Configuring the pipeline editor

Configuring supported runtimes

The pipeline editor supports three runtimes: Kubeflow Pipelines, Apache Airflow, and local execution in JupyterLab. By default, support for all runtimes is enabled when you install Elyra. The JupyterLab launcher window under the Elyra category includes a tile for each enabled runtime:

Pipeline editor tiles in the JupyterLab launcher

If you are planning to use only a subset of the supported runtimes to execute pipelines, you can enable them selectively.

Enabling specific runtimes

When you explicitly enable one or more runtimes the other runtimes are disabled. You enable runtimes by overriding the Elyra default configuration.

Override default using command line parameters

To enable one or more runtimes, launch JupyterLab with the Elyra-specific --PipelineProcessorRegistry.runtimes parameter:

$ jupyter lab --PipelineProcessorRegistry.runtimes=<runtime>

Supported parameter values for <runtime> are kfp (enable support for Kubeflow Pipelines), airflow (enable support for Apache Airflow), and local (enable support for local execution).

For example, to enable only support for Kubeflow Pipelines, run

$ jupyter lab --PipelineProcessorRegistry.runtimes=kfp

Kubeflow Pipelines editor tile in the JupyterLab launcher

To enable support for more than one runtime, specify the parameter multiple times.

$ jupyter lab --PipelineProcessorRegistry.runtimes=kfp --PipelineProcessorRegistry.runtimes=local

Kubeflow Pipelines and generic editor tiles in the JupyterLab launcher

Override default using customized configuration file

To permanently apply your runtime selection create a customized configuration file.

  1. Stop JupyterLab.

  2. Generate the configuration file.

    $ jupyter elyra --generate-config

    Note: You must specify elyra as the jupyter subcommand instead of lab.

  3. Open the generated configuration file.

  4. Locate the PipelineProcessorRegistry configuration section.

    # PipelineProcessorRegistry(SingletonConfigurable) configuration
  5. Locate the configuration entry for PipelineProcessorRegistry.runtimes

    # c.PipelineProcessorRegistry.runtimes = []
  6. Remove the leading # and add one or more of kfp,airflow, or local.

    c.PipelineProcessorRegistry.runtimes = ['kfp', 'local']
  7. Save the customized configuration file.

  8. Start JupyterLab. The pipeline editor tiles for the specified runtimes are displayed in the launcher window.

Customizing the pipeline editor

You can customize the pipeline editor behavior by opening the settings link in the empty editor window or by navigating in the JupyterLab menu bar to Settings > Advanced Settings Editor and searching for elyra. Customization options vary by release.