide values for the mandatory fields:

   1. In the Access key field, enter the access key ID for the S3-compatible object storage provider.
   2. In the Secret key field, enter the secret access key for the S3-compatible object storage account that you specified.
   3. In the Endpoint field, enter the endpoint of your S3-compatible object storage bucket.
   4. In the Region field, enter the default region of your S3-compatible object storage account.

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

      Important

      If you specify incorrect data connection settings, you cannot update these settings on the same pipeline server. Therefore, you must delete the pipeline server and configure another one.

6. In the Database section, click Show advanced database options to specify the database to store your pipeline data and select one of the following sets of actions:

   • Select Use default database stored on your cluster to deploy a MariaDB database in your project.

   • Select Connect to external MySQL database to add a new connection to an external database that your pipeline server can access.

     1. In the Host field, enter the database’s host name.
     2. In the Port field, enter the database’s port.
     3. In the Username field, enter the default user name that is connected to the database.
     4. In the Password field, enter the password for the default user account.
     5. In the Database field, enter the database name.
7. Click Configure pipeline server.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the project that you want to import a pipeline to.
3. Click Import pipeline.

4. In the Import pipeline dialog, enter the details for the pipeline that you are importing.

   1. In the Pipeline name field, enter a name for the pipeline that you are importing.
   2. In the Pipeline description field, enter a description for the pipeline that you are importing.

   3. Select where you want to import your pipeline from by performing one of the following actions:

      • Select Upload a file to upload your pipeline from your local machine’s file system. Import your pipeline by clicking upload or by dragging and dropping a file.
      • Select Import by url to upload your pipeline from a URL and then enter the URL into the text box.
   4. Click Import pipeline.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the project that contains the pipeline that you want to delete from the Project list.
3. Click the action menu (⋮) beside the pipeline that you want to delete and click Delete pipeline.
4. In the Delete pipeline dialog, enter the pipeline name in the text field to confirm that you intend to delete it.
5. Click Delete pipeline.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the project for the pipeline server that you want to delete.
3. From the Pipeline server actions list, select Delete pipeline server.
4. In the Delete pipeline server dialog, enter the pipeline server’s name in the text field to confirm that you intend to delete it.
5. Click Delete.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page opens, select the project whose pipeline server you want to view.
3. From the Pipeline server actions list, select View pipeline server configuration.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the relevant project for the pipelines you want to view.
3. Study the pipelines on the list.
4. Optional: Click Expand ( ) on the relevant row to view details of any pipeline versions associated with the pipeline.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the project that you want to upload a pipeline version to.
3. Click the Import pipeline dropdown list and select Upload new version.

4. In the Upload new version dialog, enter the details for the pipeline version that you are uploading.

   1. From the Pipeline list, select the pipeline that you want to upload your pipeline version to.
   2. In the Pipeline version name field, confirm the name for the pipeline version, and change it if necessary.
   3. In the Pipeline version description field, enter a description for the pipeline version.

   4. Select where you want to upload your pipeline version from by performing one of the following actions:

      • Select Upload a file to upload your pipeline version from your local machine’s file system. Import your pipeline version by clicking upload or by dragging and dropping a file.
      • Select Import by url to upload your pipeline version from a URL and then enter the URL into the text box.
   5. Click Upload.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.

   The Pipelines page opens.

2. Delete the pipeline versions that you no longer require:

   • To delete a single pipeline version:

     1. From the Project list, select the project that contains a version of a pipeline that you want to delete.
     2. On the row containing the pipeline, click Expand ( ).

     3. Click the action menu (⋮) beside the project version that you want to delete and click Delete pipeline version.

        The Delete pipeline version dialog opens.

     4. Enter the name of the pipeline version in the text field to confirm that you intend to delete it.
     5. Click Delete.

   • To delete multiple pipeline versions:

     1. On the row containing each pipeline version that you want to delete, select the checkbox.
     2. Click the action menu (⋮) next to the Import pipeline dropdown, and select Delete from the list.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.

   The Pipelines page opens.

2. From the Project list, select the project containing the pipeline versions that you want to view details for.
3. Click Expand ( ) on the row containing the pipeline that you want to view versions for.

4. Click the pipeline version that you want to view the details of.

   The Pipeline details page opens, displaying the Graph and YAML tabs.

Procedure

1. From the OpenShift AI dashboard, click Data Science Pipelines Pipelines.
2. On the Pipelines page, select the project that contains the version that you want to download.
3. For a pipeline that contains the version that you want to download, click Expand ( ).
4. Click the pipeline version that you want to download.
5. On the Pipeline details page, click the YAML tab.
6. Click the Download button ( ) to download the YAML file containing your pipeline version code to your local machine.