CI/CD (Continuous Integration & Delivery)
CI/CD stands for Continuous Integration and Continuous Delivery (or Continuous Deployment). It describes a software development practice where code changes are automatically built, tested, and delivered to production environments via Deployment . CI/CD pipelines reduce manual errors, shorten release cycles, and are indispensable for organizations with regular updates.
What is the difference between CI, CD, and Continuous Deployment?
Continuous Integration (CI): developers integrate code into a shared repository multiple times per day. Each integration automatically triggers a Build-Prozess and test run. Continuous Delivery (CD): every successful build is deployable — deployment to production happens manually at the push of a button. Continuous Deployment: goes one step further — every successful build is automatically delivered to production. Most web projects use Continuous Delivery with controlled release management.
Why is CI/CD essential for web projects?
Without CI/CD, deployments become risky manual processes. Bugs are discovered late, releases are delayed, and code quality declines as the team grows. A CI/CD pipeline automates linting, unit tests, integration tests, security scans, and Deployment in a reproducible sequence. Combined with Monitoring , a closed feedback loop from code to production is established.
Structure of a typical CI/CD pipeline
A pipeline consists of stages: 1. Source: code is pulled from the repository (Git push/merge). 2. Build: the application is compiled, dependencies installed, assets bundled. 3. Test: unit tests, linting, type checking, security audit. 4. Deploy to Staging: automatic deployment to a test environment. 5. Deploy to Production: deployment to the production environment after approval. Tools: GitHub Actions, GitLab CI, Jenkins, CircleCI. Containerisierung with Docker ensures consistent build environments across all stages.
Common CI/CD implementation mistakes
Hardcoding secrets in pipeline configurations instead of injecting them via Secret Management . Skipping tests to speed up builds. No staging environment before production. Missing rollback strategies. Not versioning build artifacts. Ignoring branch protection rules also allows unreviewed code to enter the pipeline.
How we use it
Our GitHub Actions pipeline builds Angular with prerendering, runs linting and type checks, and deploys via FTP to Apache — all on a self-hosted runner. For Django backends, a separate job runs with Containerisierung in Docker. FTP credentials and API keys are stored exclusively in encrypted GitHub Secrets. Through Monitoring of pipeline runtimes, we detect regressions in the Build-Prozess immediately.