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.

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Table of Contents (12 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
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
2
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
3
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
4
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
5
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
6
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
7
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
8
Monitoring the Code
Monitoring the Code
Nagios
Munin
Ganglia
Graphite
Log handling
Summary
9
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
10
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
11
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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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