ML Runtimes in Cloudera Machine Learning now support Add Ons such as Spark

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ML Runtimes are designed to be the successor to Engines in Cloudera Machine Learning (CML), moving away from the monolithic architecture of Engines and enabling finer grained control over exactly what is necessary by defining the Editor, Kernel, Edition, and Version needed for the given workload. One core piece previously missing from ML Runtimes was the ability to define Addons that go beyond these settings, in particular the ability to leverage the Spark execution engine through an ML Runtime.

Admins can now define Addons for ML Runtimes, including Spark and Hadoop CLI. In doing so, Users can leverage these Addons when running workloads such as Sessions, thereby enabling such functionality as Spark-on-K8s to be run through the ML Runtime.

To learn more, visit the documentation about Runtime Addons in CML.