Apache Hadoop Distributed File System (HDFS) is the most popular file system in the big data world. The Apache Hadoop File System interface has provided integration to many other popular storage systems like Apache Ozone, S3, Azure Data Lake Storage etc. Some HDFS users want to extend the HDFS Namenode capacity by configuring Federation of Namenodes. Other users prefer other alternative file systems like Apache Ozone or S3 due to their scaling benefit.

This is the first installment in a short series of blog posts about security in Apache Kafka. In this article we will explain how to configure clients to authenticate with clusters using different authentication mechanisms.

In this blog post, let us take a look at how you can plan your infrastructure planning that you may have to do when deploying an operational database cluster on a CDP Private Cloud Base deployment. Note that you may have to do some planning assumptions when designing your initial infrastructure, and it must be flexible enough to scale up or down based on your future needs.

Canada is poised to become a world-leader in privacy regulation and with new regulation comes record-breaking fines for those who can’t keep up. In November, Canada introduced the Digital Charter Implementation Act. If passed, companies could face fines of up to five percent of global revenue or $25 million CAD — whichever is greater — for violating Canadians’ privacy.

I met Matthew in New York City about a year ago. We sat in a private conference room and he told me the story of his pharma startup. A small group of researchers set out to solve the black-box enigma of certain kinds of vicious cancers. There are so many cancers, so their vision was to focus on especially heinous ones. Fast forward to their recent FDA approval of their “Hail Mary” procedure and treatment methodology for stage-four patients of a particular cancer.

With the complexity of data growing across the enterprise and emerging approaches to machine learning and AI use cases, data scientists and machine learning engineers have needed more versatile and efficient ways of enabling data access, faster processing, and better, more customizable resource management across their machine learning projects.

Upgrading components of Cloudera Data Warehouse (CDW) is as easy as one decision and a few clicks. While the Database (DB) Catalog and Virtual Warehouses (VWs) need to be compatible, the CDW upgrade framework understands the interoperability constraints between them.