What is a CI/CD Pipeline? Tools, Benefits, and an Example

The CI/CD pipeline, short for "continuous integration and continuous deployment (or delivery) pipeline," is a specialized practice for automating the delivery of new software versions to users throughout the development lifecycle.

In simple terms, the CI/CD pipeline automates delivering software updates to users incrementally rather than dividing the product into distinct versions that require long waits between releases. Instead, updates are delivered gradually with each iteration of the codebase. While the stages of development, testing, deployment, and release can be done manually, the true value of the CI/CD pipeline lies in automation.

Diving Deeper into CI/CD

As modern user applications (like taxi services, food delivery, or rental platforms) become central to many companies, the speed of code releases (or app updates) has become a competitive advantage. To enable the fastest possible delivery of a digital product, two core components are essential:

1. Continuous Integration (CI). Developers frequently merge changes into the main branch, using a version control system (such as Git).All changes undergo automated testing, improving the product incrementally rather than in large, disruptive updates. Imagine a development timeline as a line with update points spaced evenly along it, showing consistent progress rather than sudden, clustered changes.

2. Continuous Deployment (CD). This further extends continuous integration by automatically deploying new code changes to the production environment after the build stage. The aim is clear: to reduce developer workload, minimize human error, and maintain a steady release process.

Tools within the CI/CD pipeline may include code compilers, analyzers, unit tests, data security systems, and a variety of other components useful at all stages of product release.

It’s worth noting that CI/CD is the foundation of DevOps methodology, which automates software build, configuration, and deployment. This approach promotes close collaboration between development and operations teams, effectively integrating their workflows and fostering a culture of streamlined product creation and support.

Frequent, incremental code testing reduces the number of errors and bugs, providing users with the best possible experience. Iterative software development and delivery also accelerate the product’s return on investment and make it easier to create a Minimum Viable Product (MVP). As a result, development costs are reduced, and hypotheses can be tested quickly.

Writing small sections of code alongside automated tests also lessens the cognitive load on developers. Yes, each pipeline stage follows a strict sequence: development comes first, with deployment to the production environment at the end. Testing happens in the later stages, while static code analysis occurs earlier. Notification systems often operate between stages, sending status updates about the pipeline to messaging platforms or email.

Most importantly, the entire process runs automatically. Depending on the specific tool and developer's needs, the pipeline can be triggered with a console command or a timer.

CI/CD Tools

Many popular Git repository hosting platforms offer comprehensive systems with scripts or full interfaces to streamline CI/CD processes, such as GitHub CI/CD, GitLab CI/CD, and Bitbucket CI/CD. Other tools include Jenkins CI/CD, AWS CI/CD, and Azure DevOps CI/CD. Each has unique features, so the choice of tool often comes down to preference, though each option has its own pros and cons. Here are a few tools designed explicitly for organizing CI/CD pipelines:

• Jenkins is a free, open-source software environment (set up as a server) built specifically for continuous integration. Written in Java, Jenkins runs on Windows, macOS, and other Unix-like operating systems.

• CircleCI is a CI/CD tool delivered as a web service, enabling complete pipeline automation from code creation to testing and deployment. It integrates with GitHub, GitHub Enterprise, and Bitbucket, triggering builds whenever new code is committed to the repository. Builds run using containers or virtual machines, with automatic parallelization of the pipeline across multiple threads. CircleCI is a paid service, but it has a free option with a single job without parallelization. Open-source projects can receive three additional free containers.

• TeamCity is a build management and continuous integration server from JetBrains geared toward DevOps teams. It runs in a Java environment and integrates with Visual Studio and IDEs. TeamCity can be installed on both Windows and Linux servers and supports .NET projects.

• Bamboo is a continuous integration server that automates application release management. Developed by Atlassian, Bamboo covers the entire process from build, functional testing, and versioning to release tagging, deployment, and activation of new versions in the production environment.

Stages of CI/CD

The stages of a CI/CD pipeline can vary depending on the product and the specific development team. Still, there is a generally standard sequence of actions that nearly every pipeline follows. Some stages can be skipped or done manually, but this is considered poor practice. Typically, a pipeline can be outlined in seven main steps:

1. Trigger. The pipeline should start automatically whenever new code is committed to the repository. There are multiple ways to achieve this. For example, a CI/CD tool (such as Jenkins) may "poll" the Git repository, or a "hook" (like Git Webhooks) could send a push notification to the CI/CD tool whenever a developer pushes new code. While manual triggers are possible, automated triggers reduce human error and provide greater reliability.

2. Code Verification. The CI/CD tool pulls the code from the repository (via a hook or poll), along with details on which commit triggered the pipeline and the steps to be executed. At this stage, static code analysis tools may run to detect errors, halting the pipeline if any issues are found. If everything checks out, the CI/CD process moves forward.

3. Code Compilation. The CI/CD tool must have access to all necessary build tools for code compilation. For instance, tools like Maven or Gradle might be used for Java applications. Ideally, the build should occur in a clean environment; Docker containers are often used for this purpose.

4. Unit Testing. A critical part of the pipeline, unit testing involves running specialized libraries for each programming language to test the compiled application. If tests are completed successfully, the pipeline proceeds to the next step. Comprehensive test coverage is essential to ensure all functions and components are tested. Tests should be updated and improved as the codebase grows.

5. Packaging. Once all tests have passed, the application is packaged into a final "build" for delivery. For Java code, this might be a JAR file, while for Dockerized applications, a Docker image may be created.

6. Acceptance Testing. This stage verifies that the software meets all specified requirements, either client-specific or based on the developer’s own standards. Acceptance tests, like unit tests, are automated. Requirements and expected outcomes are specified in a format that the system can interpret, allowing them to be automatically tested repeatedly. For example, using a tool like Selenium, functional aspects of the application can be tested, such as verifying whether a user can add a product to a cart on an e-commerce site. Acceptance testing saves time by automating what would otherwise be manual tests.

7. Delivery and Deployment. At this final stage, the product is ready to be deployed to the client’s production environment. For continuous deployment, a production environment is necessary. This might be a public cloud with its own API or a tool like Spinnaker, which integrates with Kubernetes for container orchestration and works with popular cloud providers such as Google Cloud Platform, AWS, Microsoft Azure, and Oracle Cloud.

This is the endpoint of the pipeline. The next time a developer commits new code to the repository, the process will begin again.

CI/CD in Practice

Typically, when adding a new feature to a product, a separate branch is created in the version control system (such as Git). Code is written in this branch and tested locally. Once the feature is ready, the developer makes a pull request and asks a senior colleague to review the code before merging it into the main branch. Then, the updated codebase is deployed to the dev environment. All of this is done manually.

If you spend 25 hours on development and 2 hours on deployment, that’s a reasonable ratio. However, if you spend 20 minutes creating a feature and 2 hours deploying it, that’s a problem—your time isn’t being used efficiently.

At this point, you have two options:

1. Commit changes to the main branch less frequently, building up larger pull requests. However, reviewing large chunks of code is more challenging.

2. Set up a CI/CD pipeline to automate building, testing, and deployment.

With the second approach, the process is strictly standardized—any feature only makes it into the final product (main branch) once it has passed through every stage of the pipeline, with no exceptions.

Although this article isn’t intended to teach any specific CI/CD tool, let’s look at a simple example using GitLab CI/CD to illustrate how a pipeline is set up in practice.

Imagine you already have a GitLab repository with project code and want to automate the build and deployment process. In GitLab, automated processes are handled by the GitLab Runner—a standalone virtual machine that executes pipeline jobs.

The runners are programmed using YAML scripts containing detailed instructions for GitLab CI/CD. In this file, you define:

• The structure and sequence of jobs the runner should execute
• Branch-based conditions for decision-making during pipeline execution

Here is a basic example of such a file:

build-job:
  stage: build
  script:
    - echo "Hello, $GITLAB_USER_LOGIN!"

test-job1:
  stage: test
  script:
    - echo "This job tests something"

test-job2:
  stage: test
  script:
    - echo "This job tests something, but takes more time than test-job1."
    - echo "After the echo commands complete, it runs the sleep command for 20 seconds"
    - echo "which simulates a test that runs 20 seconds longer than test-job1"
    - sleep 20

deploy-prod:
  stage: deploy
  script:
    - echo "This job deploys something from the $CI_COMMIT_BRANCH branch."
  environment: production

This pipeline contains four jobs: build-job, test-job1, test-job2, and deploy-prod. Everything after echo outputs messages to the GitLab UI console. GitLab provides predefined variables like $GITLAB_USER_LOGIN and $CI_COMMIT_BRANCH, which can be used to display information in the console.

Of course, this pipeline doesn’t perform any actual operations—it only outputs messages to the console. It’s meant to illustrate how to structure a pipeline format.  This example has three stages: build, test, and deploy, with two jobs executed in the test stage. GitLab’s UI also offers a visual view of the script’s content.

^{Image source: docs.gitlab.com}

As with any CI/CD tool, GitLab has its own documentation, which includes many useful examples and specific guidelines for working with this service. GitHub, for example, offers something similar. Some developers may find it convenient to use a CI/CD tool provided by the same platform hosting their repository, which can simplify the setup.

A Few Tips for CI/CD

• Version control not only your product’s codebase but also the scripts that define your CI/CD pipeline.
• Follow the correct sequence of pipeline stages. If you deploy to production before testing, you risk issues.
• Don’t skip stages in the pipeline, even if it’s tempting. All stages should be executed in sequence. If you have hundreds of tests but a few are blocking the pipeline, fix or remove the problematic tests instead of bypassing them.
• Avoid manual intervention! Each stage of the pipeline should trigger automatically; otherwise, the DevOps methodology loses its impact.
• Set up notifications to regularly update you on the CI/CD pipeline status throughout the build, testing, and deployment processes. For example, these notifications could be sent to your messenger app.

Conclusion

This article has covered some general principles of the DevOps methodology, which is grounded in CI/CD pipelines. We looked at several popular tools and services used to automate continuous integration and deployment. While CI/CD tools share many core features, each has unique characteristics. Anyone planning to adopt a DevOps approach in their development processes will need time to get familiar with each tool, understand its nuances, and select the right one.