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1: Introduction to 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
The DevOps process and Continuous Delivery – an overview
Release management
Scrum, Kanban, and the delivery pipeline
Wrapping up – a complete example
Identifying bottlenecks
Summary
3: How DevOps Affects Architecture
Introducing software architecture
The monolithic scenario
Architecture rules of thumb
The separation of concerns
The principle of cohesion
Coupling
Back to the monolithic scenario
A practical example
Three-tier systems
The presentation tier
The logic tier
The data tier
Handling database migrations
Rolling upgrades
Hello world in Liquibase
The changelog file
The pom.xml file
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
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
Choosing a branching strategy
Branching problem areas
Artifact version naming
Choosing a client
Setting up a basic Git server
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
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
Manual testing
Pros and cons with test automation
Unit testing
JUnit 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
Why are there so many deployment systems?
Virtualization stacks
Executing code on the client
The Puppet master and Puppet agents
Ansible
PalletOps
Deploying with Chef
Deploying with SaltStack
Salt versus Ansible versus Puppet versus PalletOps execution models
Vagrant
Deploying with Docker
Comparison tables
Cloud solutions
AWS
Azure
Summary
8: Monitoring the Code
Nagios
Munin
Ganglia
Graphite
Log handling
Summary
9: 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
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
backindex: Appendix A: Index