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Practical DevOps, Second Edition

By : joakim verona

5 (1)

Practical DevOps, Second Edition

5 (1)

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.

Preface

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Introducing DevOps and Continuous Delivery

Introducing DevOps and Continuous Delivery

Introducing DevOps

How fast is fast?

The Agile wheel of wheels

Beware the cargo cult Agile fallacy

DevOps and ITIL

Summary

A View from Orbit

A View from Orbit

The DevOps process and CD – an overview

Release management

Scrum, Kanban, and the delivery pipeline

Wrapping up – a complete example

Identifying bottlenecks

Summary

How DevOps Affects Architecture

How DevOps Affects Architecture

Introducing software architecture

The monolithic scenario

The Twelve Factors

Architecture rules of thumb

Back to the monolithic scenario

A practical example

Handling database migrations

Manual installation

Microservices

Interlude – Conway's law

How to keep service interfaces forward compatible

Microservices and the data tier

DevOps, architecture, and resilience

Summary

Everything is Code

Everything is Code

The need for source code control

The history of source code management

Roles and code

Which source code management system?

A word about source code management system migrations

Shared authentication

Hosted Git servers

Large binary files

Trying out different Git server implementations

Docker intermission

Gerrit

The pull request model

GitLab

Summary

Building the Code

Building the Code

Why do we build code?

The many faces of build systems

The Jenkins build server

Managing build dependencies

The final artifact

Cheating with FPM

Continuous Integration

Continuous Delivery

Jenkins plugins

The host server

Build slaves

Software on the host

Triggers

Job chaining and build pipelines

A look at the Jenkins filesystem layout

Build servers and Infrastructure as Code

Build phases

Alternative build servers

Collating quality measures

About build status visualization

Taking build errors seriously

Robustness

Summary

Testing the Code

Testing the Code

Manual testing

Pros and cons with test automation

Unit testing

xUnit in general and JUnit in particular

Mocking

Test coverage

Automated integration testing

Performance testing

Automated acceptance testing

Automated GUI testing

Integrating Selenium tests in Jenkins

JavaScript testing

Testing backend integration points

Test-driven development

REPL-driven development

A complete test automation scenario

Summary

Deploying the Code

Deploying the Code

Why are there so many deployment systems?

Virtualization stacks

Executing code on the client

The Puppet master and Puppet agents

Ansible

Deploying with Chef

Deploying with SaltStack

Salt versus Ansible versus Puppet execution models

Vagrant

Deploying with Docker

Comparison tables

Cloud solutions

AWS

Azure

Summary

Monitoring the Code

Monitoring the Code

Nagios

Munin

Ganglia

Graphite

Log handling

Summary

Issue Tracking

Issue Tracking

What are issue trackers used for?

Some examples of workflows and issues

What do we need from an issue tracker?

Problems with issue tracker proliferation

All the trackers

Summary

The Internet of Things and DevOps

The Internet of Things and DevOps

Introducing the IoT and DevOps

The future of the IoT according to the market

Machine-to-machine communication

IoT deployment affects software architecture

IoT deployment security

Okay, but what about DevOps and the IoT again?

A hands-on lab with an IoT device for DevOps

Summary

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REPL-driven development

While REPL-driven development isn't a widely recognized term, it is my favored style of development and has a particular bearing on testing. This style of development is very common when working with interpreted languages, such as Lisp, Python, Ruby, and JavaScript.

When you work with a Read-Eval-Print-Loop (REPL), you write small functions that are independent and also not dependent on a global state.

The functions are tested even as you write them.

This style of development differs a bit from TDD. The focus is on writing small functions with no or very few side effects. This makes the code easy to comprehend, rather than when writing test cases before functioning code is written, as in TDD.

You can combine this style of development with unit testing. Since you can use REPL-driven development to develop your tests as well, this combination is a very...

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