Tag Archives: Cloudera Altus

Informatica Big Data Management on Cloudera Altus

Categories: CDH Cloud

Today, we’re really excited to announce the latest innovation from Cloudera and Informatica’s partnership. Companies are increasingly moving their data operations into the cloud. With both companies focusing on helping customers derive business insights out of vast amounts of data, our new joint offering will dramatically simplify leveraging cloud-native infrastructures for big data analytics.

Last May, Cloudera announced Cloudera Altus, a new platform-as-a-service (PaaS) offering in the cloud for big data analytics,

Read more

Cloudera Altus on Microsoft Azure

Categories: Altus Cloud

Cloudera Altus (launched in May 2017) is a platform-as-a-service (PaaS) offering that enables users to analyze and process data at scale in public cloud infrastructures. Altus was designed from the outset to support multiple clouds from the perspective of both back-end architecture and front-end workflows. With the announcement of Microsoft Azure support, Altus will be able to support data engineering workloads in Microsoft Azure, with the same Altus interfaces for API and CLI,

Read more

Customizing Docker Images in Cloudera Data Science Workbench

Categories: Altus CDH Cloud Data Science How-to Tools

This article shows how to build and publish a customized Docker image for usage as an engine in Cloudera Data Science Workbench. Such an image or engine customization gives you the benefit of being able to work with your favorite tool chain inside the web based application.

Motivation:

Cloudera Data Science Workbench (CDSW) enables data scientists to use their favorite tools such as R, Python, or Scala based libraries out of the box in an isolated secure sandbox environment.

Read more

Cloudera Enterprise 5.12 is Now Available

Categories: Altus CDH Cloud Cloudera Manager Cloudera Navigator Data Science Hue Impala Kafka Kudu

Cloudera is pleased to announce that Cloudera Enterprise 5.12 is now generally available (GA). The release includes enhancements for running in cloud environments (with broader ADLS support and improved AWS Spot Instance support), usability and productivity improvements for both data science and analytic workloads, as well as performance gains and self-service performance management across a range of workloads.

As usual, there are also a number of quality enhancements, bug fixes, and other improvements across the stack.

Read more