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.

Stop JupyterLab.
Generate the jupyter_elyra_config.py configuration file.
```
$ jupyter elyra --generate-config
```
Note: You must specify elyra as the jupyter subcommand instead of lab.
Open the generated configuration file.

Locate the PipelineProcessorRegistry configuration section.

#------------------------------------------------------------------------------
# PipelineProcessorRegistry(SingletonConfigurable) configuration
#------------------------------------------------------------------------------

Locate the configuration entry for PipelineProcessorRegistry.runtimes
```
# c.PipelineProcessorRegistry.runtimes = []
```
Remove the leading # and add one or more of kfp,airflow, or local.
```
c.PipelineProcessorRegistry.runtimes = ['kfp', 'local']
```
Save the customized configuration file.
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.