Configure a browser-based IDE as an Editor

For example, if you create a new .py file or modify an existing one with the third-party editor, the changes are propagated to Cloudera Machine Learning. When you run the code from the IDE, execution is pushed from the IDE to Cloudera Machine Learning.

Base Engine Image v8 and higher for Cloudera Machine Learning comes preconfigured with Jupyter, and any browser IDEs you want to add must be added to Base Engine Image v8 or higher. Jupyter can be selected in place of the built-in Workbench editor when you launch a session, and no additional configuration is required. You can configure additional IDEs to be available from the dropdown.

You have two configuration options:

• Project Level: You can configure an editor at the project level so that any session launched within that project can use the editor configured. Other projects across the deployment will not be able to use any editors configured in such a manner. For steps, see Configure a Browser IDE at the Project Level.
• Engine Level: You can create a custom engine configured with the editor so that any project across the deployment that uses this custom engine can also use the editor configured. This might be the only option in case of certain browser IDEs (such as RStudio) that require root permission to install and therefore cannot be directly installed within the project. For steps, see Configure a Browser IDE at the Engine Level.

Cloudera recommends you first test the browser IDE you intend to install in a session before you install it to the project or build a custom engine with it. For steps, see Test a Browser IDE in a Session Before Installation.