What is a DevOps Pipeline & How to Build One?

DevOps is a methodology that helps your organization to design, build, and deploy software solutions. Through this practice, you can align resources and processes across every stage of your software development lifestyle.

A DevOps pipeline plays a pivotal role in the success of your DevOps strategy. Implementing it allows you to enhance shared accountability, agility, and productivity among all departments of your organization. Let’s explore a DevOps pipeline in greater depth, learning about its stages, building process, and associated challenges.

What is a DevOps Pipeline?

A DevOps pipeline is a series of automated tools and processes that facilitate collaboration between your organization's development and operations teams. This structured pipeline enables systematic software building, testing, and deployment for various organizational purposes.

The first step in this process is to write and compile code. Then, you must conduct various tests to check for inaccuracies, bugs, and errors and fix them through patches. Additional testing is also required to validate the software's functionality and performance until it is stable and ready for release.

The DevOps pipeline not only accelerates software development but also boosts team communication to address challenges and maintain high-quality standards. This way, you can deliver reliable and innovative software solutions and stay competitive in the long run.

Why Build a DevOps Pipeline?

• Enhanced Efficiency: By building an automated DevOps pipeline, you can streamline repetitive tasks, such as testing code or identifying bugs. Through the removal of manual efforts that may be prone to error, you can free team members and assign them high-priority tasks. It allows them to be more productive and work on innovating solutions.‍
• Quick Resolution Time: Building a pipeline in DevOps helps you reduce delays and maintain a steady momentum for your projects. As several team members collaborate on the pipeline, identifying issues is much quicker, enabling you to deliver solutions faster to the end-users.‍
• Improved Data Consistency: A DevOps pipeline enables you to maintain data quality and integrity. The software solutions are rigorously tested and validated before deployment, helping you gauge potential bottlenecks before they cause data inconsistencies.

DevOps Pipeline Stages

Now that you have understood what is a DevOps pipeline, take a look at the crucial pipeline stages to get a better understanding of the process:

Code Commit

A pipeline in DevOps can only begin when you have defined your project resources, scope of work, and expected outcomes. This will help your organization’s developers understand system requirements and write code accordingly. In this stage, the main focus is compiling and reviewing code, which can be done in version control systems like GitHub. You can also use integrated development environments (IDEs) to detect potential issues and improve workflows.

Build

Once the code is committed to a shared repository, you must integrate it into small deployable containers and run it. You can use automated CI/CD tools like GitLab CI/CD to run integration and unit tests. Here, you will be able to identify and flag code errors and get a chance to resolve them.

Test

Testing is a crucial stage in a DevOps pipeline because, in this stage, you can ensure software reliability and security. Your team must perform various tests to validate the pipeline’s performance under different circumstances. You can even build simulated testing environments or integrate software testing tools to perform essential functional tests.

Artifact

After thorough testing, your DevOps pipeline has to be prepared for deployment. You can include approval stages or automate version releases by using tools like Docker or Kubernetes. Remember to prepare risk mitigation strategies, such as a blue/green deployment, where you can set up two identical production environments but actively work on one only.

Deploy

The deploying stage involves provisioning production environments and ensuring seamless software rollouts. Once the pipeline is deployed, you must maintain infrastructure, scale resources to meet user demands, and make sure that there is minimal downtime.

Monitor

Like all other tools and processes in your organization, a DevOps pipeline must be continuously monitored to gain insights into user preferences. This will allow you to collect relevant data and pass on feedback required to improve the software further and deliver high-quality outcomes.

DevOps Pipeline Architecture Components

Before building a DevOps pipeline to streamline software development, deployment, and operations, it is crucial to learn about the key architectural components:

Continuous Integration

Continuous Integration (CI) involves frequently merging all your code changes into a shared repository to identify and resolve errors. You can work on trunk-based development, where your team of developers merges small but frequent updates to the main trunk or repository of the code. Trunk-based development can be very important because this version control practice assists in the early detection of bugs. By incorporating automated build and test processes to validate changes, you can make continuous integration effective and reliable.

Continuous Delivery

This architectural component of the DevOps pipeline ensures that your main code branch stays ready for deployment at all times. You can automate simulated testing environments where each code update is rigorously checked before releasing the version. Continuous Delivery (CD) enables you to build a quick and easy software release process, ensuring the latest updates go live without delays.

Continuous Testing

With Continuous Testing, you can maintain the quality and reliability of your DevOps pipeline and enforce data governance and privacy laws for your software. You must conduct unit, functional, and regression tests for every block of code and complete end-to-end testing for the entire pipeline. This helps you validate changes, reduce errors, and comply with set standards.

Continuous Monitoring

The Continuous Monitoring component of your DevOps pipeline allows you to track your infrastructure performance in near real-time. By keeping track of your pipeline, you can check if all components function as intended. You can also get critical insights on how to improve development and testing processes, as well as identify bottlenecks and anomalies that can affect the software application.

Continuous Feedback

The final stage in the DevOps pipeline architecture acts as a bridge between all stakeholders and users. Through Continuous Feedback, your teams can gauge whether the pipeline has produced actionable results that meet user demands. You can establish an iterative feedback loop that is committed to refining and improving the DevOps pipeline.

How to Build an Efficient DevOps Pipeline

A well-organized and efficient pipeline provides you with a steady stream of consistent and accurate data that can be used for analysis and decision-making. Whether it is building a data pipeline or a DevOps pipeline, you must carefully consider all requirements, take stock of your resources, and understand the process thoroughly. Here is a consolidation of the critical steps required to build a pipeline in DevOps:

Select a CI/CD Tool

Since CI/CD is a foundational part of the pipeline, selecting the right tool is of utmost importance. These tools automate the process of running tests on code and deploying tested code into production. It not only helps reduce manual effort but also streamlines pipeline workflow and management. You can opt for open-source CI/CD tools like Jenkins or GitLab CI or go with cloud-based ones, such as Azure DevOps.

Choose a Version Control System

Version control management is the practice of tracking and managing all the updates and changes made to your software code. With tools like Git or Bitbucket, you can maintain the version history of pipeline code in a single repository. This gives you a clear picture of all the teams who have collaborated on the project, helping you avoid merge conflicts and establish a clear line of accountability.

Set up a Build Server

A build server, also known as a CI server, enables you to automate the process of integrating and compiling the code. You can get a stable environment to validate the code and conduct various tests. In the server, your team can also check if all features are working correctly and if additional changes are not compromising the performance of the software.

Deploy for Production

Deployment implies releasing the final software version into production. This can be configured manually, which gives you more flexibility over the release, or you can automate the deployment through your CI/CD tool. Automating deployment works best when you already have a mature pipeline that does not require robust testing.

Challenges That May Arise When Building a DevOps Pipeline

While building a pipeline in DevOps may transform your software development process, it can come with a set of challenges. Take a look at some of them:

• Using Legacy Systems: If your organization uses outdated legacy systems, building and deploying your DevOps pipeline will be complex. This can lead to higher operational costs and increased workloads.‍
• Managing Multiple Environments: As your code and applications grow, they require separate environments for development and testing. Mismanagement of these environments can lead to grave errors and disrupt workflows.‍
• Scalability Issues: During continuous testing, you must accommodate growing data volumes and complex test scenarios. Without scalable infrastructure, your organization will struggle to maintain pipeline quality as demand and usage increase.‍
• Lack of Holistic Monitoring: A DevOps pipeline has numerous interconnected components. Usually, each team is dedicated to one component and may work in silos with minimal collaboration. Without comprehensive monitoring, you may not get visibility and clarity for pipeline development, leading to production delays.

Few DevOps Pipeline Tools To Help You

Building and maintaining a pipeline in DevOps requires you to select a tool that fits most of your requirements. Here are some of the well-known DevOps tools that help you automate the process:

• AWS CodeDeploy: AWS CodeDeploy is a fully managed deployment service that allows you to rapidly release new features while avoiding downtime during deployment. It provides you with tools to easily manage and monitor your pipeline progress via the AWS Management Console or AWS CLI. You can also configure push notifications to receive pipeline updates in real-time.‍
• Jenkins: Jenkins is a well-known open-source DevOps automation tool that offers several plugins to help you build, deploy, and automate software projects. It is a self-contained Java-based application and is compatible with a wide range of operating systems, such as Windows, Linux, macOS, and Unix-like platforms. The platform’s user-friendly web interface allows you to access features like real-time error checking and integrated help for setup and configuration.‍
• DeployBot: DeployBot helps you streamline your pipeline deployments by allowing code compilations and executions on its servers through pre-defined or custom Docker containers. You can also run shell scripts on your own servers before, during, and after a DevOps pipeline deployment. DeployBot supports multiple environments and allows you to integrate third-party applications to analyze deployment impacts and results.

How Can Airbyte Help?

Once your DevOps pipeline is up and running, it is essential that you collect and process relevant data from it. However, there are separate functions for extracting and transforming raw data for business reporting and visualization. Instead of building another pipeline to carry out data extraction, you can choose a data movement platform.

‍Airbyte is a robust data integration and replication platform. Using its extensive library of 550+ connectors, you can build a data integration pipeline in just a few minutes. You can also leverage Airbyte’s no-code Connector Builder with its AI-assistant feature or low-code Connector Development Kit (CDK) to build custom connectors.

With Airbyte, you also get the flexibility to design and automate the setup of your custom data pipelines through Terraform. The Airbyte Terraform Provider facilitates easy integration with CI/CD tools and enables you to define and provision data integration infrastructure through code. This way, you can collect data from your DevOps pipeline and use Airbyte to move it into a data warehouse for further processing.

Another way to swiftly connect your DevOps tools with data warehouses and downstream applications is through PyAirbyte. This Airbyte Python environment supports source connectors for some popular DevOps platforms, such as Jenkins, GitHub, and GitLab.

With PyAirbyte, you can not only extract data from your DevOps tools but also maintain version control and transform various sections of your source code. Once you have tested and updated the data, you can directly move the updated data into a PyAirbyte-supported destination. Through this ETL pipeline, you can maintain a steady and consistent data flow from your DevOps pipeline into a central database for quicker analysis and reporting.

Conclusion

This article has given you comprehensive answers to what is a DevOps pipeline, its architectural components, and how to build one. You can leverage popular CI/CD tools that automate several steps during development and production, helping you deploy the pipeline and release the software sooner.