Category Archives: Ops and DevOps

Custom Hostname for Cloud Instances

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Categories: Altus CDH Cloud Cloudera Director How-to Ops and DevOps Tools

Cloudera Altus Director provides the simplest way to deploy and manage Cloudera Enterprise in the cloud. It enables customers to unlock the benefits of enterprise-grade Hadoop while leveraging the flexibility, scalability, and affordability of the cloud. It integrates seamlessly with Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure, and provides support to build custom plugins for other public or private cloud environments.

Motivation

While automating the provisioning of a cluster on the cloud using Altus Director,

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How-to: Deploy a Secure Enterprise Data Hub on Microsoft Azure – Part 2

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Categories: CDH Cloud How-to Ops and DevOps Platform Security & Cybersecurity

In Part 1 of the blog, we covered all the prerequisites  needed to deploy a CDH cluster on the Microsoft Azure cloud platform. In Part 2, we will cover the resources required on the Azure platform and actually deploy a cluster with Cloudera Director.

Cloudera Director Use Case

Cloudera Director simplifies cluster creation and lessen the time to an operational cluster on the cloud. It’s a great tool for running POCs in your organization.

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How-to: Deploy a Secure Enterprise Data Hub on Microsoft Azure – Part 1

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Categories: CDH Cloud Hadoop How-to Ops and DevOps Platform Security & Cybersecurity

 

Learn how to use Cloudera Director, Microsoft Active Directory (AD DS, AD CS, AD DNS), SAMBA, and SSSD to deploy a secure EDH cluster for workloads in the public cloud.

Authenticating users in Apache Hadoop is the first line of security we recommend. Like most, if not all RDBMS, a user is provided with a username and a password to validate their identity. This is a requirement to access any data managed by those systems.

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How-to: Automate Your sparklyr Environment with Cloudera Director

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Categories: Cloudera Manager Data Science Hadoop How-to Ops and DevOps Spark

Since the launch of sparklyr, working with Apache Spark in Apache Hadoop has become much easier for R users. sparklyr contains a dplyr interface into Spark and allows users to leverage crucial machine learning algorithms from Spark MLlib and H2O Sparkling Water. This greatly reduces the barrier of entry for R users in adopting Spark as a tool for big data and should go a long way in enabling R workloads to migrate to Hadoop.

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Resource Management for Apache Impala (incubating)

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Categories: CDH Cloudera Manager Hadoop Impala Ops and DevOps Use Case

Apache Impala (incubating) includes several features that allow you to restrict or allocate resources so as to maximize stability and performance for your Impala workloads. You can limit both CPU and memory resources used by Impala to manage and prioritize jobs on CDH clusters. This blog post describes the techniques a typical Impala deployment can use to manage its resources.

Static Service Pools

Static service pools isolate services from one another, so that a high load on one service has limited impact on other services.

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