CI/CD: From Code Commit to Production

In the world of modern software delivery, speed and reliability are everything. Users expect features to roll out fast — without downtime or drama. That’s where CI/CD comes in.

In this blog, we’ll break down what CI/CD really is, how it powers DevOps, and walk through a real example so you can see it in action.

What is CI/CD?

CI/CD stands for:

• Continuous Integration (CI) – Automating the build and test process every time code is committed.
• Continuous Delivery (CD) – Automating the release of that tested code to staging or production.

In simple terms:

You commit code → It’s built and tested → If successful, it’s deployed automatically

This approach avoids the nightmare of last-minute integration hell, ensures bugs are caught early, and allows teams to ship smaller, safer changes more frequently.

Benefits of CI/CD

• Faster deployments: Shipping becomes routine, not a big event.
• Improved quality: Automated testing catches issues early.
• Shorter feedback loops: Stakeholders see progress faster.
• Reduced risk: Small, incremental changes are easier to roll back.

Typical CI/CD Flow

Here’s a high-level look at what happens in a CI/CD pipeline:

1. Developer pushes code to a Git repository
2. CI pipeline triggers:

• Runs tests
• Lints code
• Builds artifacts (e.g., a Docker image or compiled binary)
  1. If all steps pass, CD pipeline triggers:
• Deploys to staging environment
• Optionally runs automated integration tests
• Promotes to production

Tools Involved in CI/CD

Depending on your stack, you might use:

• Source Control: GitHub, Azure Repos, GitLab
• CI/CD Engines: Azure Pipelines, GitHub Actions, GitLab CI, Jenkins
• Artifacts: Azure Artifacts, GitHub Packages, JFrog Artifactory
• Environments: Azure App Service, AKS, App Center, etc.

In our upcoming blogs, we’ll focus on Azure Pipelines and GitHub Actions.

Example: CI/CD for a Node.js App Using Azure Pipelines

Let’s say you have a simple Node.js app in a Git repo. You want every push to the main branch to:

• Install dependencies
• Run unit tests
• Build the app
• Deploy to Azure App Service (if all goes well)

Here’s what a basic YAML pipeline could look like:

trigger:
  branches:
    include:
      - main

pool:
  vmImage: 'ubuntu-latest'

steps:
  - task: NodeTool@0
    inputs:
      versionSpec: '18.x'
    displayName: 'Use Node.js'

  - script: |
      npm install
      npm run test
    displayName: 'Install and Test'

  - script: npm run build
    displayName: 'Build Application'

  - task: AzureWebApp@1
    inputs:
      azureSubscription: 'Your-Service-Connection-Name'
      appName: 'your-app-service-name'
      package: '$(System.DefaultWorkingDirectory)/**/*.zip'
    displayName: 'Deploy to Azure'

This is a minimal setup. Real-world pipelines often include linting, code coverage checks, approval gates, infrastructure provisioning, and rollback mechanisms.

Best Practices

• Keep builds fast — under 10 minutes ideally
• Fail fast: stop pipeline early if a key step fails
• Store pipeline definitions in code (YAML, not UI)
• Use secrets for credentials (never hardcode passwords or tokens)
• Protect production branches with approvals or checks