CDP (Cloudera Data Platform) Private Cloud 1.2 was recently released and builds on the success of CDP Private Cloud Base (see the 7.1.6 release blog). While Private Cloud Base is the ideal modernization of both CDH and HDP deployments for traditional workloads, Private Cloud adds cloud-native capabilities. In this blog, we’ll cover the complete range […]
CDP (Cloudera Data Platform) Private Cloud 1.2 was recently released and builds on the success of CDP Private Cloud Base (see the 7.1.6 release blog). While Private Cloud Base is the ideal modernization of both CDH and HDP deployments for traditional workloads, Private Cloud adds cloud-native capabilities. In this blog, we’ll cover the complete range of new capabilities and updates for CDP Private Cloud as a whole (the platform) as well as for both the CDW (Cloudera Data Warehouse) and CML (Cloudera Machine Learning) services.
With the complete overview further in this blog, we wanted to highlight three key aspects of the release; one each from platform, CDW, and CML.
To deliver its cloud-native capabilities, CDP Private Cloud leverages Red Hat’s OpenShift. Both CDP Private Cloud, as well as the OpenShift cluster it’s deployed on, may need occasional upgrading (this new 1.2 release is a case in point. Companies can now upgrade either component, CDP Private Cloud as well as OpenShift, in place and in any order thereby reducing system downtime.
When initially released for Private Cloud, CDW’s resource requirements were fully driven by the minimum specifications for OpenShift. Yet for organizations that only want to get their toes wet and perhaps just evaluate the capability, the 16 cores, 128 GB RAM, and 600 GB of storage prevented them from doing just that. With Private Cloud 1.2, we introduce detailed low resource requirements that reduce the amount of CPU, RAM, and storage needed by up to 75%.
Applied ML Prototypes, AMPs for short, provide a revolutionary new way of developing and shipping enterprise ML use cases. AMPs provide complete ML projects that can be deployed with one click directly from Cloudera Machine Learning. With AMPs, data scientists can go from an idea to a fully working ML use case in a fraction of the time, with an end-to-end framework for building, deploying, and monitoring business-ready ML applications instantly. To find out more about AMPs, read this blog, which also links to the full documentation and a webinar on the subject.
Private Cloud 1.2 delivers more than the highlights above. Here’s a list of all its new capabilities and updates:
With CDP Private Cloud 1.2 now GA, we’re already hard at work on future releases. Later this year, you can expect the long-anticipated Cloudera Data Engineering to be added to the list of services, delivering Spark on Kubernetes. Stay tuned for further announcements and communication this summer.
CDP Private Cloud Plus customers can access 1.2 directly from Cloudera Manager; to upgrade your subscription please contact your Cloudera account manager. For more information, please also read the CDP Private Cloud 1.2 documentation. If this release overview piqued your interest, you can trial CDP Private Cloud free for 60 days.