Identify and eliminate bottlenecks in your application for optimized performance.
Modern DevOps-based application delivery relies on continuous integration/continuous delivery (CI/CD) pipelines as a set of automated processes that allow software changes to be quickly and safely deployed to production. This is typically accomplished by creating and maintaining a master branch of the software that can be rapidly updated and by using automated testing to ensure that changes do not break the software or introduce new bugs.
With the popularity of CI/CD in modern development workflows, there has been an increasing number of platform offerings to help automate code builds and application tests. In this article, we discuss popular CI tools, how they support rapid integration cycles, and their most appropriate use cases.
Simply put, CI is the practice of frequently merging code changes into a shared repository, while CD is the practice of automating build, test, and deployment processes. An essential role of CI/CD tools is to act as an intermediary that transforms build assets into production-ready artifacts. These tools perform automated tests on a shared repository, then build and publish the artifact to be deployed into a workflow.
While a CI tool focuses on automating the process of compiling code changes and merging them into a central repository, a CD tool focuses on automating the process of delivering code changes to production servers. Combined, these tools are essential for the early discovery of performance and security bottlenecks, eliminating quality issues more rapidly than traditional development cycles.
This article will compare the most popular CI tools for modern application development pipelines. We’ll start by examining the key features of each.
Jenkins is a powerful open-source automation server for automated builds and tests. When a Jenkins build server is set up, it typically pulls one or more source code repositories for changes and triggers new builds automatically.
It supports complex build workflows with multiple stages, actions, and conditions. This means that developers can configure Jenkins to automate any aspect of their development process.
Key features of Jenkins for CI include:
Due to its popularity, most tools used in modern CI/CD pipelines have developed plugins for Jenkins CI integration. As a result, Jenkins is supported by an extensive plugin ecosystem that allows it to be extended and customized to fit the needs of any project.
These plugins can be used for a wide range of tasks, including adding new components into the Web UI, enhancing code management, or simplifying Jenkins administration tasks. The community-driven nature of the plugin ecosystem also ensures that there is always someone working on improving and maintaining the plugins.
Jenkins can be installed and run on-premises or used as a cloud-based service. It supports most environments out of the box through native integrations and extensible plugins.
Additionally, the Jenkins server offers multiple installation and deployment options, enabling automated builds on a wide range of hosts.
Jenkins comes with a simple-to-use web UI that enables pipeline deployment, administration, and management using click-based workflows. Besides the ability to view the build progress and inspect server health, the UI also offers a variety of powerful features, such as the ability to trigger jobs based on changes in source code repositories, monitor job execution and view build logs.
Jenkins CI can be run on a single machine, on a dedicated server, or a hosting service. It can be distributed on several workstations and hosts, making it easy to scale and port across different platforms.
Travis CI is a powerful, cloud-based continuous integration tool popular for its single-command operations and multi-environment testing. The tool monitors your code repository for changes and automatically runs the appropriate build, test, and deploy steps for your project. This allows you to focus on writing code and not worry about the management overhead of setting up and maintaining a build server.
In addition, the platform provides features that make it easy to work with multiple branches of code, manage dependencies, and integrate with other popular development tools.
Key features of Travis CI include:
Live build requests are webhooks that are sent to Travis CI from your GitHub repository. These requests trigger a build on the commit that was made and scan the contents of the commit for any changes. If any changes are found, the build is queued and processed. This eliminates the manual process of scanning code and allows you to debug the results of your builds before they are actually completed.
When you create a new branch in your repository, Travis CI automatically creates a new build environment and runs your tests against it. If you want to merge your branch into another upstream branch, you can create a pull request.
It also automatically runs the tests for the target branch of the pull request and reports the results back to you. If all the tests pass, you can merge your changes into the target branch without impacting the existing build.
Travis CI performs auto-deployment and compatibility testing when simultaneously running builds on different machines. This offers developers key insights into the compatibility of their code with various versions of the deployment platform in use. By evaluating whether the code may break when launched on a different platform version, the auto deployment feature essentially ensures constant service availability.
Travis CI comes with pre-installed database services for quick and simple setup, which makes it an ideal tool for testing applications that rely on data from a database. These pre-installed databases can provide a ready-made data store already populated with data, which can be helpful when testing builds against a consistent, known state.
code from the initial idea stage to the final delivery stage. It serves as a central hub for managing and coordinating the different stages of code development—including building, testing, and deployment. Every time a developer changes the codebase, the tool triggers automated tests in a new virtual machine or container. This approach allows each job to be isolated from the others, so if one job fails, it doesn't impact the others.
Since each job can be assigned to a different machine or container, you can also run multiple jobs in parallel. In addition, you can use different versions of software for different jobs and test new versions without affecting existing ones.
Key features of CircleCI include:
CircleCI is one of the few DevOps tools that can help an organization meet SOC 2 Type II compliance standards, thanks to its built-in support for secure environments, secret management, and compliance logging. This compliance with security regulations also means that CircleCI has deployed policies and procedures to audit and investigate the CI pipeline.
CircleCI's API gives you complete control over integrating your CI pipeline with any tool or service. With the API, you can:
In addition, CircleCI’s orbs registry contains numerous shareable packages of CI pipeline configuration that can be reused across projects. You can use private orbs exclusive to your deployment or get one from the official CircleCI, community, or partner orbs. Orbs are easily customizable and can set up common workflows with just a few clicks.
The Insights dashboard provides an overview of your builds, tests, and deployments over time. The overview helps understand how your development process has evolved and for identifying potential areas of improvement.
The time series data displayed in the dashboard can also be customized to show different timeframes and include key information on state and utilization of build processes.
CircleCI provides clean environments for every build, ensuring that every build is isolated from the others. This is typically achieved by running each job on a clean container or virtual machine and then destroying it after executing the pipeline. This isolation is crucial for preventing unexpected side effects and reducing build times.
Clean environments also provide the perfect testing ground for your code and are especially important when working with large projects or with complex dependencies.
GitLab CI is a Git-based continuous integration tool that allows developers to easily create and manage CI pipelines. GitLab CI is great for collaborative workflows that rely on multiple developers to work on the same version of the codebase simultaneously. If any problems arise with a change, they can be quickly identified and fixed before they escalate.
The GitLab CI architecture is designed over a distributed system of workers to parallelize the work across multiple machines. With GitLab CI, you can define runners (pieces of software that run the tasks defined in a YAML file) to automatically run your tests and builds whenever you push code to your repository.
You can also define stages, which are like sequential sections of a pipeline that let you run multiple runners in parallel. This can be an efficient approach to speed up the development process by running tests and builds in parallel.
Key features of GitLab CI include:
A GitLab CI merge train is a special type of branch used to manage concurrent development on the same project. It allows developers to work on different parts of the codebase at the same time and then merge changes back into the master branch when they are ready.
The feature is designed to avoid merge conflicts by automatically merging changes from all branches into a single branch as they are made. This ensures that distributed teams only work on an updated code version and prevents multiple people from working on the same file and making conflicting changes.
The GitLab runner manager can instantiate as many machines as it requires to effectively run the CI pipeline. By using elastic scaling, you can automatically add or remove CI runners as needed. When running multiple pipelines in parallel, the feature ensures that there are enough CI runners available to handle the load, but not too many, to the point of wasting resources.
The test usage visualization feature provides you with an overview of all the tests that have been run in your pipeline, along with detailed information on each individual test—such as what tests are taking the most time and which ones are causing the most failures.
Through the GitLab web UI, developers can also inspect the portions of the code covered by automated tests. This lets developers access data from their chosen test suites, parse the job, and show which lines of the code are covered by the test, allowing them to customize tests for full code coverage.
GitLab Container Registry is a private registry of Docker images that comes integrated with GitLab CI, making it easy to package your applications and run them in any environment.
Being built on top of Docker distribution, the registry offers native compatibility with the Docker API and several other supported platforms. And because it's integrated with GitLab CI, you can easily build and push images from your CI pipelines. This is useful if you want to test your images locally before pushing them to a remote registry.
Bitbucket Pipelines allows developers to implement CI functions by enabling automated tests and builds within the Bitbucket environment. By using Bitbucket’s language-specific templates, you can easily configure your Bitbucket pipeline for powerful CI workflow automation. In addition to automating your workflow, language-specific templates can also help you ensure that your code is consistently formatted and compliant with best practices.
As the platform has a built-in CI runner, you don't need to install and maintain additional software. The runner is isolated from your development environment so there's no need to worry about potential conflicts. This also implies that if you have your own runners in a private cloud or behind organization firewalls, the platform will help provide a unified experience for the entire pipeline without having to jump between multiple solutions.
Bitbucket Pipelines uses Docker containers to execute the steps in your pipeline. This means that each step in your pipeline will run in its own container. This has a number of benefits, including isolation of each step from the others and consistent execution environments for each step.
Key features of Bitbucket Pipelines include:
Bitbucket Pipelines integrates seamlessly with Jira to provide end-to-end visibility of deployment workflow to help track bugs and feature requests. You can define steps that your code will go through every time you push changes. This could include running tests, linting your code, and building binaries. And because Bitbucket integrates with Jira, you can automatically update issues when new code is pushed or when builds fail.
Bitbucket Pipelines provides a straightforward, adaptable tracker for detecting issues alongside deployments for intuitive tracking. The tracker includes multiple configurable fields, including versions and milestones that enable you to pinpoint the code commits at fault. With the built-in issue tracker, you can track the status of vulnerabilities, pull requests, and issues assigned to you.
Bitbucket allows developers to insert threaded conversations and in-line comments into code snippets. The feature improves collaboration between cross-functional teams, making it easy to inspect code changes and get real-time feedback from all stakeholders of the workflow.
Bitbucket implements a rapid code review system by allowing teams to review pull requests as soon as they are committed. You can configure your pipelines to specify when and how often your code should be evaluated. This commit-level evaluation helps developers detect errors early on before they could propagate through the codebase.
GitHub Actions is a powerful tool that enables you to automate your development workflow by triggering events in your codebase and taking specific action. For instance, you can set up an action that will run tests when you push code to your repository. Or, you can configure an action for automated code deployment when it is merged into the master branch.
GitHub Actions operates on the principle that everything is an action—any task that can be performed by your codebase. Actions are triggered by events that happen in your codebase, such as a new commit or creation of a new branch. When an event occurs, all associated actions of the event get executed.
Leveraging the GitHub API, the power of GitHub Actions lies in its flexibility. You can configure actions to perform any task required, from running tests and deploying code to sending notifications and building reports. As actions are triggered by events, they can be easily configured to run automatically, making the development workflow much more efficient.
Key features of GitHub actions include:
The built-in secret store is a simple key/value store that is used to manage secrets for GitHub Actions. The store is backed by the GitHub database and all data is encrypted at rest.
When you create a secret in GitHub Actions, it is encrypted and stored in the GitHub Secrets Store by default. You can store encrypted secrets within the repos settings, and provide them as step inputs or environment variables within the actions. The secrets are only decryptable by the actions that need them.
Live logs enable real-time visualization of events with a single click to pinpoint the specific line of code that has led to a particular outcome. These logs are updated every time a new event occurs and are a key source for debugging or monitoring the progress of your workflow.
Multi-container testing helps test the platform compatibility of complex applications running in different environments. GitHub Actions makes it easy to run multi-container tests by providing pre-built actions for your workflow file.
These actions invoke the required containers and integrate them for seamless communication. Once the containers are started, the workflow runs tests against the defined actions.
Matrix builds allow you to build and test code on multiple platforms simultaneously. With GitHub Actions, you can easily create and manage multiple build configurations and quickly find the one that works best for your project.
The table below compares the popular CI tools of 2023.
|Ease of use
|Pre-installed database services for quick and easy CI
|Relatively steep learning curve
|Web UI for simple administration and visualization
|Easy setup and use
|Supports multiple deployment environments and target platforms
|Managed vs self-hosted
|Self-hosted, private server or cloud hosted
|Distributed architecture for simultaneous builds
|Incremental “stories” to implement code changes
|Jira integration and inline discussion
|Extensive plugin ecosystem
|Restricted integration with third-party limiting flexibility options
|CircleCI API and orbs enable flexibility and extensibility
|GitLab container registry for automated, shared, and customizable workflows
|Integrates with most popular cloud-based CI tools and services for extensibility and flexibility
|Provides matrix builds for tests and builds across different deployment platform versions and operating systems
|Requires a governed CI for enterprise-sized requirements
|Ready and easy to use within a few clicks
|Expert account management and round-the-clock support
|Auto-scaling for production-sized workloads
|Not built for modern microservices
|Suggests workflows based on project details for production pipelines
As each CI tool is built differently and comes with its own strengths and weaknesses, it's important to choose the one that best fits your use case. The following section contains the most appropriate use cases for each of the CI tools described above.
Free for open source projects: This means that anyone can build and test their code without incurring charges.
Easy to set up and use: It integrates seamlessly with GitHub, so you can simply push your code to GitHub, and Travis CI will automatically start building and testing it. There's no need to install any special software or set anything up on your server.
Reliable and fast: It runs your builds in parallel on multiple servers, so you don't have to wait for one build to finish before starting another. And if one build fails, you can fix the problem and push the code again—Travis CI will automatically rerun the build and test it again.
Offers multiple server hosting options and can be configured to run complex pipelines with Docker caching, resource classes, and advanced caching mechanisms
Built for speed and includes filters to sort jobs and pipelines, making it appropriate for teams looking to implement an ordered series of jobs or run a build job on specific branches
Unparalleled iOS support, with dedicated macOS build images that are updated regularly to keep up with the latest Apple operating system releases
Makes it easy to run parallel tests on multiple devices, so you can quickly and easily test your app across a wide range of devices and ensure that it works flawlessly on all of them. This makes it a huge time-saver compared to other CI tools that require you to set up and manage separate build environments for each device type.
Enforces artifact storage and pipeline administration capabilities, making it appropriate for managing updates and releases in modern CI workflows
Highly scalable thanks to its distributed architecture and can handle large projects with ease. The architecture allows developers to easily add more runners to a project without worrying about performance issues.
In this article, we have covered a range of different CI tools that can help streamline the development process. While there is no one-size-fits-all solution, each tool has its own strengths and weaknesses that make it suited for different use cases. By taking the time to evaluate your needs and choose the right tool for the job, you can ensure that your project is set up for success from the start.
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