Database development & CI/CD
Schema as code, automated tests, and pipelines that ship database changes as confidently as application code.
- Schema in source control with SSDT or migrations-based tooling
- Automated unit and integration tests with tSQLt
- GitHub Actions / Bamboo / Bitbucket pipelines for build, test, deploy
- Drift detection and environment promotion strategy
- Code review standards and templates the team can adopt
When you need this
Database changes ship in Word documents, hot-fix scripts, or Slack messages. Environments drift. A schema change broke prod last quarter and nobody can reconstruct the timeline. You want database deploys to look like application deploys — reviewed, tested, repeatable, reversible.
What’s included
- Source-of-truth model. Set up SSDT (state-based, DACPAC) or a migrations-based approach — whichever fits your team’s workflow and toolchain.
- Pipeline. Build the database on every PR, run tests against an ephemeral instance, and gate deploys behind reviewable artifacts — using GitHub Actions, Atlassian Bamboo, or Bitbucket Pipelines.
- Testing. Unit tests for stored procedures and functions with tSQLt, and integration tests for cross-object behavior. Realistic, anonymised test data.
- Promotion & drift. A defined path from dev → test → staging → prod, with drift detection so reality stays in sync with the repo.
- Standards. Code review checklist, naming conventions, and templates so the team can keep up the quality after I leave.
Typical engagement
A working pipeline plus a tested first deploy usually takes three to six weeks, depending on the size of the schema and how much existing tooling there is. I prefer to leave the team able to extend it themselves.
Deliverables
- Schema repo wired to your CI of choice (GitHub Actions, Bamboo, or Bitbucket Pipelines)
- Test framework, sample tests, and a short author’s guide
- Deployment runbook and drift report
Sound like a fit?
First 30 minutes are free.