Managing ML Runtimes
Provides overview, installation, set up, configuration, and customization information for Machine Learning Runtimes.
ML Runtimes are responsible for running the code written by users and intermediating access to the Data Hub.
You can think of an ML Runtime as a virtual machine, customized to have all the necessary dependencies to access the computing cluster while keeping each project’s environment entirely isolated. To ensure that every ML Runtime has access to the parcels and client configuration managed by the Cloudera Manager Agent, a number of folders are mounted from the host into the container environment.
ML Runtimes have been open sourced and are available in the cloudera/ml-runtimes GitHub repository. If you need to understand your Runtime environments fully or want to build a new Runtime from scratch, you can access the Dockerfiles that were used to build the ML Runtime container images in this repository.