Today, people expect to see their favorite apps with the latest bells and whistles faster than ever. Long gone are the days when developers had years to develop and release new software products.

Hence, every software-development company needs an effective DevOps pipeline to keep up with customer demands and requirements.

devops pipeline flow diagram

This article covers the basic concepts of a DevOps pipeline, how pipelines work in DevOps environments, and explains the stages code has to pass through before being deployed to production.

What is a DevOps Pipeline?

A DevOps pipeline is a set of practices that the development (Dev) and operations (Ops) teams implement to build, test, and deploy software faster and easier. One of the primary purposes of a pipeline is to keep the software development process organized and focused.

The term "pipeline" might be a bit misleading, though. An assembly line in a car factory might be a more appropriate analogy since software development is a continuous cycle.

Before the manufacturer releases the car to the public, it must pass through numerous assembly stages, tests, and quality checks. Workers have to build the chassis, add the motor, wheels, doors, electronics, and a finishing paint job to make it appealing to customers.

DevOps pipelines work similarly.

Before releasing an app or a new feature to users, you first have to write the code. Then, make sure that it does not lead to any fatal errors that might cause the app to crash. Avoiding such a scenario involves running various tests to fish out any bugs, typos, or mistakes. Finally, once everything is working as intended, you can release the code to users.

From this simplified explanation, you can conclude that a DevOps pipeline consists of the build, test, and deploy stages.

Refer to our article DevOps Roles and Responsibilities for more information on how different roles and responsibilities influence the pipeline.

Components of a DevOps Pipeline

To ensure the code moves from one stage to the next seamlessly requires implementing several DevOps strategies and practices. The most important among them are continuous integration and continuous delivery (CI/CD).

Continuous Integration

Continuous integration (CI) is a method of integrating small chunks of code from multiple developers into a shared code repository as often as possible. With a CI strategy, you can automatically test the code for errors without having to wait on other team members to contribute their code.

One of the key benefits of CI is that it helps large teams prevent what is known as integration hell.

In the early days of software development, developers had to wait for a long time to submit their code. That delay significantly increased the risk of code-integration conflicts and the deployment of bad code. As opposed to the old way of doing things, CI encourages developers to submit their code daily. As a result, they can catch errors faster and, ultimately, spend less time fixing them.

At the heart of CI is a central source control system. Its primary purpose is to help teams organize their code, track changes, and enable automated testing.

In a typical CI set-up, whenever a developer pushes new code to the shared code repository, automation kicks in to compile the new and existing code into a build. If the build process fails, developers get an alert which informs them which lines of code need to be reworked.

Making sure only quality code passes through the pipeline is of paramount importance. Therefore, the entire process is repeated every time someone submits new code to the shared repository.

Continuous Delivery

Continuous delivery (CD) is an extension of CI. It involves speeding up the release process by encouraging developers to release code to production in incremental chunks.

Having passed the CI stage, the code build moves to a holding area. At this point in the pipeline, it's up to you to decide whether to push the build to production or hold it for further evaluation.

In a typical DevOps scenario, developers first push their code into a production-like environment to assess how it behaves. However, the new build can also go live right away, and developers can deploy it at any time with a push of a button.

To take full advantage of continuous delivery, deploy code updates as often as possible. The release frequency depends on the workflow, but it's usually daily, weekly, or monthly. Releasing code in smaller chunks is much easier to troubleshoot compared to releasing all changes at once. As a result, you avoid bottlenecks and merge conflicts, thus maintaining a steady, continuous integration pipeline flow.

Continuous Deployment

Continuous delivery and continuous deployment are similar in many ways, but there are critical differences between the two.

While continuous delivery enables development teams to deploy software, features, and code updates manually, continuous deployment is all about automating the entire release cycle.

At the continuous deployment stage, code updates are released automatically to the end-user without any manual interventions. However, implementing an automated release strategy can be dangerous. If it fails to mitigate all errors detected along the way, bad code will get deployed to production. In the worst-case scenario, this may cause the application to break or users to experience downtime.

Automated deployments should only be used when releasing minor code updates. In case something goes wrong, you can roll back the changes without causing the app to malfunction.

To leverage the full potential of continuous deployment involves having robust testing frameworks that ensure the new code is truly error-free and ready to be immediately deployed to production.

Continuous Testing

Continuous testing is a practice of running tests as often as possible at every stage of the development process to detect issues before reaching the production environment. Implementing a continuous testing strategy allows quick evaluation of the business risks of specific release candidates in the delivery pipeline.

The scope of testing should cover both functional and non-functional tests. This includes running unit, system, integration, and tests that deal with security and performance aspects of an app and server infrastructure.

Continuous testing encompasses a broader sense of quality control that includes risk assessment and compliance with internal policies.

Discover DevSecOps - the combination of cybersecurity best practices and DevOps principles to enhance DevOps security.

Continuous Operations

Having a comprehensive continuous operations strategy helps maintain maximum availability of apps and environments. The goal is for users to be unaware that of constantly releasing code updates, bug fixes, and patches. A continuous operations strategy can help prevent downtime and availability issues during code release.

To reap the benefits of continuous operations, you need to have a robust automation and orchestration architecture that can handle continuous performance monitoring of servers, databases, containers, networks, services, and applications.

Phases of DevOps Pipeline

There are no fixed rules as to how you should structure the pipeline. DevOps teams add and remove certain stages depending on their specific workflows. Still, four core stages make up almost every pipeline: developbuildtest, and deploy.

different Phases of DevOps Pipeline

That set-up can be extended by adding two more stages - plan and monitor - since they are also quite common in professional DevOps environments.


The planning stage involves planning out the entire workflow before developers start coding. In this stage, product managers and project managers play an essential role. It's their job to create a development roadmap that will guide the whole team along the process.

After gathering feedback and relevant information from users and stakeholders, the work is broken down into a list of tasks. By segmenting the project into smaller, manageable chunks, teams can deliver results faster, resolve issues on the spot, and adapt to sudden changes easier.

In a DevOps environment, teams work in sprints - a shorter period of time (usually two weeks long) during which individual team members work on their assigned tasks.


In the Develop stage, developers start coding. Depending on the programming language, developers install on their local machines appropriate IDEs (Python IDEs, Java IDEs, etc), code editors, and other technologies for achieving maximum productivity.

In most cases, developers have to follow certain coding styles and standards to ensure a uniform coding pattern. This makes it easier for any team member to read and understand the code.

When developers are ready to submit their code, they make a pull request to the shared source code repository. Team members can then manually review the newly submitted code and merge it with the master branch by approving the initial pull request.


The build phase of a DevOps pipeline is crucial because it allows developers to detect errors in the code before they make their way down the pipeline and cause a major disaster.

After the newly written code has been merged with the shared repository, developers run a series of automated tests. In a typical scenario, the pull request initiates an automated process that compiles the code into a build - a deployable package or an executable.

Keep in mind that some programming languages don't need to be compiled. For example, applications written in Java and C need to be compiled to run, while those written in PHP and Python do not.

If there is a problem with the code, the build fails, and the developer is notified of the issues. If that happens, the initial pull request also fails.

Developers repeat this process every time they submit to the shared repository to ensure only error-free code continues down the pipeline.


If the build is successful, it moves to the testing phase. There, developers run manual and automated tests to validate the integrity of the code further.

In most cases, a User Acceptance Test is performed. People interact with the app as the end-user to determine if the code requires additional changes before sending it to production. At this stage, it's also common to perform security, performance, and load testing.


When the build reaches the Deploy stage, the software is ready to be pushed to production. An automated deployment method is used if the code only needs minor changes. However, if the application has gone through a major overhaul, the build is first deployed to a production-like environment to monitor how the newly added code will behave.

Implementing a blue-green deployment strategy is also common when releasing significant updates.

A blue-green deployment means having two identical production environments where one environment hosts the current application while the other hosts the updated version. To release the changes to the end-user, developers can simply forward all requests to the appropriate servers. If there are problems, developers can simply revert to the previous production environment without causing service disruptions.


At this final stage in the DevOps pipeline, operations teams are hard at work continuously monitoring the infrastructure, systems, and applications to make sure everything is running smoothly. They collect valuable data from logs, analytics, and monitoring systems as well as feedback from users to uncover any performance issues.

Feedback gathered at the Monitor stage is used to improve the overall efficiency of the DevOps pipeline. It's good practice to tweak the pipeline after each release cycle to eliminate potential bottlenecks or other issues that might hinder productivity.

How to Create a DevOps Pipeline

Now that you have a better understanding of what a DevOps pipeline is and how it works let's explore the steps required when creating a CI/CD pipeline.

Set Up a Source Control Environment

Before you and the team start building and deploying code, decide where to store the source code. GitHub is by far the most popular code-hosting website. GitLab and BitBucket are powerful alternatives.

To start using GitHub, open a free account, and create a shared repository. To push code to GitHub, first install Git on the local machine. Once you finish writing the code, push it to the shared source code repository. If multiple developers are working on the same project, other team members usually manually review the new code before merging it with the master branch.

If you are new to Git, check out our Git Commands List article with a free downloadable Cheat Sheet.

Set Up a Build Server

Once the code is on GitHub, the next step is to test it. Running tests against the code helps prevent errors, bugs, or typos from being deployed to users.

Numerous tests can determine if the code is production-ready. Deciding which analyses to run depends on the scope of the project and the programming languages used to run the app.

Two of the most popular solutions for creating builds are Jenkins and Travis-CI. Jenkins is completely free and open-source, while Travis-CI is a hosted solution that is also free but only for open-source projects.

To start running tests, install Jenkins on a server and connect it to the GitHub repository. You can then configure Jenkins to run every time changes are made to the code in the shared repository. It compiles the code and creates a build. During the build process, Jenkins automatically alerts if it encounters any issues.

Run Automated Tests

There are numerous tests, but the most common are unit testsintegration tests, and functional tests.

Depending on the development environment, it's best to arrange automated tests to run one after the other. Usually, you want to run the shortest tests at the beginning of the testing process.

For example, you would run unit tests before functional tests since they usually take more time to complete. If the build passes the testing phase with flying colors, you can deploy the code to production or a production-like environment for further evaluation.

Deploy to Production

Before deploying the code to production, first set up the server infrastructure. For instance, for deploying a web app, you need to install a web server like Apache. Assuming the app will be running in the cloud, you'll most likely deploy it to a virtual machine.

For apps that require the full processing potential of the physical hardware, you can deploy to dedicated servers or bare metal cloud servers.

There are two ways to deploy an app - manually or automatically. At first, it is best to deploy code manually to get a feel for the deployment process. Later, automation can speed up the process, but only if you are confident, there are barriers that will stop bad code from ending up in production.

Releasing code to production is a straightforward process. The easiest way to deploy is by configuring the build server to execute a script that automatically releases the code to production.

In Closing

Now you understand what a devops pipeline is and how it can help speed up your software development life cycle.

However, this is just the tip of the iceberg.

The DevOps pipeline is a broad subject, and every organization will have its way of integrating one into their workflows. The ultimate goal is to create a repeatable system that takes advantage of automation and enables continuous improvements to help deliver high-quality products faster and easier.