Cloudera Machine Learning release takes cloud-native path

TONY BAER (OVUM) | December 19, 2018

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On the heels of its last quarterly report prior to the expected closing of its merger with Hortonworks, Cloudera has announced the ability to gain access to a preview of a new cloud-native counterpart for its Cloudera Data Science Workbench (DSW) that goes full tilt on Kubernetes. Significantly, it carries a different branding -- Cloudera Machine Learning (Cloudera ML).The architecture and the branding reflect two shifts in the market. The first is the move to cloud. While we estimate that only about 25 – 30% of Cloudera's installed base is running workloads in the cloud, the velocity toward cloud adoption is unmistakable. Ovum has predicted that next year, half of new big data workloads will be running on the cloud. And that dictates supporting the type of autoscaling that is possible in the cloud.The second trend is AI, or more specifically machine learning. When Cloudera initially released DSW, the brunt of activity was building more on building conventional data science models that are static – they are deployed, and then any changes made to the models are done by people.

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