Continuous Integration and Continuous Delivery (CI/CD)
Practices and methods for automated integration, testing and deployment of software via pipelines. CI/CD shortens feedback loops, increases release consistency and enables repeatable deployments.
Classification
- ComplexityMedium
- Impact areaOrganizational
- Decision typeOrganizational
- Organizational maturityIntermediate
Technical context
Principles & goals
Use cases & scenarios
Compromises
- Insufficient test coverage leads to faulty releases
- Pipeline complexity can cause maintenance issues
- Misconfigured rollouts can cause production outages
- Keep pipelines small and modular
- Version pipeline definitions together with code
- Prioritize fast, deterministic tests for CI
I/O & resources
- Source code repositories and branching strategy
- Automated tests (unit, integration, e2e)
- Pipeline definitions, secrets and deployment configs
- Build artifacts and container images
- Test and quality reports
- Deployments with rollback capability and audit log
Description
CI/CD encompasses practices and automation mechanisms for continuous integration, testing and delivery of software. The goal is short feedback loops, reliable releases and reproducible deployments via automated pipelines. Implementations include build and test automation, artifact management, rollback strategies and Canary/Blue-Green deployments.
✔Benefits
- Faster feedback loops and reduced release risk
- Higher consistency and reproducibility of deployments
- Scalable release processes and improved collaboration between dev and ops
✖Limitations
- Initial effort for pipeline creation and maintenance
- Not all legacy systems can be integrated without refactoring
- Requires investment in test automation and infrastructure
Trade-offs
Metrics
- Lead Time for Changes
Time from commit to production deployment. Low values indicate efficient pipelines.
- Deployment Frequency
How often deployments occur to production. Indicates delivery agility.
- Change Failure Rate
Share of failed releases requiring rollback or hotfixes. Low values signal stability.
Examples & implementations
GitHub Actions for CI/CD automation
A team uses GitHub Actions for build, test and release pipelines including deployment to staging and production.
GitLab CI in a microservice architecture
GitLab CI orchestrates independent pipelines per service with a shared artifact repository and deployment triggers.
Jenkins pipelines for legacy automation
Jenkins was used to automate existing build and release processes and to modernize them incrementally.
Implementation steps
Analyze existing build and release processes
Define lean pipeline stages (build, test, release)
Introduce versioning and artifact repository
Automate tests and quality gates
Roll out incrementally to staging and production
Measure, observe and continuously optimize
⚠️ Technical debt & bottlenecks
Technical debt
- Outdated scripts without modularization
- Missing test partitioning causing long runtimes
- Manual steps preventing automation
Known bottlenecks
Misuse examples
- Deploying without automated tests directly enables production changes
- Using pipeline as a substitute for missing architecture or design decisions
- Over-automating non-value-adding steps
Typical traps
- Ignoring slow or unstable tests
- Relying too much on incomplete metrics
- Unclear responsibilities for pipeline maintenance
Required skills
Architectural drivers
Constraints
- • Legacy systems without automation interfaces
- • Limited infrastructure resources for parallel builds
- • Regulatory requirements and audit obligations