Book Image

Hands-on DevOps

By : Sricharan Vadapalli
Book Image

Hands-on DevOps

By: Sricharan Vadapalli

Overview of this book

<p>DevOps strategies have really become an important factor for big data environments.</p> <p>This book initially provides an introduction to big data, DevOps, and Cloud computing along with the need for DevOps strategies in big data environments. We move on to explore the adoption of DevOps frameworks and business scenarios. We then build a big data cluster, deploy it on the cloud, and explore DevOps activities such as CI/CD and containerization. Next, we cover big data concepts such as ETL for data sources, Hadoop clusters, and their applications. Towards the end of the book, we explore ERP applications useful for migrating to DevOps frameworks and examine a few case studies for migrating big data and prediction models.</p> <p>By the end of this book, you will have mastered implementing DevOps tools and strategies for your big data clusters.</p>
Table of Contents (22 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
11
DevOps Adoption by ERP Systems
12
DevOps Periodic Table
13
Business Intelligence Trends
14
Testing Types and Levels
15
Java Platform SE 8

Principles to build big data enterprise applications


Big data platforms and applications manage, integrate, analyze, and secure analytics on many data types both within the enterprise as well as in external data. They integrate multiple data sources in real time, taking into account volume, velocity, and variety. The platform can be built as a repository of an enterprise knowledge base with the organization's collective data assets.

Some of the salient features for building these platforms are discussed and as we see DevOps is very appropriate and instruments to enhance value at every stage, like versioning systems for building algorithms, data models, scalable reproducible platforms with virtual machines as seen in previous chapter:

  • Flexible data modeling: Big data systems integrate many different forms of data from multiple data sources. Rather than a pre-defined schema of rigid rows and columns, the schema is to be defined on the fly and data modeled to reflect how information is to be...