Implementing a CI/CD Pipeline Step by Step

A CI/CD pipeline is an automated sequence of stages that carries every code change from a commit in the repository all the way to a running production environment. Implementing one turns manual, error-prone integrations and deployments into a repeatable, verifiable process — code reaches users faster and, at the same time, more safely, because every change passes through the same automated quality gates. This guide walks through the implementation step by step: from the first build, through test automation, to deployment strategies and metrics.

What CI/CD and a pipeline are

CI/CD stands for Continuous Integration and Continuous Delivery (or Deployment) — a set of practices that automate the integration, verification, and deployment of software. A pipeline is the concrete implementation of those practices: a sequence of stages defined as code, which the CI/CD system runs automatically on a specific event, most often a push to the repository or the opening of a pull request.

The heart of a pipeline is the gate principle. Every stage must complete successfully for the change to move on. If regression tests detect a broken feature or a scanner finds a critical vulnerability, the pipeline stops and the change never reaches production. This shifts problem detection as far left as possible — to the moment when the fix is cheapest, because the context of the change is still fresh in the developer’s mind. We described the broader picture of good practices in the article CI/CD — best practices, and you’ll find term definitions in the glossary: CI/CD (glossary) and CI/CD pipeline (glossary).

CI vs CD vs Continuous Deployment

These three concepts are often confused, yet the difference between them is practical and significant.

Continuous Integration (CI) is the practice of frequently merging changes into a shared branch — ideally several times a day. Every integration automatically triggers a build and tests. The goal of CI is the early detection of conflicts and regressions before they grow into a hard-to-solve problem.

Continuous Delivery (CD) extends CI so that every change that has passed all tests is automatically prepared for deployment. The artifact is built, tested, and ready. The release to production, however, requires a deliberate human decision — clicking the “deploy” button.

Continuous Deployment is the final step: every change that passes all gates reaches production automatically, without manual approval. This demands the highest process maturity — without complete test coverage and solid monitoring, automated deployment to production is risky.

Most organizations should aim for Continuous Delivery as the target state and introduce Continuous Deployment selectively, where trust in the pipeline is highest.

Pipeline stages: build, test, scan, artifact, deploy

A well-designed pipeline has distinct, clearly defined stages. The order is not arbitrary — it follows the principle of fast feedback and the rising cost of successive steps.

Build. The first stage compiles the code and installs dependencies. It should be fast and deterministic — the same commit always produces the same result. If the build fails, there is no point in running the rest.

Test. The heart of the pipeline. This is where unit tests run (the fastest, earliest), then integration tests, regression tests, and finally E2E. Regression tests are especially important, because they protect against the silent breaking of already-working features when new changes are introduced — a topic we expand on in the article on regression testing. We described the details of integrating tests with the pipeline in the guide integrating tests with CI/CD.

Scan. The security and quality stage: static code analysis (SAST), scanning dependencies for known vulnerabilities (SCA), and scanning container images. This is the moment when a vulnerability is caught before it reaches production.

Artifact. Building an immutable, versioned artifact — a container image, package, or binary. The key principle: build the artifact once and promote the same file through subsequent environments. You don’t build separately for test and separately for production, because that introduces the risk of drift.

Deploy. Rolling the artifact out to successive environments — from test, through staging, to production — with smoke tests after each step.

Implementation step by step

A pipeline is built iteratively, not all at once. Here is a proven implementation order.

Step 1: Repository and branching strategy. The starting point is a repository with a clear branching strategy (e.g., trunk-based or GitHub Flow). Without orderly work on branches, automation will fight chaos instead of bringing order to it.

Step 2: The first automated build. Configure a single build triggered on every push. At this stage the goal is repeatability itself — every change should build automatically, without manual steps.

Step 3: Test automation. Add unit tests to the build, then regression and integration tests. Set up a gate: failing tests block the merge. This is the moment when the pipeline stops being just a build and becomes a quality pipeline.

Step 4: Security scanning. Wire in SAST and dependency scanning. At the start, set thresholds sensibly — overly aggressive gates early on will discourage the team and lead to controls being bypassed.

Step 5: Artifact and automated deploy to test. Build a versioned artifact and deploy it automatically to a test environment, with smoke tests confirming that the application came up.

Step 6: Promotion to staging and production. Add further environments, initially with manual approval before production (Continuous Delivery). Introduce automated deployment to production only once trust in the pipeline is well established.

We described practical configuration patterns in the guide CI/CD pipeline configuration.

Tools

The choice of tool matters less than the discipline of the process, but it’s worth knowing the landscape. GitLab CI is an integrated solution in which the pipeline is defined in a .gitlab-ci.yml file next to the code, with the repository, CI/CD, and artifact registry all in one place. GitHub Actions is based on workflows in the .github/workflows directory and has a rich ecosystem of ready-made actions — a natural choice for teams already on GitHub. Jenkins is the veteran, self-hosted and maximally flexible thanks to its huge base of plugins, but requiring more maintenance.

In practice, modern pipelines are defined as code (pipeline as code), versioned together with the application. Regardless of the tool, the key is that the pipeline configuration lives in the repository, is subject to code review, and is repeatable.

Deployment strategies: blue-green and canary

The way the artifact reaches production determines the risk. The two most important strategies for limiting that risk are blue-green and canary.

Blue-green deployment maintains two identical production environments. One (blue) serves traffic, the other (green) is updated to the new version. After verification, traffic switches to green in a single move. If something goes wrong, the rollback is an instant switch back to blue. The advantage: zero downtime and instant rollback. The cost: duplicating infrastructure.

Canary deployment releases the new version first to a small portion of users (e.g., 5%), monitors error and performance metrics, and then gradually increases the share until it reaches 100%. If metrics deteriorate, the deployment is paused and rolled back before it affects the majority of users. Canary limits the reach of a potential problem and is a natural complement to solid monitoring.

The choice depends on context: blue-green works well for simple wholesale switches, canary — when you want to validate a change against real traffic while minimizing the blast radius.

Pipeline security

A pipeline has privileged access — to code, secrets, and production environments — so it becomes a target of attack itself. A few principles are indispensable.

Secrets management. Passwords, API keys, and tokens never belong in the code or in the pipeline configuration in plaintext. Use dedicated secret stores and inject them into the pipeline at runtime, with the narrowest possible scope and the shortest possible lifetime.

Scanning in the pipeline. SAST, dependency scanning (SCA), and container image scanning should be permanent gates, not a one-off audit. A vulnerability in a third-party library is one of the most common vectors today.

Principle of least privilege. Pipeline runners and service accounts should have only the permissions they actually need. Separate credentials per environment limit the impact of a potential leak.

Immutability and auditability. Artifacts and logs from pipeline runs should be immutable and retained, so that it’s possible to reconstruct what was deployed, when, and by whom. This is the DevSecOps philosophy — security built into the process, not bolted on at the end.

DORA metrics

To know whether implementing the pipeline actually improves delivery, you have to measure it. The standard is the four DORA metrics (DevOps Research and Assessment):

• Deployment Frequency — how often you deploy to production. A higher frequency, with quality maintained, indicates a more mature process.
• Lead Time for Changes — the time from commit to the change running in production. Shortening this time is a direct effect of an efficient pipeline.
• Change Failure Rate — the percentage of deployments that cause a failure requiring a fix or rollback. It measures quality, not just speed.
• Mean Time to Recovery (MTTR) — how quickly you return to working order after an incident. This is exactly where blue-green and canary pay off.

The first two metrics describe pace, the next two — stability. A healthy pipeline improves all four simultaneously; if only frequency rises, and the Change Failure Rate rises with it, that’s a signal that the quality gates are too weak.

The most common mistakes

CI/CD implementations stumble on recurring pitfalls. It’s worth knowing them before you fall into them.

• A slow pipeline. When feedback takes tens of minutes, the team stops waiting and bypasses the process. Make sure the fast path (build + unit tests) fits within a few minutes.
• Flaky tests. Tests that pass one time and fail the next destroy trust in the gates. As a result, people ignore red results. Fix flaky tests aggressively instead of weakening the criteria.
• Building the artifact separately for each environment. This introduces drift between what was tested and what was deployed. Build once, promote the same artifact.
• Secrets in configuration. Keys embedded in the pipeline file are a leak waiting to happen.
• No rollback strategy. A pipeline that can only deploy forward leaves the team with no way out in the event of a failure. The rollback must be tested, not hypothetical.
• Building everything at once. Trying to stand up a complete, multi-stage pipeline in a single pass ends in a fragile, incomprehensible construction. Add stages iteratively.

How ARDURA Consulting supports DevOps and CI/CD

Implementing a mature CI/CD pipeline is not a one-off project but a competency that the team needs on board day to day. ARDURA Consulting supports companies with a staff augmentation model — we provide experienced DevOps engineers who join your team and work on your stack, processes, and goals.

This is a partnership approach, not a sales one: our specialists build the pipeline together with your people, transferring knowledge instead of creating dependence on an external vendor. We have a team of 500+ seniors, onboarding an engineer takes 2 weeks on average, and the model maintains 99% retention — which translates into continuity and stability of the collaboration. We have 211+ projects delivered in this model behind us.

If you’re planning a CI/CD implementation from scratch, the modernization of an existing pipeline, or you need to strengthen your team with DevOps competencies — check out ARDURA Consulting’s software development services and let’s talk about how to tailor the support to your context. Get in touch with us to discuss which engineer profile you need and how quickly they can join your team.