How to Set Up a CI/CD Pipeline Without a Dedicated DevOps Team

How to Set Up a CI/CD Pipeline Without a Dedicated DevOps Team

Continuous integration and continuous deployment (CI/CD) is one of the highest-leverage investments a development team can make. Teams with mature CI/CD pipelines deploy code more frequently, with significantly lower change failure rates, and recover from incidents faster than teams without them. The DORA research that established these findings is one of the most cited bodies of evidence in software engineering.

The perception that CI/CD requires a dedicated DevOps team to implement and maintain is inaccurate. Modern cloud platforms have made it possible for a small development team to set up a reliable deployment pipeline in days rather than months.

What CI/CD Actually Does

Continuous Integration (CI) automatically runs tests, static analysis, and other quality checks every time a developer pushes code. If the checks pass, the code is safe to merge. If they fail, the developer is notified immediately, before the broken code reaches the main branch or any deployed environment.

The value of CI is that it catches integration problems — when two developers' changes conflict, when a new change breaks an existing test, when static analysis identifies a security issue — immediately after the code is written, when the fix is cheapest.

Continuous Deployment (CD) automatically deploys code that has passed CI checks to one or more environments. In a typical setup: every push to a development branch deploys to a staging environment. Every merge to the main branch deploys to production.

The value of CD is that deployment becomes a boring, routine event rather than a high-risk, high-effort manual process. Small changes deploy frequently instead of large batches of changes deploying infrequently. Small deployments are easier to debug when something goes wrong.

What You Need Before Setting Up a Pipeline

CI/CD amplifies existing engineering practices. Before investing in pipeline infrastructure, you need:

A version control workflow. The pipeline needs to know when to run. Most teams use feature branches: developers work on feature branches, open pull requests to the main branch, and CI runs on pull request creation and update. CD runs on merge to main. Without a defined branching strategy, the pipeline has no clear trigger points.

Some tests. CI's primary value is running tests. A CI pipeline with no tests provides build automation but not quality assurance. You do not need comprehensive test coverage to start — even 20 percent coverage provides immediate feedback on the most critical paths.

A deployment mechanism. CD needs a way to deploy. This might be a script that pushes to a cloud provider, a Docker image to a container registry, or a serverless function deployment. Define what "deploy" means before automating it.

Choosing a CI/CD Platform

The ecosystem of CI/CD platforms has consolidated significantly. For most teams without a dedicated DevOps function, the choice is usually between:

GitHub Actions. If your code is on GitHub, GitHub Actions is the natural choice. It is integrated into the same platform where your code lives, has an extensive library of pre-built actions (steps that handle common tasks like setting up a Node environment or deploying to AWS), and has a generous free tier for public repositories.

GitLab CI/CD. For teams on GitLab, the built-in CI/CD is mature and capable. Similar integration benefits to GitHub Actions.

Bitbucket Pipelines. For teams on Bitbucket (common in teams that use Jira and Confluence). Less ecosystem support than GitHub Actions but fully capable.

CircleCI / BuildKite. More configurable than the platform-native options, appropriate for teams with more complex pipeline requirements. Slightly steeper learning curve.

For a team getting started, choose the platform that integrates with your version control. GitHub Actions if you are on GitHub, GitLab CI if on GitLab. The learning curve for a second platform is not justified by the marginal capability difference at this stage.

A Basic Pipeline in GitHub Actions

A minimal but useful GitHub Actions workflow for a Node.js application:

This pipeline: runs on every push and pull request, installs dependencies, runs tests, and deploys to production only when tests pass and the push is to the main branch.

The deployment step depends on your hosting platform. Most major platforms (Vercel, Railway, Heroku, AWS Elastic Beanstalk, Render) provide GitHub Actions integrations that make the deployment step a single action call.

What to Add Beyond the Basics

Once a basic pipeline is running reliably, additions that provide the most value:

Static code analysis. Tools like ESLint (JavaScript), Ruff (Python), or SonarCloud catch code quality issues and common bugs before review. Runs in CI, fails the build if there are issues above a defined threshold.

Security scanning. Tools like Snyk or GitHub's native Dependabot audit your dependency tree for known vulnerabilities and open pull requests when fixes are available. SAST (Static Application Security Testing) tools like Semgrep identify security issues in your application code.

Environment-specific deployments. A staging environment that receives every merge to a develop branch, with production receiving only after a release review. This provides a pre-production test environment without requiring manual deployment.

Deployment notifications. A Slack or Teams notification when a deployment succeeds or fails, with a link to the deployment log. Eliminates the "did that deploy go out yet?" question.

Caching of dependencies. Adding dependency caching reduces pipeline runtime from several minutes to under a minute for teams with large dependency trees. GitHub Actions provides built-in caching that is configured with two lines.

Common CI/CD Pitfalls

Flaky tests. Tests that pass and fail non-deterministically are CI's worst enemy. A pipeline that fails 20 percent of the time for reasons unrelated to the code being tested teaches developers to ignore pipeline failures. Fix or delete flaky tests; do not work around them by re-running pipelines.

Pipelines that take too long. A CI pipeline that takes 30 minutes discourages frequent pushes. Target under 10 minutes for a complete CI run. Parallelise test suites, cache dependencies aggressively, and remove slow tests that are not providing proportionate value.

Deploying to production without a staging environment. The pattern of "CI passes, deploy to production" skips the manual verification that catches issues automated tests do not. At minimum, have a staging environment that mirrors production and receives code before production does.

No rollback mechanism. Every deployment pipeline needs an answer to "what happens if this deployment breaks production?" The answer should be: one command or one button that reverts to the previous working version. Without it, a broken deployment that cannot be rolled back quickly is a prolonged incident.

The platform engineering guide covers how CI/CD fits into the broader internal developer platform as your engineering organisation grows. The DevOps for startups guide covers the infrastructure decisions around the pipeline itself.

If you want help setting up a reliable CI/CD pipeline for your application, our DevOps team has set up deployment pipelines for dozens of applications across the technology stack. Contact us to discuss your current setup and what you want to achieve.