Trunk-Based Development
Integrating work frequently to reduce risk, shorten feedback loops, and make change safer in complex systems.
What is this practice?
Trunk-based development is a way of working where changes are integrated into a shared codebase frequently, rather than being developed in long-lived branches. The practice emphasizes small, incremental changes and rapid feedback to reduce the risk that comes from delayed integration.
Instead of treating integration as a separate phase, integration becomes a routine part of daily work.
Why does this matter in this transformation?
During a cloud migration, systems, environments, and assumptions change continuously. Long-lived branches can hide integration problems until late in the process, when they are harder to diagnose and more expensive to resolve.
This practice supports the transformation by making integration a habit. It allows teams to adapt incrementally as systems evolve, rather than accumulating hidden risk that surfaces all at once.
What does “good” look like?
When trunk-based development is working well, teams integrate changes frequently and conflicts are small and manageable. Builds and tests provide fast feedback, and integration rarely feels dramatic or risky.
Over time, integration becomes routine rather than stressful, and problems are discovered close to when they are introduced.
What gets in the way?
Common challenges include fear of breaking shared code, insufficient automated testing, unclear ownership, and organizational pressure to batch work. Teams may also misunderstand the practice as encouraging reckless change rather than disciplined integration.
Without supporting practices, frequent integration can feel unsafe instead of stabilizing.
How might someone begin?
Teams often start by shortening branch lifetimes, integrating at least once per day, or limiting how much work is allowed to accumulate before merging. Feature flags or similar techniques can help decouple deployment from exposure, making small integrations safer.
Beginning with small, low-risk experiments tends to be more effective than attempting to change everything at once.
Explore deeper with your AI assistant
Use your AI assistant to reason through this practice in your own context.
Prompt:
I’m exploring the practice of trunk-based development in the context of a cloud migration and broader organizational change.
Help me reason through this practice by:
- explaining it in plain language without assuming specific tools or frameworks
- highlighting the tradeoffs and tensions it introduces
- describing what “good” tends to look like in real teams
- calling out common failure modes or misunderstandings
- suggesting small, low-risk ways teams often begin experimenting
- articulating who are the vendor-neutral thought leaders in the space
Please keep the discussion exploratory and context-aware rather than prescriptive.