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  • Book Overview & Buying Practical DevOps
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Practical DevOps

Practical DevOps

By : joakim verona
4.7 (6)
Buy this Book
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Practical DevOps

Practical DevOps

4.7 (6)
By: joakim verona
Buy this Book

Overview of this book

DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments. It stresses the cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations. After a quick refresher to DevOps and continuous delivery, we quickly move on to looking at how DevOps affects architecture. You'll create a sample enterprise Java application that you’ll continue to work with through the remaining chapters. Following this, we explore various code storage and build server options. You will then learn how to perform code testing with a few tools and deploy your test successfully. Next, you will learn how to monitor code for any anomalies and make sure it’s running properly. Finally, you will discover how to handle logs and keep track of the issues that affect processes
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
Lock Free Chapter
1
1. Introduction to DevOps and Continuous Delivery
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1. Introduction to DevOps and Continuous Delivery
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Introducing DevOps
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How fast is fast?
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The Agile wheel of wheels
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Beware the cargo cult Agile fallacy
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DevOps and ITIL
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Summary
2
2. A View from Orbit
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2. A View from Orbit
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The DevOps process and Continuous Delivery – an overview
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Release management
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Scrum, Kanban, and the delivery pipeline
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Wrapping up – a complete example
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Identifying bottlenecks
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Summary
3
3. How DevOps Affects Architecture
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3. How DevOps Affects Architecture
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Introducing software architecture
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The monolithic scenario
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Architecture rules of thumb
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The separation of concerns
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The principle of cohesion
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Coupling
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Back to the monolithic scenario
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A practical example
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Three-tier systems
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The presentation tier
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The logic tier
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The data tier
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Handling database migrations
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Rolling upgrades
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Hello world in Liquibase
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The changelog file
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The pom.xml file
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Manual installation
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Microservices
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Interlude – Conway's Law
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How to keep service interfaces forward compatible
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Microservices and the data tier
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DevOps, architecture, and resilience
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Summary
4
4. Everything is Code
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4. Everything is Code
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The need for source code control
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The history of source code management
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Roles and code
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Which source code management system?
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A word about source code management system migrations
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Choosing a branching strategy
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Branching problem areas
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Artifact version naming
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Choosing a client
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Setting up a basic Git server
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Shared authentication
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Hosted Git servers
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Large binary files
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Trying out different Git server implementations
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Docker intermission
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Gerrit
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The pull request model
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GitLab
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Summary
5
5. Building the Code
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5. Building the Code
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Why do we build code?
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The many faces of build systems
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The Jenkins build server
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Managing build dependencies
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The final artifact
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Cheating with FPM
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Continuous Integration
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Continuous Delivery
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Jenkins plugins
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The host server
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Build slaves
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Software on the host
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Triggers
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Job chaining and build pipelines
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A look at the Jenkins filesystem layout
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Build servers and infrastructure as code
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Build phases
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Alternative build servers
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Collating quality measures
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About build status visualization
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Taking build errors seriously
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Robustness
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Summary
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6. Testing the Code
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6. Testing the Code
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Manual testing
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Pros and cons with test automation
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Unit testing
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JUnit in general and JUnit in particular
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Mocking
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Test Coverage
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Automated integration testing
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Performance testing
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Automated acceptance testing
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Automated GUI testing
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Integrating Selenium tests in Jenkins
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JavaScript testing
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Testing backend integration points
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Test-driven development
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REPL-driven development
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A complete test automation scenario
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Summary
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7. Deploying the Code
chevron up
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7. Deploying the Code
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Why are there so many deployment systems?
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Virtualization stacks
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Executing code on the client
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The Puppet master and Puppet agents
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Ansible
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PalletOps
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Deploying with Chef
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Deploying with SaltStack
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Salt versus Ansible versus Puppet versus PalletOps execution models
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Vagrant
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Deploying with Docker
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Comparison tables
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Cloud solutions
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AWS
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Azure
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Summary
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8. Monitoring the Code
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8. Monitoring the Code
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Nagios
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Munin
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Ganglia
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Graphite
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Log handling
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Summary
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9. Issue Tracking
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9. Issue Tracking
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What are issue trackers used for?
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Some examples of workflows and issues
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What do we need from an issue tracker?
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Problems with issue tracker proliferation
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All the trackers
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Summary
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10. The Internet of Things and DevOps
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10. The Internet of Things and DevOps
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Introducing the IoT and DevOps
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The future of the IoT according to the market
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Machine-to-machine communication
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IoT deployment affects software architecture
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IoT deployment security
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Okay, but what about DevOps and the IoT again?
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A hands-on lab with an IoT device for DevOps
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Summary
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Index
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Index

Deploying with SaltStack

SaltStack is a Python-based deployment solution.

There is a convenient dockerized test environment for Salt, by Jackson Cage. You can start it with the following:

docker run -i -t --name=saltdocker_master_1 -h master -p 4505 -p 4506 \
   -p 8080 -p 8081 -e SALT_NAME=master -e SALT_USE=master \
   -v `pwd`/srv/salt:/srv/salt:rw jacksoncage/salt

This will create a single container with both a Salt master and a Salt minion.

We can create a shell inside the container for our further explorations:

docker exec -i -t saltdocker_master_1 bash

We need a configuration to apply to our server. Salt calls configurations "states", or Salt states.

In our case, we want to install an Apache server with this simple Salt state:

top.sls:
base:
  '*':
    - webserver

webserver.sls:
apache2:               # ID declaration
  pkg:                # state declaration
    - installed       # function declaration

Salt uses .yml files for its configuration files, similar to what...

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