Version Control

Overview

Version control is a crucial capability that plays a significant role in driving higher software delivery and organizational performance. Version control systems such as Git, Subversion, and Mercurial enable teams to effectively organize files and coordinate their creation, controlled access, updating, and deletion across teams and organizations. In addition, there should be a system to version, store and manage build artifacts.

Version control is closely linked to automation and continuous integration. Automation and continuous integration rely on version control for the source code of the automation itself, as well as the configuration to be automated and the data to be distributed. By using version control for source code, test and deployment scripts, infrastructure and application configuration information, and the many libraries and packages they depend upon, teams can improve their software delivery process.

Within the version control system, teams must be able to query the current (and historical) state of their environments. Version control also provides direct benefits such as disaster recovery and possibility to , which are essential for ensuring the stability and reliability of the software delivery process. Overall, version control is a critical capability for any team or organization seeking to optimize their software delivery process and achieve high performance.

What should be versioned

Application code and dependencies
Any script used to create database schemas, application reference data
Environment creation tools and artifacts described in the previous step
File used to create and compose containers
All supporting automated tests and any manual test scripts
Any script that supports code packaging, deployment, database migration, and environment provisioning
Supporting project artifacts (for example, requirements documentation, deployment procedures, and release notes)
Container orchestration
All cloud configuration files
Any other script or configuration information required to create infrastructure that supports multiple services

Version Control practices

To optimize the software delivery process and achieve high performance, it is essential to implement several key practices related to version control and automation.

One such practice is to ensure that every commit to version control triggers the automated creation of packages that can be deployed to any environment using only information in version control. This approach streamlines the deployment process and reduces the risk of errors or inconsistencies.

In addition to version control of a regular source code it is important to store packages created through the automation in an artifactory to simplify distribution and overall management of the produced software.

Produced and version controlled packages should be properly named to indicate the stage of the package lifecycle and possible scope of changes.

Another crucial practice is to make it possible to create production-like test environments on demand using only scripts and configuration information from version control. This enables teams to quickly and efficiently test new code and changes in a realistic environment, ensuring that any issues are identified and resolved before deployment. Additionally, this approach makes it easier to create packages using the automated process described in the previous approach.

To further improve efficiency and reduce the risk of errors, it is important to script testing and production infrastructure so that teams can add capacity or recover from disasters in a fully automated fashion. This ensures that critical infrastructure is always available and that teams can quickly respond to changes or disruptions without manual intervention. Overall, by implementing these practices, teams can optimize their software delivery process and achieve high performance.

Quick Links

Templates Process Capabilities Iteration Planning Work Management

Adoption expectations

System Components	MVP	MVP+
Store application code	+	+
Store system configurations	+	+
Store and version build artifacts	+	+
Map stored artifacts and software delivery process stage	+	+
Store application configuration		+
Store scripts for automating build and configuration		+

Tools

Functionality	Tool Name
Version Control System	Git
Version Control Collaboration	Azure DevOps Repo, Bitbucket
Artifact Management System	JFrog Artifactory, Azure Artifacts

Roles

Name	Responsibilities
Scrum Master/Team Coach	Coach and support usage of version control and artifactory to manage changes
Developer	Adopt version control for all new changes Decouple code and configuration changes
Build Engineer	Integrate automated quality gates and deployment process to promote new version control changes
System Engineer	Create and store infrastructure configurations in version control systems Establish automated infrastructure creation and configuration from the version control
Test Automation Engineer (TAE)	Version control new automated tests and related test data