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OpenStack Trove

  • Book
  • © 2015

Overview

  • The first and best book on OpenStack Trove

  • The authors are leading contributors to the project and thought leaders in the community.

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Table of contents (11 chapters)

About this book

OpenStack Trove is your step-by-step guide to set up and run a secure and scalable cloud Database as a Service (DBaaS) solution. The book shows you how to set up and configure the Trove DBaaS framework, use prepackaged or custom database implementations, and provision and operate a variety of databases—including MySQL, PostgreSQL, MongoDB, Cassandra, and Redis—in development and production environments.

Authors Amrith Kumar and Douglas Shelley, both active technical contributors to the Trove project, describe common deployment scenarios such as single-node database instances and walk you through the setup, configuration, and ongoing management of complex database topics like replication, clustering, and high availability. The book provides detailed descriptions of how Trove works and gives you an in-depth understanding of its architecture.

It also shows you how to avoid common errors and debug and troubleshoot Trove installations, and perform common tasks such as:

About the authors

Amrith is the CTO at Tesora, which he founded, bringing more than two decades of experience delivering industry-leading products for companies specializing in enterprise storage applications, fault tolerant high performance systems and massively parallel databases. He is an active technical contributor to the OpenStack Trove (database as a service project), and is a member of the core review team for that project. Before that, he served as vice president of technology and product management at Dataupia, maker of the Satori Data Warehousing platform, and Sepaton’s director and general manager where he was responsible for the development of the core virtual tape library product. He is the named inventor in a number of patents on technologies related to high performance databases and algorithms with wide applicability in distributed computing.

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