CI/CD Pipeline Setup From Scratch

Build your first automated deployment pipeline with version control integration, testing stages, and release automation.

15 min read Beginner August 2026

Developer at desk with multiple monitors showing code and system dashboards in a modern office environment

What You’ll Learn

Setting up CI/CD might sound intimidating, but it’s really about automating the boring parts. You’ll understand how your code moves from your laptop to production without manual handoffs.

We’ll walk through the fundamentals. No fancy enterprise tools required — just the core concepts you need to build something real. By the end, you’ll have a working pipeline that catches problems early and deploys faster.

Modern development workflow showing git commits flowing through automated testing and deployment stages in a clean visual diagram

The Pipeline Foundation

A CI/CD pipeline has three main parts working together. Continuous Integration watches your repository. When you push code, it automatically runs tests. If something breaks, you know immediately instead of finding it weeks later in production.

Continuous Delivery keeps everything ready to ship. Your code gets built, tested, and packaged. It’s waiting for approval to go live. Continuous Deployment takes it further — no approval step needed. Push code, tests pass, it goes live automatically.

The key difference: Delivery stops before production. Deployment goes all the way. You’ll pick what works for your team.

Diagram showing three connected stages of CI/CD pipeline with version control, automated testing, and deployment to production servers

Educational Context: Individual learning outcomes vary from person to person. Your specific pipeline needs depend on your team size, deployment frequency, and risk tolerance. Use these fundamentals as a starting point and adjust based on what your organization actually requires.

Getting Started: Version Control

Everything starts with Git. You’re probably already using it — pushing code to GitHub, GitLab, or Bitbucket. Your pipeline watches that repository. When you push a commit, a webhook fires and triggers the pipeline automatically.

Set up a dedicated branch for releases. Don’t run the pipeline on every feature branch — that’s wasteful. You’ll want main branch commits to trigger the full pipeline. Feature branches can run a lighter version that just checks for syntax errors and basic tests.

Enable webhooks in your repository settings

Point webhooks to your CI server URL

Create a pipeline configuration file in your repo

Git workflow showing branches, commits, and webhook triggers flowing into automated pipeline execution

Building Your Testing Stages

Tests are where CI/CD actually provides value. Your pipeline should run three types of tests in sequence. Unit tests go first — they’re fast and catch obvious problems. You’ll run these on every commit because they complete in seconds.

Integration tests come next. They’re slower because they spin up databases and external services. You don’t run these on every commit — maybe once per hour or when merging to main. They check whether your components work together.

Smoke tests run last. These are quick sanity checks in your actual deployment environment. They verify the application started, the database connected, and basic endpoints respond. If anything fails at any stage, the pipeline stops immediately and notifies your team.

Pipeline execution dashboard showing test results with green checkmarks for passed tests and failure notifications

Automating Deployments

Once tests pass, deployment should be automatic or one-click. This is where you move code to staging first. Run your smoke tests there. If everything’s healthy, you’re ready for production.

Start with manual approval for production. Your pipeline prepares everything, then waits for someone to click “deploy.” After a few weeks of smooth deployments, you can make it fully automatic. This confidence only comes from watching it work reliably.

Track deployments carefully. You’ll want to know what version is running where, when it deployed, and who approved it. This becomes crucial when something goes wrong — you can pinpoint exactly what changed.

Production deployment process showing infrastructure provisioning and application release automation across multiple servers

Popular Pipeline Tools

You don’t need enterprise software. Here’s what actually works for small teams starting out.

GitHub Actions

Built into GitHub repositories. Free for public projects, reasonable pricing for private. YAML-based configuration is straightforward once you get the syntax.

GitLab CI/CD

Excellent if you’re already using GitLab. Container-native, which means you can test your Docker images directly in the pipeline.

Jenkins

The workhorse. Open source, mature, tons of plugins. Steeper learning curve but incredibly flexible for complex pipelines.

CircleCI

Cloud-hosted, minimal maintenance. Great if you don’t want to manage servers. Generous free tier for small projects.

Travis CI

Simple and straightforward. Configuration lives in .travis.yml file. Good for projects that don’t need advanced features.

ArgoCD

Kubernetes-native, GitOps approach. Your entire infrastructure lives in Git. Perfect for container-based deployments.

Moving Forward

You now understand the fundamentals. Start simple — hook up version control, add basic tests, deploy to staging. Don’t over-engineer it. Get something working first, then iterate.

Your pipeline will evolve. You’ll add security scanning, performance testing, and deployment approval workflows. But that foundation stays the same. Automate, test, deploy. That’s it.

The real benefit appears after a few weeks. You’ll stop dreading deployments. Your team ships features faster. Bugs get caught before they reach users. That’s when CI/CD becomes invaluable.

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