Book Image

OpenStack for Architects - Second Edition

By : Michael Solberg, Ben Silverman
Book Image

OpenStack for Architects - Second Edition

By: Michael Solberg, Ben Silverman

Overview of this book

Over the past six years, hundreds of organizations have successfully implemented Infrastructure as a Service (IaaS) platforms based on OpenStack. The huge amount of investment from these organizations, including industry giants such as IBM and HP, as well as open source leaders, such as Red Hat, Canonical, and SUSE, has led analysts to label OpenStack as the most important open source technology since the Linux operating system. Due to its ambitious scope, OpenStack is a complex and fast-evolving open source project that requires a diverse skill set to design and implement it. OpenStack for Architects leads you through the major decision points that you'll face while architecting an OpenStack private cloud for your organization. This book will address the recent changes made in the latest OpenStack release i.e Queens, and will also deal with advanced concepts such as containerization, NVF, and security. At each point, the authors offer you advice based on the experience they've gained from designing and leading successful OpenStack projects in a wide range of industries. Each chapter also includes lab material that gives you a chance to install and configure the technologies used to build production-quality OpenStack clouds. Most importantly, the book focuses on ensuring that your OpenStack project meets the needs of your organization, which will guarantee a successful rollout.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Big data and scientific compute use case


When we think of large clouds of compute, storage, and network, many think of parallel processing, large amounts of data, and data analytics. However, in order to get to that panacea of cloud computing, we have to first design and orchestrate a solution. With data being generated from almost every device and being delivered through the network, it's very difficult to collect and store this data and almost impossible to perform analytics with traditional tooling. There are many approaches to solving this issue. Some of these are:

  • Hadoop: Based on a filesystem called Hadoop Distributed File System (HDFS) and related technologies such as Map/Reduce
  • NoSQL: MongoDB, Cassandra, CouchDB, Couchbase, and so on
  • NewSQL: InnoDB, Scalebase, and newer technologies such as NuoDB

Hadoop is the leader in the market right now, but all of the solutions mentioned previously are based on the CAP Theorem (Brewer's conjecture). Unlike RDBMS, which was the leading solution to...