This trace follows a change from a Git commit to production. A deployment pipeline can automate steps, but the team still needs to define what evidence is sufficient to advance or stop a release.
1. Identify the change
The pipeline checks out a specific commit and records its identity. Review and branch protections can establish that the change was inspected, but they do not replace tests or production monitoring.
2. Verify and build
The pipeline runs formatting, static analysis, unit and integration checks, then creates a deployable artifact. Pin dependencies and record build inputs so the artifact can be reproduced or investigated. Identify the result with a version or digest rather than a mutable tag alone.
3. Release with a controlled exposure
The deployment system starts the new version using a rolling, canary, or blue-green strategy. Health checks determine whether instances are eligible for traffic; they should test the behavior users depend on, not only whether a process exists.
4. Decide from signals
Compare error rate, latency, saturation, and key product behavior against a baseline. If guardrails fail, stop promotion and use a rollback or forward fix. Check data migrations and external side effects: reverting application binaries does not automatically undo schema or business changes.
The Pro Git book explains commit identity and history; release criteria should be specific to the service and its risk.