Trunk-Based Development

Trunk-Based Development organizes development around one shared integration branch, commonly named main. Developers integrate small changes frequently, usually at least daily, rather than maintaining isolated feature branches for weeks. Teams may commit directly to the trunk or use short-lived branches with lightweight pull requests. The defining characteristic is frequent integration into the shared codebase, not the absence of branches or code review.

Every integration should trigger continuous integration checks. These commonly include compilation, unit tests, static analysis, dependency checks, and selected integration tests. Branch protection can require successful checks and review before merging. Because concurrent changes can interact, the pipeline should also validate the resulting trunk revision after merge. When the trunk fails, restoring it becomes a priority: revert the offending change or deliver a small corrective commit rather than allowing failures to accumulate.

In a cloud delivery workflow, connect the repository to a pipeline and configure its source events to recognize changes to the trunk. Pull-request validation can run separately without deploying unmerged code into shared production environments. A successful trunk build produces a versioned artifact associated with the exact source commit. Promote that same artifact through development, testing, staging, and production instead of rebuilding it separately for each environment. For container workloads, an immutable image digest provides a precise artifact identity.

Application environments do not require corresponding long-lived Git branches. A staging branch and a production branch that continually diverge create additional integration work and can obscure which code was actually tested. Prefer environment-specific deployment configuration, infrastructure parameters, and separately managed secrets. Use pipeline approvals and automated quality gates to control promotion. Trunk-Based Development does not require every merged commit to reach production immediately; continuous delivery can retain an explicit production approval.

For example, a team introducing a new checkout flow can merge its implementation incrementally behind a feature flag. The pipeline tests the code and deploys the artifact to a test account, then promotes it to production after validation. The feature remains disabled until it is ready for users. Flags separate code deployment from feature release, but disabled code still requires testing, and obsolete flags should be removed. Database changes should preserve compatibility during rollout, often by adding a new schema element before migrating consumers and later removing the old element.

The trade-off is a stronger dependency on fast, trustworthy tests, small change sizes, and disciplined collaboration. Slow approvals or unreliable checks encourage branches to live longer and undermine the model. Short-lived release branches can support exceptional maintenance needs, but fixes should also reach the trunk to prevent divergence. For certification scenarios, distinguish this strategy from workflows centered on long-lived development, release, or environment branches: the key signals are frequent integration, a healthy shared mainline, and traceable artifact promotion across environments.