The past decade has witnessed the most technological advancement in every industry, especially in terms of the digital world. As the world now uses some type of software in day-to-day life, it is essential to reduce the overall software development lifecycle and reduce human efforts in doing so. And with that goal, Azure DevOps came into existence. Developed by Microsoft, Azure DevOps is an overall package that offers tons of useful services to enhance the overall development lifecycle of software or an application. Legions of organizations have already implemented Azure DevOps in their culture to reduce the development time without compromising the code quality.
Azure DevOps comes with several features including Azure Boards, Test Plans, Repos, Artifacts and Pipeline.
For more info visit Azure DevOps Documentation.
What is Azure DevOps Pipeline?
Many people believe that automation is the future and this is exactly what Azure DevOps Pipeline is all about. It is a set of automated processes that developers can use to create and deploy codes to computation platforms. The idea is that every time there is human intervention in a process, the probability of mistakes or issues will always exist. Being a continuous delivery tool based on automation processes, its primary goal is to eradicate or minimize human intervention in projects that will automatically reduce the possibility of errors. Not only that, but the tasks achieved through the Azure DevOps pipeline are accurate, seamless, and faster as well.
Continuous Intergration (CI)
Continuous integration (CI) is the practice of automating the integration of code changes from multiple contributors into a single software project. It’s a primary DevOps best practice, allowing developers to frequently merge code changes into a central repository where builds and tests then run. Automated tools are used to assert the new code’s correctness before integration.
A source code version control system is the crux of the CI process. The version control system is also supplemented with other checks like automated code quality tests, syntax style review tools, and more.
Continuous Delivery (CD)
Continuous delivery is all about boosting the delivery process and making sure that every policy is followed, each test is performed effectively, and code is deployed in the right environment. Moreover, it integrates the code with infrastructure and assists the developers in fixing bugs, making essential changes in the code, and adding new features as well. With all these actions, CD ensures that bug fixes are delivered faster, and the overall risk related to release is reduced to a maximum extent so that software delivery can become faster and more feasible.
Components of Azure DevOps Pipeline
There are certain components that make up an Azure DevOps pipeline and comprehending them is essential to ensure its smooth implementation and attain effective outcome. With that in mind, here are the different components of the Azure DevOps pipeline.
An Azure DevOps pipeline artifact is a collection of packages published by build pipelines that allow the team to assort the dependencies for the development of the application. In most cases, these artifacts are available to desired tasks.
Whenever a developer runs a build or deployment, their system commences single or multiple jobs. An agent will run one job at a single time as it is equipped with agent software and is entirely a computing infrastructure. To make its management easier, these agents can be grouped into agent pools, eradicating the need of managing each agent separately.
A library is like storage or safe for your variable groups and secure files. Azure DevOps pipeline variable groups have secrets and store values that you want to include in the YAML pipeline or several other pipelines. On the other hand, a secure file is a method of storing files that can be shared to multiple pipelines. Storing variable groups and secure files will allow you to gain access to them whenever you want.
Continuous delivery is an integral component of the Azure DevOps pipeline where code is created, tested, and deployed in a test and production stage. Running tests on a single code but in multiple test and production stages helps in reducing errors and enhancing the overall code quality.
Sometimes, code testing can be complicated for the team. Continuous integration helps the team in simplifying not just testing but building the code as well. By performing automated tests on the code, CI aims to eradicate bugs and issues by detecting them in the early stages of software development. It all depends on the developer whether they want to run CI whenever a code is pushed or set a schedule or both. CI systems create artifacts mentioned above which are further used in CD release pipelines for automated deployments.
In general, approval is a nod for agreement or permission to perform a specific task. In the Azure DevOps pipeline, approval is a set of validations necessary prior to running a deployment. Unless all the checks are completed or approvals are achieved, the pipelines will stop functioning to prevent the deployment environment from starting.
Deployment and Deployment Group:
Deployment is performing tasks for a stage including deploying build artifacts, performing automated tests, and other actions for a stage. For Azure DevOps pipeline YAML, this deployment is also called a deployment job which is an assortment of steps that run in a sequence in an environment. Apart from that, a deployment group is a collection of deployment target machines where agents are installed, making it highly similar to an agent pool.
A release is a versioned set of artifacts that includes a snapshot of the crucial details necessary to perform different tasks and actions in the release pipeline. In a classic pipeline, these actions can include policies, stages and deployment options.
Whenever a pipeline is told to run at a specific time, it is triggered. In other words, a trigger is set by a developer that activates the pipeline at the desired time. Configuration of a pipeline at schedule time or post-completion of a build is possible and these actions are considered an Azure DevOps pipeline trigger.
A script helps in running a code as a step in a pipeline through the command line. However, the difference between a task and script is that the latter is entirely custom code and exclusive for your pipeline.
If you want to implement any function in a pipeline, you need to use the run command. By gathering the logs linked with all the currently performing steps, it evaluates the pipeline and transfers the run to several agents afterward.
Stage: A logical boundary in the pipeline is a stage and it is majorly used to highlight the separation of concerns like production, build, and quality assurance. Every stage will have at least one job, but it can have multiple jobs as well. Whenever there are multiple stages defined, they always run consecutively by default.
Phases of Azure DevOps Pipeline
The Azure DevOps pipeline is not the same for every project or team, but it varies with the requirements, technology stack, budget and the engineer’s experience. With that in mind, there cannot be an accurate framework of a DevOps pipeline, but a common framework that can be altered to meet the requirements. Below are the common phases of an Azure DevOps pipeline.
Planning is the first part of the Azure DevOps phase which includes incremental planning for the next sprints, releases or iterations in the project. The two most widely used Agile methodologies focusing on planning are XP and Scrum. Picking the right one can be done based on factors like company structure, project needs and individual choice. Both XP and Scrum can provide information on backlogs, stand-ups, and metrics which can help in enhancing overall team transparency and visibility. Furthermore, the project and product managers will build a roadmap for development that will help the entire team in the upcoming tasks to achieve.
Development is the part where the coding begins. In this part, the developers install their desired programming language’s integrated development environment, code editors and any other tool necessary for coding on the machine. To make understanding the code easier for the entire team, developers follow a specific coding style and meet the set standards to maintain utmost uniformity in the code. Once the developers are done writing the code, a pull request is made to the code repository. Afterward, the code is reviewed by the team members.
If the code with potential errors reaches the Azure DevOps pipeline, it could lead to a significant problem that could not just ruin it but may also lead to huge losses in the future. Due to this reason, several automated tests are performed on the code post-submission to the shared repository. In the building stage, the developers will try to find and eradicate as many issues from the code as possible. In most cases, once the pull request is sent, it will commence an automated process that will compile the code to a build.
Languages including Python and PHP do not require compilation whereas C and Java need to be compiled before doing so. Though all experienced developers are aware of this fact, it is always essential to keep that in mind. Coming to the test, the build will fail if there is an issue with the code. In case that happens, the developer will be alerted and they will make the necessary fixes to the code and repeat the process until they achieve the desired results.
Once the build stage is complete and is successful, it is time for the actual testing to begin. Even though the developers will perform several automated tests in the build stage, still running full-fledged testing to the code is crucial. In this stage, the developers will not just run automated tests, but manual tests as well. Several checks including performance, security and load testing are done before the code is sent for production. Furthermore, a user acceptance test is also performed to understand user behavior and decide whether any additional changes are required or not. If everything goes well, the code is pushed for the next stage.
Deployment: After the testing is completed, the build will reach the deployment stage where it will be pushed for production. In case the code passes the earlier tests smoothly without any major changes, the automated deployment method will be used. However, if the aforementioned does not happen and the build goes through major changes, it will be deployed to an environment similar to the production to monitor its behavior.
There are several ways to do so, but the commonest one is the blue-green strategy where two similar production environments are used. One environment will host the new version of the build whereas the other one will host the unchanged version of the build. Doing this will help them in monitoring the performance of the build, and if anything goes out of hand, they can simply switch to the working environment to fix the issue.
Monitoring the deployed build is the final stage of the Azure DevOps pipeline. Here, the operations team will monitor the system, application and infrastructure to ensure the smooth working of the program. Collecting Azure DevOps pipeline logs, monitoring systems, analytics, and feedback from users is also part of this phase. This collected data will help the team in finding and fixing any issues in the code. Apart from that, it will also assist them in eradicating all the issues in the production environment, directly improving their efficiency.
Building an Azure DevOps Pipeline
Building an Azure DevOps pipeline is an intriguing process that will aid in enhancing the team’s productivity and efficiency. This guide is all about building a sample application through Azure YAML pipelines using a YAML pipeline editor. Before you begin with the process, make sure that you have a GitHub account to create a repository, authority to run pipelines on Microsoft-hosted agents and an Azure DevOps organization.
- Creating the first Pipeline: Before you create your first Azure DevOps pipeline, you need to specify the programming language that you are going to use. Depending on the language, you need to attain the sample code from GitHub. Once you have attained the sample code, you need to sign in to your Azure DevOps organization and head towards your project.
- Afterward, you need to select the New Pipeline option from the Pipelines section. Now select GitHub as the location of the source code. Keep in mind that you may have to sign in to your GitHub account to move forward to the next step. Upon successful login to your GitHub account, you will see a list of available repositories. Here you need to select your repository.
- In case you have not installed the Azure Pipelines application, the system may redirect you to GitHub to install the same. All you have to do is click on Approve & Install to begin the installation. Once the installation is complete, Azure Pipelines will analyze the repository and recommend the desired pipeline template based on the programming language that you have preferred.
- Once you have the Azure DevOps pipeline template, you can review the YAML to understand its functionalities and click on Save and Run whenever you are done to move to the next step. Now you will have to commit a new Azure Pipelines YAML file to your repository.
- Now, you need to select the build job to see your pipeline functioning and the pipeline is ready to be used. You can customize the newly created Azure DevOps pipeline from your repository. Just head towards the Pipeline page and click on the Edit button to make any desired changes to the pipeline.
- Clone Azure DevOps Pipeline: Sometimes you just need to copy an already created pipeline and customize it to create a new one. Pipelines created from both YAML and classic editor can be copied but the process is a bit different. When compared with the classic editor, YAML pipelines are easier to copy. Keep in mind that cloning a pipeline is only possible when it is done within the same project. For different projects, the pipelines can be exported.
- YAML Pipeline: The process of cloning Azure DevOps YAML pipelines can only be done from the source pipeline. Start by heading towards the Pipeline Details of the pipeline which you want to clone and click on the Edit button. Now all you have to do is copy the pipeline YAML from the editor and paste the same to your new pipeline’s YAML editor. After cloning the pipeline, you can begin customizing it as per the project’s demands.
- Classic Editor Pipeline: Before you begin the process, you need to make sure that you have either Edit Build Pipeline or Edit Release Pipeline permissions. If you already have those, you can head towards the pipeline details page of the pipeline which you want to copy and click on the Clone button. The cloned pipeline will come with the name-cloned where you just need to click on Save & Queue or Save button and the pipeline will be cloned.
Benefits of Azure DevOps Pipeline
When implemented and utilized appropriately, the Azure DevOps pipeline provides several benefits to the organization.
Support for Multiple Languages:
As there are multiple programming languages and application types, having a single culture that supports all the major types is essential. Azure DevOps pipeline can be used in several application types along with all the leading programming languages like Java, Python, Ruby, C, PHP, and many others. Support for not just Windows, but macOS, and Linux is also present as well.
Development and testing is the phase where the scope of improvement is the most. Azure DevOps pipeline allows the developer to set multiple stages in these phases to control the project’s quality prior to moving to the next phase. The idea is to make sure that the code is optimized to the fullest and is error-free entirely. Moreover, it assists in identifying hidden bugs as well as several issues to eradicate them from the root.
One of the best things about the Azure DevOps pipeline is not just its features, but the frequency of upgrades. Managed by Microsoft, Azure DevOps is updated rapidly to ensure that it remains updated with the latest features.
Azure DevOps pipeline is a widely used service that has helped innumerable organizations. Another great thing about this is its pricing. For a public project, the Azure DevOps pipeline is entirely free of cost. However, developers working on a private project need to pay its subscription fee post-1800 minutes every month.
Azure DevOps is all about making software development, operations, and deployment faster and more effective. Azure DevOps pipeline helps in streamlining the implementation of these actions and promotes continuous delivery practices into the organization. With the rising use of artificial intelligence, machine learning, and automation, it can be said that the DevOps pipeline will become an integral strategic asset for an organization.
For more information visit Azure DevOps documentation.