Book Image

Practical DevOps - Second Edition

By : joakim verona
Book Image

Practical DevOps - Second Edition

By: joakim verona

Overview of this book

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all code workflows from testing environments to production environments. It stresses cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations. Practical DevOps begins with a quick refresher on DevOps and continuous delivery and quickly moves on to show you how DevOps affects software architectures. You'll create a sample enterprise Java application that you’'ll continue to work with through the remaining chapters. Following this, you will explore various code storage and build server options. You will then learn how to test your code with a few tools and deploy your test successfully. In addition to this, you will also see how to monitor code for any anomalies and make sure that it runs as expected. Finally, you will discover how to handle logs and keep track of the issues that affect different processes. By the end of the book, you will be familiar with all the tools needed to deploy, integrate, and deliver efficiently with DevOps.
Table of Contents (12 chapters)

Taking build errors seriously

The build server can signal errors and code quality problems as much as it wants, but if developer teams don't care about the problems, then the investment in the notifications and visualization is all for nothing.

This isn't something that can be solved by technical means alone. There has to be a process that everybody agrees on, and the easiest way for a consensus to be achieved is for the process to be of obvious benefit to everyone involved.

Part of the problem is organizations where everything is on fire all the time. Is a build error more important than a production error? If code quality measures estimate that it will take years to improve a code base's quality, is it worthwhile to even get started with fixing the issues?

How do we solve these kinds of problems?

Here are some ideas:

  • Don't overdo your code quality metrics...