YAML Pipeline Templates for iPaaS Solutions
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They provide configuration-as-code and support the creation of pipeline templates. However, as the number of integrations grows, the complexity of pipelines increases. This sets the need for a scalable pipeline design that provides a uniform development experience and minimizes configuration effort. This post explores such a design. Niels van der Kaap 9 September Organizations are increasingly moving their existing integration solutions to the cloud. The resulting solutions include components such as Logic Apps and Azure Functions.
YAML pipelines provide a pipeline-as-code approach, allowing you to use modular templates. Thus, pipelines can reuse these templates to simplify their configuration. Consequently, this reduces deployment failures and increases development speed.
It is common for integration environments to contain many independent solutions, each requiring dedicated pipelines. Moreover, most integration solutions follow similar patterns. Therefore, YAML templates are a good option to simplify the configuration.
But to be successful, a pipeline template must meet a number of criteria: Minimize solution-based configuration to reduce complexity. Limit template size to reduce complexity. Allow for versioning to increase flexibility. Minimize pipelines creation effort to increase development speed. Reduce effort to support new PaaS components. The first stage builds all components and creates an environment agnostic package. The second stage then deploys this package to a given environment.
Azure DevOps must retain the generated packages for later use. This can either be for a rollback or a manual deployment. Yet single YAML pipelines cannot retain their packages at the time of writing.
Therefore, we use separate CI and CD pipelines. This leads to a separation of component configuration: CI pipelines contain the build configuration, whereas CD pipelines hold the deployment configuration. Merging the CI and CD configuration into a third template reduces this complexity.
This structure is shown below. A push first triggers a CI pipeline run. Once completed, this run triggers the CD pipeline. Solution Specific Configuration CI. They also define the config parameter. This parameter contains the base path for the solution and signals the downstream template that it should either act as a CI or a CD pipeline.
The Solution. First, it defines the variable groups for build-and-release stages. It also creates the components parameter. The example below shows a case with one Azure Function. The above approach centralizes and condenses the pipeline configuration for each solution. This increases maintainability. Moreover, automated scripts can use the above files as a template for creating new pipelines.
Pipeline variables cannot contain objects, and so this approach uses parameters. Generic Pipeline Definition The generic Template. Here, each stage either builds or deploys the components from Solution. The entire file looks as follows: The template starts by defining the four parameters from the Solution. It then introduces the environments parameter. This parameter contains the environment configuration for all pipelines, defining the name, service connection, dependencies, and deployment conditions.
After initializing the base path of the current solution, the file determines whether it acts as a CI or as a CD pipeline. CI Pipelines generate a single Build stage. This stage first loads the variable groups from the buildVariableGroups parameter. It then generates a job for every component. The compiler uses the type of each component to dynamically load a task template with the corresponding build tasks.
CD pipelines generate identical Deploy stages for each environment. The stage first links the deployment variable groups for the right environment and by default also loads the Infra variables group for the right environment. The stage conditions depend on the existence of a custom environment condition. The condition also includes a mechanism for performing manual deployments to a single environment.
Next, the stage defines deployment jobs for all components. Each of the jobs loads a task template containing the deployment tasks for a component. Again, the component type determines what template to use. Task template Each component type requires a seperate build and deployment task template.
Both files contain the component parameter. This parameter includes the component-specific information from Solution. In addition, the deployment task template defines the environment parameter. This parameter contains the environment name and the service connection to use. Both templates use the parameters to include component and environment-specific information in the template.
In addition, the build task template uses the basepath variable from Template. The component type also contains a version, providing a versioning strategy for task templates. Conclusion In conclusion, the pipeline design of this post satisfies the stated criteria: It minimizes solution-based configuration It allows for automated pipeline creation, using scripts.
It provides a mechanism for performing on-demand deployment to a given environment. It includes a versioning strategy for build and deployment tasks Extension with new components does not require modification of existing files. Therefore, this approach improves maintainability and reduces overall complexity.
Trigger a Pipeline from an Azure DevOps Pipeline
An empty Azure WebApp deployed using dotnetcore 2. You can see what to expect below. This will open the Azure DevOps blade as you can see below. Azure DevOps dashboard 2. You will be brought to a page where you can create a new organization as shown below. Once here, click on the blue Create new organization button. Create new Azure DevOps organization page 3.
On the next page, provide a name for the organization. If you run into problems with using a specific name, be sure to check the Azure DevOps organization naming conventions.
On this screen, also specify an Azure region closest to you. Once done, click Continue. Azure DevOps gives you the ability to create a project during the same workflow as creating an organization as performed above. If you followed along, you should now be presented with a project creation page as shown below. On the project creation page, provide a name for your project in the Project name field. For now, leave the Visibility set to Private.
The pipeline is where all the magic happens. From the dashboard, select Pipelines then on Builds. Azure DevOps Builds menu 2. You will see a message telling you there are no build pipelines found yet. Click on New pipeline to begin creating the build pipeline. No build pipelines bound yet. Creating a new pipeline. You will then be prompted for where your code is stored.
In this Project, the code is stored in a GitHub repository. Select GitHub. This is the place where code is stored and the triggers for invoking the build will come from. Selecting version control source 4. Before you begin this step, remember to have an empty GitHub repo created as defined in the Prerequisites section of this article! Providing GitHub credentials 5. Next, confirm the step where you are asked to authorize Azure Pipelines. Select the empty GitHub repo you have created for this Project.
Empty source GitHub repo 2. Allow the project to read, write and check source code from the repository you selected earlier. Confirm Azure DevOps Github integration 3. By clicking confirm, you will see an error generated as shown below.
This error will happen because the GitHub Repo selected is empty. In this repo, I have all the source code available to publish an e-commerce sample application in Azure WebApps. The sample code for this repo will contain a sample e-commerce application called SimplCommerce. Navigate to this sample GitHub repo and click on Import code as shown below.
Empty myfirstrepo GitHub repo 2. Proving the repo clone URL When the repo import step is completed successfully, refresh the Azure DevOps Pipeline window, which should allow you to continue now. You will now be presented with a representation of the build pipeline in YAML. This YAML file is automatically built based on the detection of the source code language which is dotnetcore in this Project.
With many other DevOps tools, you have to build a pipeline file manually. But, you can also manually trigger the build pipeline to run. This will start the pipeline build process as you can see from the below screenshot. Pipeline starting After a few seconds, you can see that the process will be running for macOS as shown below. The build pipeline will return information in real-time as each job and task in the pipeline runs. Running on the macOS build agent The build pipeline will then repeat the same process for the other operating systems in this example as shown below.
The steps taken will vary greatly depending on how the YAML file was built. Running on the Linux build agent Once the build has completed, you are greeted with green checkmarks as you can see below. This screenshot indicates each platform build passed successfully. The ultimate goal of software needs to be deployed so customers can use it. A release pipeline takes a build artifact, a result of the build process and deploys that to one or more environments. Releases menu item 2.
Next, select New and then New Release Pipeline. This launches the New release pipeline wizard. New release pipeline menu option 3. From the template list on the right, select Azure App Service Deployment. Select the Azure App Service deployment template 4. Provide a description for the Stage Name.
The stage will contain release tasks. Specify the stage name The release pipeline should now look like the below screenshot. Created stage 5. In the Stages field, select 1 job, 1 task.
This field is where you will eventually provide the settings of the Azure Web App environment you will use for the actual deployment. Stage Name — Deploy-to-webapps2 in this example. Azure Subscription — select your subscription and confirm with Authorize needs credentials App type — Web App on Linux App Service Name — the web app you created earlier Setting template parameters 7.
When done, click Pipeline in the top menu of your Azure Pipeline project as shown below. This will return you to the main screen and allow you to complete the next step which is specifying the artifacts. Going back to the pipeline Adding Artifacts to the Azure DevOps Release Pipeline Within a release pipeline, there are many different items that need to be deployed.
These items are called artifacts. Artifacts put simply, are deployable components of your application. Azure Pipelines can deploy artifacts that are produced by a wide range of artifact sources. While on the Pipeline screen, click on Add an Artifact.
Choose the build pipeline created earlier in the Source build pipeline dropdown. When finished, click on Add to save the configuration. Adding an artifact 4. Finally, click on the Save button in the upper right corner of the screen to save the release pipeline.
A release is a particular run of the pipeline. Think of the release pipeline as the template and specific instances of that release pipeline as releases. Once you have a release, that release can then be deployed.
To create a release: Click the Create Release button in the upper right corner of the window as shown below. New release pipeline overview 2. You only have a single stage at this time and have a single version of the build artifact to deploy now. Create a new release item 3. After a few seconds, you will receive a notification the green bar that the release has been created as shown below.
Now click on Release-1 which will redirect you to the details of the release process. Manually Deploying a Release A release is a set of instructions to perform on how to deploy a build. When you do so, the status will change to In progress as shown below.
At this point, the release is grabbing the source code from the build pipeline executed earlier and pushing it to the Azure WebApp instance. This step will initiate a job running in the back-end on an agent copying source code and performing the actual release cycle.
Stage in progress 2. You will see any logging information shown in the console output area. Job log showing stage in progress When complete, the stage should show Succeeded as seen below. Successful stage If all went well, the release should have finished and you should now have a web app published to an Azure Web App! Inspecting the Deployed Azure WebApp Now that the entire process is complete, be sure to check out the fruits of your labor.
You now have an Azure web app deployed from a GitHub repo able to be automated to the fullest! Cleaning Up If you followed along throughout this Project, you now have a new Azure DevOps organization, project, build pipeline, release pipeline and release.
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Find below some of the pre-defined variables more commonly used. Workspace This variable stores local path on agent for running build, both variables have the same values. TempDirectory A temporary folder that is cleaned after each pipeline job. You can use this variable to store secret files during the pipeline and clean it up after that.
BuildNumber The ID for the completed build. DefaultWorkingDirectory The local path on the agent where you download source code files. Agent Node Pool: In order to run, build and deploy a pipeline for your application you need at least one agent.
When you configure your pipeline, you have two agent options: Azure managed agent and self-hosted agent. An agent can be a virtual machine or a container which acts as a compute engine. The important point to consider here is the cost.
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With a self-hosted agent you can use the Azure pipeline for free. Here you are able to provide compute resources and use Azure DevOps pipelines as an orchestrator. A self hosted agent allows you to install software or libraries required to build and deploy a pipeline.
To use a Microsoft-hosted agent in your Azure pipeline, mention the operating system name as shown in the below YAML format: pool: 3. Go to Organization Settings.
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Click on Agent Pools. Click on Add Pool. Fill the details as shown in the picture below. Then on the next screen click on New Agent.
To do this, click on the Set up build button located at the top of your repo. A pipeline is a preconfigured set of steps that determine the build and deployment process every time there is an update on your code. This is an automated process and can save time on deployment.
If you click on Show more, it will expand a series of options that will let you build your code based on your preferred methodology. Your pipeline is configured through a YAML file. This will automatically boot up your first build. Once your build is completed, the blue process bubble will turn into a green tick. However, a build by itself is not very useful until it is deployed. To do this, you need to set up your environment.
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Click on the blue Create environment button. This will give you a side popup where you can set up your new environment. Once you fill in the Name and Description section, you can create your environment.
If you already know what kind of environment you want, you can select it now. Otherwise, you can attach it later.
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Depending on what you choose, you might need to either set up a Kubernetes cluster and link it in or set up a virtual PC. Then, you can create a release pipeline by clicking on Releases on the sidebar panel. This will navigate you to the new release pipeline process: To add a source of your build, select the Add an artifact bubble. This will bring a popup where you can select the source of your artifact. The next step is to add a stage. Different development cycles have different stages for release.
In our case, we are going to make a User Acceptance Test stage, which is where we can deploy our prototypes and preapproved builds before it hits production. A list of templates will be presented.
Select the one that applies to your project and it will run you through the setup process for it. In the final step, it will ask you to set a name for the stage. Once completed, click on the X in the corner.
This will take you back to your pipeline area. If you click on the 1 job, 1 task link, it will take you to the pipeline tasks set up. Fill in the necessary information. Once done, click on the save button at the top.