This topic describes how to manage engines and configure engine environments to meet your project requirements.
By default, Cloudera Machine Learning ships a base engine image that includes kernels for Python, R, and Scala, along with some additional libraries ( see Configuring Cloudera Machine Learning Engines for more information) that can be used to run common data analytics operations. Occasionally, new engine versions are released and shipped with Cloudera Machine Learning releases.
Engine images are available in the Site Administrator panel at Settings on the left navigation bar., under the Engine Images section. As a site administrator, you can select which engine version is used by default for new projects. Furthermore, project administrators can explicitly select which engine image should be used as the default image for a project. To do so, go to the project's Overview page and click
If a user publishes a new custom Docker image, site administrators are responsible for white-listing such images for use across the deployment. For more information on creating and managing custom Docker images, see Configuring the Engine Environment.