Practice : Deployment Pipelines

Purpose and Strategic Importance

Deployment pipelines are the automated paths that take code from development to production. They orchestrate building, testing, packaging, deploying, and verifying software - enabling teams to release with confidence, speed, and reduced risk.

By automating and codifying the delivery process, deployment pipelines ensure that software moves through consistent, repeatable, and observable stages. This accelerates time to value, improves quality, and builds trust in every release.

Description of the Practice

  • A deployment pipeline consists of sequential stages (e.g. build, test, deploy, verify) triggered on code change.
  • Each stage is automated and includes validations (e.g. unit tests, integration tests, security scans).
  • Pipelines promote artefacts between environments (e.g. dev → staging → production).
  • Deployments are tracked, observable, and reversible.
  • All pipeline definitions are stored in source control and evolve with the codebase.

How to Practise It (Playbook)

1. Getting Started

  • Choose a CI/CD toolchain (e.g. GitHub Actions, GitLab, Azure DevOps, CircleCI).
  • Define a basic pipeline with at least: build, lint, unit test, and deploy to a test environment.
  • Use environment variables and secrets management to secure credentials.
  • Store pipeline configuration as code in the repository.

2. Scaling and Maturing

  • Add automated gates: security scans, integration tests, smoke tests, contract tests.
  • Promote artefacts through gated environments (dev, staging, prod) using the same binaries.
  • Make rollback part of the pipeline with a clearly defined fallback process.
  • Integrate notifications and dashboards for pipeline status, failures, and deployment outcomes.
  • Version the pipeline alongside the application, and continuously evolve it with the product.

3. Team Behaviours to Encourage

  • Treat the pipeline as part of the system - code, monitor, and improve it regularly.
  • Include pipeline improvements in backlog grooming and retros.
  • Encourage pair programming or knowledge sharing around pipeline changes.
  • Investigate failures collaboratively and improve the feedback loop.

4. Watch Out For…

  • Manual steps that break the automation chain and introduce human error.
  • Long pipeline runtimes that slow feedback and delay releases.
  • “Snowflake” pipelines that differ across services and teams without good reason.
  • Poor visibility - make pipelines observable, not hidden scripts.

5. Signals of Success

  • Pipelines deliver working software to production with minimal human intervention.
  • Feedback is received within minutes of a commit.
  • Releases are predictable, safe, and reversible.
  • All changes go through a consistent delivery path.
  • Teams treat pipeline reliability and speed as part of product quality.