A Practical Guide to Continuous Delivery

Book Preface

Continuous Delivery makes it possible to bring software much faster and with substantially higher reliability into production than before. The basis for these improvements is a Continuous Delivery pipeline that automates the software rollout to a large degree and thus represents a reproducible, low-risk process for rolling out new releases.

Where does the term Continuous Delivery originate from?

The Agile Manifesto (http://agilemanifesto.org) defines as its most important objective:

“Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.”

Therefore, Continuous Delivery is a technique from the Agile field.

This book explains how such a pipeline can be built in practice and which technologies can be employed for building it. The focus is not only on compiling and installing the software, but also on the different tests needed to ensure high software quality.

In addition, the book demonstrates how Continuous Delivery affects the interplay between development and operations in the context of DevOps. Moreover, the book describes the effects of Continuous Delivery on software architecture. Further, it discusses not only the theory behind Continuous Delivery, but also introduces a possible technology stack that covers build, continuous integration, load tests, acceptance tests, and monitoring. For the internal components of the technology stack there is always an example project provided that helps the reader to gain practical experience. While the book offers a first introduction into the technology stack, it also highlights ways to gain more comprehensive knowledge on the different topics. By providing suggestions for experiments and for how to try things out on their own it invites the readers to broaden their practical knowledge. In this way the readers receive guidance about how to continue studying the presented topics and how to develop hands-on experience with them. For instance, the example projects can serve as bases for individual experiments or even for the buildup of an individual Continuous Delivery pipeline