CI/CD (Continuous Integration/Continuous Deployment) represents a set of automated practices that enable development teams to deliver code changes more frequently and reliably. Continuous Integration focuses on merging code changes into a shared repository multiple times per day, with automated builds and tests validating each integration. Continuous Deployment extends this by automatically releasing validated changes to production, while Continuous Delivery stops at staging, requiring manual approval for production deployment.
The core value of CI/CD lies in reducing integration risk, catching bugs early, and accelerating feedback loops. By automating repetitive tasks like building, testing, and deploying, teams can focus on feature development while maintaining high quality standards and rapid release cadence.
Pipeline Stages
Build: Compile source code, resolve dependencies, and package artifacts. This stage transforms code into deployable units and runs static analysis or linting.
Test: Execute automated tests including unit tests, integration tests, and end-to-end tests. Testing ensures code changes don’t introduce regressions and meet quality gates.
Deploy: Automatically or semi-automatically release artifacts to target environments. Deployment strategies include blue-green deployments, canary releases, and rolling updates to minimize downtime and risk.
Best Practices
Effective CI/CD pipelines are fast (providing feedback within minutes), reliable (consistent results), and secure (handling credentials safely). Pipelines should be version-controlled alongside application code, follow the principle of failing fast, and provide clear visibility into deployment status and history.
Tooling Ecosystem
Popular CI/CD platforms include GitHub Actions, Azure DevOps Pipelines, GitLab CI/CD, Jenkins, CircleCI, and TeamCity. Modern platforms increasingly support declarative pipeline definitions (pipeline-as-code), container-based builds, and integration with cloud providers and Kubernetes.
Related Topics
CI/CD is central to DevOps practices and often integrates with Infrastructure as Code, GitOps, Kubernetes, and Automation workflows. It supports Platform Engineering by enabling self-service deployment capabilities and golden paths.