We are excited to announce the release of Cloudbreak 2.7! This release includes many new enhancements that further extend the ability of the Enterprise to harness the agility of the cloud for big data workloads. Here is just a sampling of the new features available with Cloudbreak 2.7:
Running big data workloads in the cloud means you need data. Cloudbreak makes it easy to work with data that is setup in cloud storage, whether it be AWS (S3), Azure (ADLS + WASB), or Google (GCS).
Powered by Apache Knox, Cloudbreak can “wrap” your cluster in a secure gateway and reduce the network surface area by only exposing those cluster services that you plan to let users access. Cloudbreak dynamically reads your cluster blueprint and intelligently allows you to select which service(s) to configure with the gateway.
Automation and cloud go hand-in-hand. Getting your clusters to leverage external sources, such as databases or LDAP, has to be easy. Cloudbreak introduces a new capability: Dynamic Blueprints to accomplish just that. With Dynamic Blueprints, you can configure External Sources for authentication (LDAP/AD) and databases (for Hive, Ranger, etc) one time. Then these settings can be “injected into the blueprint” at provisioning time of your workload. This reduces the need for “one-off” blueprints and simplifies the DevOps experience with repeatable configuration settings.
As part of this Cloudbreak release, we are excited to announce the Data Lake Shared Services Technical Preview. This technical preview allows you to define schema and security policies as a set of Shared Data Lake Services that can be leveraged across workloads in the cloud. When you launch your clusters, you can “attach” them to a Shared Data Lake with already defined methods for authentication (LDAP/AD), schema for Hive databases, security policies (powered by Apache Ranger) and audit logging on cloud storage. The resulting modern data architecture allows you to have workloads that are ephemeral (i.e. “spun-up and spun-down” on demand) to right-size your infrastructure and only consume cloud resources when needed. As your workload executes, the defined security context, audit controls, and schema will be applied automatically and consistently.