What is CI/CD and How Does It Work?

What is CI/CD and How Does It Work?


Continuous integration (CI) and continuous delivery (CD), also called CI/CD, is the culture, operating principle and a set of techniques that developers of applications utilize to make changes to code more frequently and with greater consistency.

CI/CD is an ideal method for teams working in DevOps. It’s also an excellent method to use in agile methodologies. Through the automation of the integration and delivery process, CI/CD lets software development teams concentrate on meeting the business needs while also ensuring code quality and security of software.

CI/CD defined

Continuous integration is a coding philosophy and set of practices that encourage development teams to regularly make minor changes to their code and check them to the repository of version control. Modern applications often require the development of code on different tools and platforms, which is why teams need a standard process to verify and integrate modifications. Continuous integration provides an automated process to develop, package, and test the application. A consistent method for integration allows developers to commit changes to code more frequently, resulting in better collaboration and code quality.

Continuous delivery picks up where continuous integration stops and automates the delivery of applications to specific environments, including production, development and test environments. Continuous delivery is an automated method to push code changes to these environments.

Automating the CI/CD pipeline

CI/CD tools assist in storing specific parameters for each environment that must be included with every delivery. The automation of CI/CD makes required service calls to databases, web servers and other systems which require restarting. It also performs additional procedures after the deployment.

Since the goal is to provide high-quality applications and code, CI/CD also requires continuous testing. Continuous testing is a set of automated regression, performance, and other tests are executed in the CI/CD pipeline

A mature DevOps team with the ability to build a solid CI/CD pipeline could also deploy continuous deployment, in which application modifications are made via the CI/CD process, and subsequent builds are delivered directly onto the production system. Some teams using continuous deployment choose to deploy daily or even daily to production, even though continuous deployment is not the best option for all business applications.

Companies implement CI/CD pipeline typically use various DevOps practices, such as  microservices development, serverless architecture, continuous testing, infrastructure as code, and deployment containers. These practices increase process automation and enhance the reliability of cloud-based computing systems. Together, they provide the foundation for continuous deployment.

How continuous integration helps improve collaboration and code quality

Continuous integration is a development philosophy supported through process mechanics and automation. Continuous integration is a method by which developers regularly put their code in the version control repository. Most teams have a standard of committing code at least daily. This is because it’s easier to detect problems and other software quality issues with smaller code variations than large ones created over a longer period. Furthermore, for the developers who have shorter commit times, there is less chance that multiple developers will modify the same code and need the merging process when they commit.

Teams implementing continuous integration begin with the version control configuration and practice definitions. Although checking code is often done, agile teams create improvements and features at short and long intervals. Developers teams who practice continuous integration employ various methods to ensure that features and codes are ready to be released for production.

Many teams employ feature flags to switch features and code on or off when running. Features in development are wrapped in feature flags inside the code, then deployed by the main branch, and then moved to production and turned off when they are ready to use. A recent study that DevOps teams used feature flags saw an increase of ninefold in development frequency. Features flagging tools such as CloudBees, Optimizely Rollouts, and LaunchDarkly are integrated with CI/CD tools to allow features-specific configurations.

Automated build

When you build an automated process, all software, database, and other components are integrated into one package. For instance, if we were working on a Java application, continuous integration would include every static web server file, such as HTML, CSS, and JavaScript, together with the Java application and database scripts.

Continuous integration does not just include the entire database and software components. Still, it will perform tests for units and other kinds of tests. Testing is crucial to inform developers that their changes aren’t breaking anything.

Most CI/CD tools allow developers to start builds at any time when code commits are made within the repository for version control or based on a set timetable. Teams should choose the best build schedule that is most suitable with the number of people on their team, the number of daily commits to be expected, and other considerations for the application. It is best to ensure that commits and builds are quick; otherwise, the processes could hinder teams trying to code fast and commit often.

Continuous testing and security automation

Automated testing frameworks assist quality assurance engineers in defining, implementing, and automating various kinds of tests. These tests can help development teams determine if software build passes or fails. They also include functional tests developed at the end of each cycle and rolled to create a regression test for the whole application. The regression test tells the team if a code modification failed one or more of the tests designed within the functional aspects of the application, where there is coverage for tests.

The best way to go about it is to allow developers to test all or a portion of regression tests within their environments. This ensures that developers only commit their code to version control once code modifications have been tested for regression.

Regression tests are only the beginning. DevOps teams also automatize the performance, API browser, device and testing. Teams can now integrate static code analysis and security testing within the CI/CD pipeline to perform shift-left testing. Agile teams also can test the interaction with APIs from third parties, SaaS and other systems that are not under their control with the virtualization of services. The key is to initiate these tests using commands, webhook or Web service and then receive an answer of either success or failure.

Continuous testing means the CI/CD pipeline is integrated with testing automation. Some functional and unit tests may flag potential issues before and during continuous integration. Testing that requires a complete delivery environment, for example, security and performance tests, are usually included in continuous delivery and are completed when a build has been delivered to the intended settings.

Stages in the continuous delivery pipeline

Continuous delivery is an automated process that pushes applications into at least one delivery environment. The development teams usually have multiple environments to test and review modifications for testing and reviewing. DevOps engineer utilizes a CI/CD tool like Jenkins, CircleCI, AWS CodeBuild, Azure DevOps, Atlassian Bamboo Argo CD, Buddy, Drone, and Travis CI to automate the process and also provide reports.

For instance, Jenkins users define their pipelines in a Jenkinsfile which describes various stages such as build, testing and deployment. Environment variables such as options such as secret keys, certificates and many other parameters are defined in the file and later are referenced in the various stages. The post section deals with errors and issues.

The typical pipeline for continuous deployment consists of the build, test, and deploy phases. The following tasks can be carried out at various stages:

  • Retrieving code from version control and performing a build.
  • Enabling stage gates to automated security and quality and compliance inspections and supporting approvals as needed.
  • Implementing any necessary infrastructure tasks that can be automated as code to build or demolish cloud infrastructure.
  • Transferring code to the desired computer environment.
  • Configuring environment variables and managing them to suit the specific environment.
  • Connecting components of an application to their appropriate services, like APIs, web servers and databases services.
  • Perform any steps to restart services or call the service endpoints required for new code pushes.
  • Conducting continuous tests and rolling rollback environments in case tests fail.
  • Notifying the user of logs and notifications regarding the status of delivery.
  • Update the configuration management database and send out alerts for IT Service Management workflows upon successful deployment

A more advanced continuous delivery pipeline could include additional steps like storing data, synchronizing data resources, or patching software and libraries.

Teams that use continuous deployment to ensure they deliver to production can employ various cutover methods to reduce downtime and deployment risk. One option is configuring canary deployments using an orchestrated traffic shift from the older version of the software to the more recent version.

Tools and plugins for CI/CD

Tools for CI/CD typically have the market of plugins. For instance, Jenkins lists more than 1 800 plugins which allow connectivity with other platforms, user interface administration, source code management, and building administration.

When the team for development has chosen a CI/CD tool is to ensure that all variables in the environment are set outside of the application. The CI/CD tools enable developers to define these variables, mask variables like passwords and keys to accounts and then configure them before installation for the environment they are targeting.

Continuous delivery tools also offer the ability to report dashboard functions improved when DevOps teams adopt visible pipelines for CI/CD. Developers are notified when a delivery or build is unsuccessful. Reporting and dashboard functions work with the tools for version control and agile to aid developers in determining which modifications to the code and user stories comprised the development.

CI/CD with Kubernetes and serverless architectures

Many teams that run CI/CD pipelines in cloud environments also use containers, such as Docker and orchestration tools like Kubernetes. Containers allow for packaging and shipping services in a normal and portable manner. Containers allow you to increase or demolish environments with varying workloads.

There are various ways to use containers, infrastructure as code (IaC) and CI/CD pipelines together. Free tutorials like Kubernetes in conjunction with Jenkins and Kubernetes using Azure DevOps can assist you in exploring the options.

Another option is to utilize servers to run and scale up your applications. In a serverless system, a cloud service provider handles the infrastructure and applications and consumes resources as required based on its configuration. On AWS, for instance, serverless apps operate in the form of Lambda processes and deployments are integrated into the Jenkins C/C pipeline by using an extension. Azure Serverless and Google GPS for serverless computer systems are two similar services.

Next-generation CI/CD applications

You might be thinking about the most advanced areas of CI/CD pipeline management and development. Here are a few of the most notable sites:

  • MLOps is the IaC and CI/CD model for machine learning and provides infrastructure, integration and deployment in production and training environments.
  • The synthetic data generation techniques use machine learning to generate data sets that engineers use in test automation to test APIs, and Data scientists use them to build models.
  • AIOps platforms, machine learning and automation in IT Ops collect observability data and correlates alerts from a various source into the incident. Automations can trigger deployments of CI/CD and rollbacks when needed.
  • Teams that work on microservices design pipelines that can be reused to support and scale the development process and review options on Azure and AWS.
  • Engineers utilize CI/CD in various areas, such as embedded systems, network configuration, database changes, IoT and AR/VR.


To summarize, continuous integration programs test software builds and inform developers when their modifications fail unit tests. Continuous delivery refers to the process that provides services, applications, and other technologies to the runtime infrastructure and could also execute additional tests.

Creating a CI/CD pipeline has become an everyday practice for companies that frequently upgrade their apps and demand a stable delivery system. Once it is in place, the CI/CD pipeline allows the team to concentrate more on developing applications rather than the specifics of delivering them to different environments.

Beginning with CI/CD requires DevOps teams to cooperate on using technologies, practices and priorities. Teams must agree on the best method for their company and technology. Once a pipeline has been put in position, teams must be consistent with CI/CD processes.

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