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 on its own.
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. The goal is always 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.