AI-Native Software Delivery

Chapter 2. Source Control Management

Imagine a scenario where you and your team are collaborating on a complex software project. Multiple minds are contributing, making revisions and enhancements. Without a clear system for managing changes, you risk overwriting each other’s work and losing track of who updated what and why they made those changes. Without a clear system to tag sets of changes, you are unable to navigate back to a previous stable version of your team’s code should an issue arise. Without defined workflows and structured access control, anyone can change anything at any time, with no oversight. Without controls, your team is unable to determine which code files were used to build a particular release should you need to recreate it.

Next, imagine that several teams have worked for months on a new application and it is now nearing time to deploy to your production environment. Ad hoc fixes and tweaks have been made to various development and QA environments, but those have not been reliably reflected in the production environment. Important production settings have not been repeated in QA environments, and development environments vary widely. Given the increasing complexity of the required environments, spinning up new environments has become a time-consuming and error-prone bottleneck that creates frustration and delay.

These situations are recipes for dysfunction and wasted effort. Source control management (SCM) practices were created to address these very problems. ...