Published: 16 July 2024
Contributors: Chrystal R. China, Michael Goodwin
Continuous integration (CI) is a software development process where developers integrate new code into the code base throughout the development cycle.
When the code is submitted, CI tools verify each integration by creating an iteration of the build and running a battery of automated tests to detect and address integration errors more quickly.
CI was created as a response to the challenges of traditional software development, namely the processes associated with integration and deployment. In traditional development, each developer was responsible for manually integrating new code into new iterations of an app or service, making integration a slow, error-prone process, especially for large development teams.
Different pieces of code didn’t always work well together and developers integrated their changes on different timelines—and sometimes at the last minute—so feedback on integration issues was often delayed. Delays related to inconsistent integrations made it harder for teams to figure out which change introduced the bug, so debugging also became an arduous process.
Furthermore, software testing was infrequent, with large batch updates made all at once, so bugs could slip through the cracks and accumulate in the code base, leading to errors and glitches for end users. (And more difficult troubleshooting for developers.)
CI tools—which are foundational to modern DevOps practices, continuous integration/continuous deployment (CI/CD) pipelines and microservices architectures—help streamline the build process by providing rapid feedback on integration performance.
With a CI system, new code is added to a central repository (typically, multiple times a day), where it remains for building and testing. If the system detects an error, it sends out notifications, corrects the code and confirms that the updated code is correct before fully merging it with the code base.
Consequently, the CI approach enables software development teams to catch and fix errors before they affect software performance, resulting in higher-quality software and more predictable delivery schedules.
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While the exact configuration of a continuous integration system is variable from team to team and business to business, every CI system uses certain components and processes to optimize integration tasks.
CI starts with a central repository where all developers commit their code. Central repositories serve as the cornerstone of CI practices and are often managed by version control systems (VCSs) such as Git and Bitbucket. When developers submit changes, the central repository keeps track of them, creating a complete history of code changes that development teams can use to collaborate more efficiently.
Repositories also use branching strategies, such as trunk-based development or GitFlow, to facilitate parallel development. Branching enables developers to create feature branches and short-lived branches to isolate their work before merging it back into the main code branch.
CI servers, which can be configured to build various projects for different platforms, centralize all CI operations and provide a stable, reliable platform for software development. They model and visualize workflows (for continuous delivery) and provide an intuitive interface for building continuous delivery (CD) pipelines.
CI servers also run automated builds, tests and releases, orchestrate version control protocols, monitor code repositories, handle status reporting and support plug-ins that can enhance system functionality.
CI systems encourage developers to submit code changes several times daily, prioritizing small, focused changes to specific tasks or features. Using tools such as pull requests (description) and merge requests, teams can initiate code reviews and discuss issues before merging new code, so that errors are caught early on.
Continuous integration servers and tools (including popular open-source CI tools like Jenkins, CircleCI, GitHub, AWS CodePipeline and GitLab CI) monitor the central repository for code changes. When they detect a new change, build servers trigger the build process and execute predefined workflows and build scripts, compiling and packaging the code in preparation for testing and ultimately, deployment.
CI tools run a range of tests to validate code before it merges with the code base. Unit tests validate individual components or functions, providing immediate feedback on code behavior. Integration tests assess interactions between software components and modules to make sure they’re working together correctly and to catch any issues unit tests might miss.
In some CI workflows, end-to-end testing validates software by simulating user interactions to verify that the software behaves correctly from a user’s perspective. Teams can also run code quality tests and static analyses to check the application’s responsiveness and stability under load and to identify coding standard violations and security vulnerabilities.
CI servers notify developers immediately if a build or test fails. In the event of a failure, developers prioritize repairing the code to ensure the main branch remains deployable.
If a build is successful, the servers produce artifacts (such as compiled binaries, Docker images and installers) that are versioned and stored in artifact repositories for future testing and deployment. Regardless of the result, leading CI systems will log integration attempts, success rates and other metrics to make sure team members can always access comprehensive version documentation.
Testing is a vital component of continuous integration processes. At a minimum, testing constitutes about a third of CI activities, but that’s only true when teams run a single test stage. In reality, testing activities can make up the majority of the workload for CI tools.
Continuous testing in a CI environment begins when a developer produces a build and a package (also known as an installable entity or a packaged entity) and ends when the package goes into production. Every step, from end to end, comprises the test suite.
As part of the automated testing process in CI, test-driven development iteratively builds code and tests it one use case at a time; and then notifies teams of how the code performed across functional areas of the application.
However, it’s important that developers run all tests—and subsets of tests—in their local environment to ensure that they only commit source code to version control after the new code changes pass their tests. This approach maximizes test coverage, prevents code regression and lays the groundwork for continuous delivery.
In a DevOps framework, continuous integration sits at the beginning of the software development process. DevOps pipelines accelerate the delivery of high-quality software by automating and combining the efforts of development and IT operations teams, which traditionally existed in their own silos.
The best DevOps processes and cultures extend beyond development and operations to include platform and infrastructure engineering, security, compliance, governance, risk management, line-of-business, end-users and customers. In other words, good DevOps should incorporate input from all application stakeholders into the software development lifecycle.
As part of DevOps, CI enables developers to check their code at least once a day to keep local copies from drifting too far away from the main branch of the code build. This approach helps teams avoid disastrous merge conflicts that could "break" the build in the delivery and deployment phases.
Continuous integration is the first stop in the CI/CD pipeline and is typically followed by continuous delivery and continuous deployment processes.
Continuous delivery (CD) picks up where continuous integration leaves off, automating the delivery of applications and validated code base changes (updates, bug fixes and even new features) to all necessary environments for development, testing and ultimately, delivery to end users. CD processes keep the build phase “green,” so that artifacts are ready to deploy at any time.
With continuous deployment (the final phase of DevOps), code changes are automatically released into the production environment and distributed to the end user. At this point, code modifications have passed all the testing protocols and are therefore safe and ready for public use. CI scripts or tools then move the software artifact to public servers or distribution platforms (such as application stores) and push the update to end users.
Continuous integration and agile development have many of the same features, including testing automation, so it can be useful to discuss how the two interact.
Agile is a practice that organizes the development process into smaller groups of work, or “sprints,” to minimize barriers, enable developer collaboration and accelerate software delivery. Agile methodologies recognize that software development practices and customer needs are dynamic, which make them likely to change over time.
As such, agile provides an iterative approach to development that enables teams and businesses to adapt more easily to change and to scale and evolve software solutions over time. And since CI encourages frequent updates and code validation, it also enables agile teams to push high-quality products out even faster, making it an inherently agile practice.
Continuous integration helps DevOps teams rely on a shared repository for coding, testing, deploying and supporting software, but there are some additional steps a business can take to optimize the process. Commonly implemented CI best practices include:
A consolidated, centralized code base can simplify distribution and visibility. Many organizations use source control management to maintain a single repository that tracks and controls all the files associated with a product build.
Organizations can create a culture of consistency by requiring developers to commit their changes to the main development stream at least once a day. This also enables developers to verify that their working copy is consistent with the main development stream.
Optimizing build scripts, parallelizing tasks and using caching mechanisms can reduce build times. Teams can also configure CI pipelines so that new integrations, should they have issues, fail early in the process. This enables developers to address problems quickly and spend less time debugging.
Making the test environment as similar as possible to the final production environment can ensure test results provide an accurate representation of how software will perform in the real world.
Implementing feature flags to control the release of new features enables CI systems to merge incomplete or experimental features into the main branch without affecting overall production.
Periodically reviewing and updating the CI pipeline to incorporate new tools, technologies and best practices enables the pipeline to evolve with a project’s needs.
Setting up a robust CI pipeline—especially as part of DevOps and agile development—requires careful planning and configuration, including choosing the right tools, defining build and test workflows and configuring infrastructure. CI pipelines also require regular maintenance to accommodate changes in the code base, dependencies (such as APIs) and infrastructure.
However, implementing CI can offer software development teams an array of benefits, including:
CI processes enable teams to address errors early—sometimes within minutes of check-in.
Everyone on the team can change code, integrate code changes and identify code incompatibilities and integration errors, simplifying knowledge sharing and improving code and software quality through peer feedback.
Because new code is integrated continuously, teams spend less time integrating and testing large batches of code. And the accelerated feedback loop CI tools offer helps developers iterate and deliver software updates and new products to end users faster.
Frequent code commits mean smaller, more incremental changes that are easier to understand, review and test. This reduces the risk of introducing significant issues into the code base during development.
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