Book Image

Extending OpenStack

By : Omar Khedher
Book Image

Extending OpenStack

By: Omar Khedher

Overview of this book

OpenStack is a very popular cloud computing platform that has enabled several organizations during the last few years to successfully implement their Infrastructure as a Service (IaaS) platforms. This book will guide you through new features of the latest OpenStack releases and how to bring them into production straightaway in an agile way. It starts by showing you how to expand your current OpenStack setup and how to approach your next OpenStack Data Center generation deployment. You will discover how to extend your storage and network capacity and also take advantage of containerization technology such as Docker and Kubernetes in OpenStack. Additionally, you'll explore the power of big data as a Service terminology implemented in OpenStack by integrating the Sahara project. This book will teach you how to build Hadoop clusters and launch jobs in a very simple way. Then you'll automate and deploy applications on top of OpenStack. You will discover how to write your own plugin in the Murano project. The final part of the book will go through best practices for security such as identity, access management, and authentication exposed by Keystone in OpenStack. By the end of this book, you will be ready to extend and customize your private cloud based on your requirements.
Table of Contents (12 chapters)

Big data in OpenStack

Big data analytics has recently seen a lot of hype. With the increasing amount of generated and used data, organizations today are facing new challenges to satisfy the exponential increase in data needs. Managing petabytes of records and trying to analyze the growing data in real time won't be possible without having the right tools. Fortunately, several open source solutions have come to the rescue, such as the Hadoop and Spark frameworks.

Other tools and projects have been developed around the Hadoop and Spark ecosystems to address the specific needs of different big data use cases, including HBase, Storm, MapReduce, and Avro, to name but a few. Organizations could start a less painful journey in analyzing and processing the huge amount of data by integrating Hadoop tools and others in their data science endeavors. On the other hand, this smooth start...