The ALM Accelerator pipelines are the engine of the ALM Accelerator and are used to automate the ALM process for Power Platform. The pipelines are built using Azure DevOps and are stored in a project in Azure DevOps. The ALM Accelerator solution includes a custom connector for the Azure DevOps API that can be used to invoke the pipelines via Flow or other Power Platform technologies. The key to using the pipelines independently is understanding the parameters that are passed to the various pipelines. There are four main pipelines that are used to automate the ALM process for the Power Platform:
The pipelines are designed to be used used in conjunction with the ALM Accelerator canvas app. The ALM Accelerator canvas app provides a simple interface for invoking the pipelines and provides a way to configure the pipelines without having to understand the underlying parameters. The ALM Accelerator canvas app is not required to use the pipelines, but it is recommended.
ALM Accelerator Azure DevOps pipelines
The ALM Accelerator pipelines and app have default configurations that allow you to get started quickly with ALM for Power Platform. The ALM Accelerator pipelines have been developed in a way that makes it possible for many different ALM scenarios to be covered, based on your organization's requirements. The following is a description of some common scenarios and how they can be covered through configuration of the pipelines, related deployment profiles, and steps in the ALM Accelerator app or through the pipeline directly.
Installing the Azure DevOps pipelines in one project and source code in another project
From the ALM Accelerator app and in the Deployment Profiles, there's now an option to specify a pipeline project, in addition to source project. An option has also been added to the setup wizard to specify a separate pipeline project and repo. This is useful if you want to segment the storage of solutions within your organization based on users, corporate structure, or other factors. In most cases, the pipeline YAML files will be stored in the pipeline project while the export, import, and delete pipelines are created in the project where the solution is source controlled.
Run the ALM Accelerator Azure DevOps pipelines without installing the ALM Accelerator canvas app and solution
The ALM Accelerator canvas app provides an easy button layer for running the ALM Accelerator pipelines. However, the pipelines themselves, are the engine of the ALM Accelerator and can be run independently of the app. If you want to use the pipelines independently, you can run the pipelines directly from the command line or build your own app to invoke the pipelines through the Azure DevOps API.
Additionally, the ALM Accelerator solution includes a custom connector for the Azure DevOps API that can be used to invoke the pipelines via Flow or other Power Platform technologies. The key to using the pipelines independently is understanding the parameters that are passed to the various pipelines.
Parameters for import-unmanaged-to-dev-environment - The import solution pipeline is used to import an unmanaged solution from source control into a Dev environment. The parameters are as follows:
|Project||My Azure Devops Project||The name of the project to import the solution into.|
|Repo||My Azure Devops Repo||The name of the repo to import the solution from.|
|SolutionName||MySolutionName||The name of the solution to import.|
|email@example.com||The email address of the user importing the solution.|
|UserName||Last, First||The user name of the user importing the solution.|
|Branch||main||The branch to build the solution and import from.|
|ServiceConnectionName||MyServiceConnection||The name of the service connection to use for the import.|
|ServiceConnectionUrl||example.crm.dynamics.com||The URL of the maker environment for the import.|
|EnvironmentName||MyDevEnvironment||Used to find the deployment settings in the deployment pipeline. This will be a folder name under the config directory in the solution source.|
Parameters for delete-unmanaged-solution-and-components - The delete solution pipeline is used to delete an unmanaged solution and all its components from a Dev environment. The parameters are as follows:
|SolutionName||MySolutionName||The name of the solution to delete.|
|ServiceConnectionName||MyServiceConnection||The name of the service connection to use for the solution to be deleted.|
|ServiceConnectionUrl||example.crm.dynamics.com||The URL of the maker environment for the solution to be deleted.|
Parameters for export-solution-to-git - The export solution pipeline is used to export the solution to a GIT repository. The pipeline parameters are as follows:
|Project||My Azure Devops Project||The name of the project to export the solution source code to.|
|Repo||My Azure Devops Repo||The name of the repo to export the solution source code to.|
|SolutionName||MySolutionName||The name of the solution to export.|
|firstname.lastname@example.org||The email address of the user exporting the solution.|
|UserName||Last, First||The user name of the user exporting the solution.|
|CommitMessage||Fixes #1234 Bug||A description of the changes to store on the commit in the repository.|
|Branch||main||Either the source branch from which to create a new branch or the existing branch to commit to.|
|BranchToCreate||feature-1234||The unique name of a new branch to create based on the Branch parameter, if required.|
|ServiceConnectionName||MyServiceConnection||The name of the service connection to use for the solution export.|
|ServiceConnectionUrl||example.crm.dynamics.com||The URL of the maker environment where the unmanaged solution to be exported exists.|
|Data||[Deployment Settings JSON]||A JSON string containing the deployment settings to use for the export and configuring deployment pipelines (read more here).|
|PortalSiteName||MyPortalSite||The name of the Power Pages website associated with the solution to be exported.|
Customize versioning of solutions when exporting or deploying the solution using the ALM Accelerator pipelines
The ALM Accelerator pipelines allow you to customize the versioning of the solution when exporting or deploying the solution. The following is a description of the methods available that can be used to customize the versioning of the solution when exporting or deploying the solution. The default versioning method is to use the name specified in the deployment pipeline YAML file.
Use Exported versioningThere are scenarios where you may want to use the version number exported by the pipelines as the version number in all of the deployed environments. To achieve this, you can create a variable in your export pipeline or a global variable in the variable library for the ALM Accelerator with the name UseSolutionVersionFromDataverse and a value of True. This will ensure that the version number exported in your solution is preserved in downstream environments and will also be reflected in your source control when the solution source is committed.
Use Custom versioning logicYou can use ALM Accelerator hooks to set the version of the solution by adding your custom logic to the build-solution-pack-pre-hook.yml template to manipulate the Solution.xml directly or by using other tools like pac solution version.
Use Custom bring your own templates versioningThe ability to bring your own templates for generating deployment pipelines provides flexibility when deployment pipelines are generated during the initial export of a solution. An example of using this technique would be to create a copy of one of the build-deploy-validation/test/prod-SampleSolution.yml and updating the build name from the default to a versioning strategy using configure run or build numbers as a reference.
build: - name: 1.0.$(Date:yyyyMMdd)$(Rev:.r) ...
Once you have your templates in place, you can update your Deployment Steps in your Deployment Profile to point to your newly created template by following the instructions below.
Customize the number of deployment steps in your pipelines and the names of the target environments
Similar to the custom versioning mentioned above, the ability to bring your own templates for generating deployment pipelines provides flexibility when deployment pipelines are generated during the initial export of a solution. Bringing your own templates supports the ability to specify the project in which your templates exist, and the path to the template to use to generate the deployment pipeline(s). The setting for the project and path lives on the Deployment Profile and Deployment Steps table in the ALM Accelerator Administration app. The path to the template is relative to the root of the location of the export pipeline. For example, the path to the default validation environment deployment pipeline templates is /Pipelines/build-deploy-validation-SampleSolution.yml. If you wanted to use a template in the same project as the export pipeline, you would specify the path as /Pipelines/build-deploy-validation-MyCustomTemplate.yml. The templates contain placeholders for the following solution-specific values that are replaced when the deployment pipeline is generated.
|SampleSolutionName||The name of the solution to deploy.|
|RepositoryContainingTheBuildTemplates||The repository containing the build templates to use for the deployment pipeline.|
|BranchContainingTheBuildTemplates||The branch containing the build templates to use for the deployment pipeline.|
|alm-accelerator-variable-group||The global variable group the build templates will use for the deployment pipeline.|
It's recommended that you copy one of the existing build-deploy-validation/test/prod-SampleSolution.yml pipeline templates to get started with your own, custom template. Once you have your templates in place, you can update your Deployment Steps in your Deployment Profile to point to your newly, created template.
Execute custom steps in my export/import/delete and deploy pipelines without modifying the templates provided by the ALM Accelerator Team
The ALM Accelerator for Power Platform pipeline templates has several extension points that you can use to customize the pipelines. Using these extension points, or hooks, allows you to customize the pipelines while minimizing the noise from merge conflicts in upgrade scenarios. Learn more: ALM Accelerator hooks
Toggle on/off specific actions in the pipelines
There are several places in the pipelines where pipeline variables are used to dictate whether or not a task should be executed or which specific task should be executed. The following variables can be set either on an individual pipeline or through the alm-accelerator-variable-group to apply to all pipelines.
If you want to set these variables for specific solutions on export, you can create a specific export pipeline based on the export pipeline template using the naming convention export-solution-to-git-SolutionName. The ALM Accelerator app will use this export pipeline for your specific solution, rather than the general purpose export-solution-to-git pipeline.
|GenerateDeploymentSettings||True||Export||If false, the deployment settings won't be generated and stored in source control.|
|UseDeploymentSettingsPlaceholders||True||Export||If false, the deployment settings won't use placeholders and all values for the deployment settings will be saved in the deploymentSettings.json and customDeploymentSettings.json files.|
IMPORTANT: Sensitive information may be saved in plain text in your deployment settings. Any users with access to source control will be able to read these values. Take care when settings this variable.
|DisableFlows||False||Export||If true, all flows will be turned off in the unpacked, source code before committing.|
|UseSolutionVersionFromDataverse||False||Export||If true, the version number exported in your solution will be preserved in downstream environments. The version number will also be reflected in your source control when the solution source is committed.|
|DoNotExportCurrentEnvironmentVariableValues||False||Export||If true, the variable values for the current environment will be removed from the source code for the unpacked solution.|
|PublishCustomizationsBeforeExport||True||Export||If false, the customizations won't be published before the solution is exported. This is useful if you're working in a shared environment and only want to export the latest, published customizations.|
|CacheEnabled||True||Export / Deploy||If false, the caching of powershell modules will be disabled. This is useful if you're pipelines execute clean-up of the cache directory after execution of the pipelines.|
|ProcessCanvasApps||True||Export / Deploy||If false, the canvas apps won't be unpacked during export or packed during builds. The canvas unpack and pack functionality is currently in preview. It's not recommended for use in production environments at this time. However, you won't be able to view canvas source code in source control unless you set this variable to true.|
|DisableSolutionChecker||False||Deploy||By default, solution checker will run on every build that is initiated through a pull Request. You can disable solution checker from running using this variable either on an individual pipeline or for all pipelines by adding this variable to the global variable group.|
Set up pipeline sync
- Sign-in to your Azure DevOps organization and go to your project.
- Go to Pipelines, and then select New pipeline.
- Do the steps of the wizard by first selecting GitHub as the location of your source code.
- You might be redirected to GitHub to sign in.
- Go to Power Platform admin center.
- Select your environment, and then select Settings.
- Select Users + permissions > Application users.
- Select New app user to add a new application user.
- Select the Azure app registration you created, Business Unit, and Security Role. Note.
There are two main options for operating Azure Pipelines—you can define pipelines using YAML code or the classic UI.How to setup a build and release pipeline with Azure DevOps and Azure App Services? ›
- Create a pipeline and select the ASP.NET Core template. ...
- Save the pipeline and queue a build to see it in action.
- Create a release pipeline and select the Azure App Service Deployment template for your stage. ...
- Link the build pipeline as an artifact for this release pipeline.
Azure Pipelines automatically builds and tests code projects. It supports all major languages and project types and combines continuous integration, continuous delivery, and continuous testing to build, test, and deliver your code to any destination.How do I run pipeline automatically in Azure DevOps? ›
To force a pipeline to run even when there are no code changes, you can use the always keyword. Scheduled builds aren't supported in YAML syntax in this version of Azure DevOps Server. After you create your YAML build pipeline, you can use pipeline settings to specify a scheduled trigger.What is the accelerator for power platform? ›
The ALM accelerator for Microsoft Power Platform components enable makers to apply source-control strategies with Azure DevOps, and use automated builds and deployment of solutions to their environments without the need for manual intervention by the maker, administrator, developer, or tester.What is ALM in powerapps? ›
ALM is the lifecycle management of applications, which includes governance, development, and maintenance.How do I create an ALM project? ›
- (Optional) Create a project domain. ...
- Create project administrator users. ...
- Create a new project. ...
- (Optional) Assign more project administrators to the project. ...
- Define the project's settings. ...
- Add and customize the project users.
The Azure DevOps Server provides two different types of pipelines to perform build, deployment, testing and further actions. A Build Pipeline is used to generate Artifacts out of Source Code. A Release Pipeline consumes the Artifacts and conducts follow-up actions within a multi-staging system.
Declarative versus Scripted Pipeline syntax
Declarative and Scripted Pipelines are constructed fundamentally differently.
- Go to Azure Devops and select the project for your deployment.
- Click Pipelines.
- Click the pipeline. For example, the infrastructure pipeline.
- Click Run Pipeline. Note. ...
- In the Run Pipeline dialog click Run. Azure Devops will queue the job and start the redeployment.
So what is the difference between Azure Pipelines and release pipelines? Well, a release represents continuous delivery in Azure DevOps. A pipeline usually takes code, builds it, tests, and creates an artifact. Release pipelines takes the artifact and deploys it.How do I import Pipelines into Azure DevOps? ›
To import the pipeline, navigate to the Pipelines page in your project. Choose ..., select Import a pipeline, and select the corresponding import pipeline option. You will now be prompted to select a JSON file to import its contents. Browse to and select the JSON file that you previously exported.What are two ways of executing pipelines in Azure? ›
You can execute a pipeline either manually or by using a trigger. This article provides details about both ways of executing a pipeline.What are the limitations of Azure DevOps pipeline? ›
Azure DevOps Services limits each organization to 1000 projects per organization, an increase over the previous limit of 300 projects. Above 300 projects certain experiences, such as connecting to a project from Visual Studio, may start to degrade.What are the tools used in Azure DevOps pipeline? ›
- Azure Boards.
- Azure Repos.
- Azure Pipelines.
- Azure Test plans.
- Azure Artifacts.
- Azure DevOps Server.
- All services.
The Build Workflow must complete before another Workflow in the Pipeline can deploy the artifact. Always Put Build Workflow First — The Build Workflow should always be the first stage in the Pipeline. This enables the rest of the Pipeline to use the artifact it builds and collects.How do I allow access to all pipelines in Azure DevOps? ›
- From within your project, select Pipelines > Pipelines.
- Select More actions > Manage security.
- Modify the permissions associated with an Azure DevOps group, for example, Build Administrators, or for an individual user.
Go to Pipelines and click on New pipeline in the upper right corner. Select the code hoster in the Connect step and the repository in the Select step where your YAML file resides. In the Configure step choose the option Existing Azure Pipelines YAML file and select the correct file in the dropdown menu.
Their job is to speed up and increase the energy of a beam of particles by generating electric fields that accelerate the particles, and magnetic fields that steer and focus them.What is the purpose of Power Platform? ›
Power Platform integrates low-code solutions with secure and trusted Microsoft cloud services, including Azure, Dynamics 365, and Microsoft 365.How do you deploy a project accelerator? ›
Deploy the Accelerator
Open the Environment menu and select your Project for the web environment. In the navigation pane, select Solutions. On the command bar, select Import. In the Import a solution dialog, select Browse, then find and select the Accelerator file you downloaded.
Application lifecycle management (ALM) is an integrated system of people, tools and processes that supervise a software application from its initial planning and development, through testing and maintenance, and into decommissioning and retirement.What is the ALM process? ›
ALM uses defined roles, record types, and state transition models to help you manage the software development process from requirements submission through development, build management, and testing. A typical ALM process is as follows: A stakeholder submits a request against a software project.What is an example of ALM? ›
Examples of ALM tools:
Atlassian Jira. IBM ALM solutions. CA Agile Central. Microsoft Azure DevOps Server.
11.5 ALM Process
The scope of ALM function can be described as under: Liquidity risk management. Management of market risks. Funding and capital planning.
Essentially, three major types of pipelines occur along the transportation route: gathering lines, the interstate pipeline, and the distribution system.What are three basic types of pipeline systems *? ›
There are essentially three major types of pipelines along the transportation route: gathering systems, transmission systems, and distribution systems.What language is used in Azure pipelines? ›
Azure Pipelines is a cloud service that is useful in automating build and testing the code project. It is implementable to any programming language or type of project. It supports languages such as C#, C++, Go, Java, Java Script, PHP, Python, Ruby, YAML and many more.
Those stages are, Fetch, Decode, Execute, Memory, and Write.What is pipelining give an example? ›
Pipelining is the process of storing and prioritizing computer instructions that the processor executes. The pipeline is a "logical pipeline" that lets the processor perform an instruction in multiple steps. The processing happens in a continuous, orderly, somewhat overlapped manner.What are pipelines examples? ›
There are two types of oil pipeline: crude oil pipeline and product pipeline. While the former carries crude oil to refineries, the latter transports refined products such as gasoline, kerosene, jet fuel, and heating oil from refineries to the market.Where is pipeline Yaml in Azure DevOps? ›
Usually, this file is named azure-pipelines. yml and is located at the root of your repo. Navigate to the Pipelines page in Azure Pipelines, select the pipeline you created, and choose Edit in the context menu of the pipeline to open the YAML editor for the pipeline.How do I connect to Azure in Azure DevOps pipeline? ›
In Azure DevOps, open the Service connections page from the project settings page. In TFS, open the Services page from the "settings" icon in the top menu bar. Choose + New service connection and select Azure Resource Manager. Choose Service Principal (manual) option and enter the Service Principal details.What is Azure DevOps also called? ›
Azure DevOps is also known as Microsoft visual studio team services (VSTS). It is a set of collaborative development tools built for the cloud. VSTS was commonly used as a standalone term, and Azure DevOps is a platform which is made up of a few different products, such as: Azure Test Plans.How do I write a YAML file in Azure DevOps? ›
- Create a new file named azure-pipelines. yml file in your repo.
- Copy the content from the Samples/azure-pipelines. yml file.
- Commit the changes to your repo. You'll reference and update the azure-pipelines. yml file when you're configuring your pipeline in Step 4.
- To start, you need the Azure CLI with the Azure DevOps extension installed. ...
- Clone your Git repository and navigate to the repo directory.
- Run az pipelines create : ...
- Follow the steps to set up the pipeline.
Components of a DevOps Pipeline
Continuous Integration and Continuous Delivery: These two components are typically mentioned together, usually referred to as CI/CD or a CI/CD pipeline.
During a run, the pipeline is processed, and agents process one or more jobs. A pipeline run includes jobs, steps, and tasks. Runs power both continuous integration (CI) and continuous delivery (CD) pipelines. When you run a pipeline, many things happen under the covers.
- Pipelines > New Pipeline.
- Select “Azure Repos Git (YAML)”
- Select the target repository in the DevOps project.
- Configure: Existing Azure Pipelines YAML File.
- Path: select target yaml file > Continue.
- Go to pipelines again > click on more opntions (virtical dots) of newly created pipeline > Rename / Move.
- Step 1: Choose CI/CD Tool. Although DevOps methodologies might differ from company to company, each company must pick a CI/CD tool that suits its specific needs. ...
- Step 2: Establish a Control Environment. ...
- Step 3: Set up a build server. ...
- Initiate Automated Tests. ...
- Step 5: Deploy to Production.
- Get started. Concept. Quickstart. ...
- Build, deploy, test-any language, any ecosystem. Tutorial. ...
- Key concepts. Concept. ...
- Reference guidance. Reference. ...
- Build any repository. How-To Guide. ...
- Deploy to Azure. Overview. ...
- Manage agents & self-hosted agents. How-To Guide. ...
- Set up continuous testing. Tutorial.
- Create a data factory.
- Create a pipeline with a copy activity.
- Test run the pipeline.
- Trigger the pipeline manually.
- Trigger the pipeline on a schedule.
- Monitor the pipeline and activity runs.
- Step 1: Create a deployment environment. ...
- Step 2: Get a copy of the sample code. ...
- Step 3: Create your pipeline. ...
- Step 4: Activate your pipeline to deploy your code. ...
- Step 5: Commit a change and then update your app. ...
- Step 6: Clean up your resources.
- Select Pipelines in the left navigation pane.
- Select Create Pipeline.
- Select GitHub YAML.
- Search for or select your repo.
- Select Existing Azure Pipelines YAML file.
- Set the path to the Azure YAML pipeline file you created earlier.
- Select Continue: ...
- Update repositories name to your repo.
The first step in building an information production system is to connect to all the required sources of data and processing, such as software-as-a-service (SaaS) services, databases, file shares, and FTP web services. The next step is to move the data as needed to a centralized location for subsequent processing.How do I create an Azure pipeline for Azure function? ›
To create a build pipeline in Azure, use the az functionapp devops-pipeline create command. The build pipeline is created to build and release any code changes that are made in your repo. The command generates a new YAML file that defines the build and release pipeline and then commits it to your repo.How do I create a pipeline in Azure DevOps using PowerShell? ›
- Push your script into your repo.
- Add a PowerShell build task.
- Drag the build task where you want it to run.
- Specify the name of the script.
- Version Control.
- Acceptance Tests.
- Independent Deployment.
- Production Deployment.
The configuration of a pipeline used to handle a web service request is specified in an XML document, known as a pipeline configuration file . The pipeline configuration file is stored in the z/OS® UNIX System Services file system and its name is specified in the CONFIGFILE attribute of a PIPELINE resource definition.How do I deploy a VM with Azure DevOps pipeline? ›
Sign into your Azure DevOps organization and navigate to your project. Go to the Pipelines page and select Environments > Create Environment. Specify a Name (required) for the environment and a Description. Choose Virtual Machines as a Resource to be added to the environment, and then select Next.Where is pipeline YAML in Azure DevOps? ›
Usually, this file is named azure-pipelines. yml and is located at the root of your repo. Navigate to the Pipelines page in Azure Pipelines, select the pipeline you created, and choose Edit in the context menu of the pipeline to open the YAML editor for the pipeline.What is YAML file used for DevOps? ›
YAML is a human-readable data serialization language that is often used for writing configuration files. Depending on whom you ask, YAML stands for yet another markup language or YAML ain't markup language (a recursive acronym), which emphasizes that YAML is for data, not documents.