Srinivas Blog

Recently, I had the opportunity to set up an Azure DevOps pipeline to automate the deployment of Managed Solutions in Dynamics 365 Customer Engagement (Dataverse). The goal was to streamline the release process across multiple environments (ITG → PreProd → Production) with minimal manual intervention.

While the process involves a bit of configuration and understanding of Microsoft’s Power Platform tooling, once it’s in place, it can save a lot of time and reduce deployment errors. In this post, I’ll walk through the approach I followed and point to the official documentation that helped me along the way.

Objectives

Export and store Managed Solution from source environment (e.g., Dev or ITG)
Use Azure DevOps Pipeline to deploy the solution into target environments
Parameterize the deployment using variables
Ensure auditability and automation across environments

Tools & Prerequisites

To begin with, here are the core tools and prerequisites:

Azure DevOps Project
Power Platform Build Tools Extension (Install from Marketplace)
Service Principal or Application User with environment-level access
Power Platform CLI (PAC CLI) – optional for local testing

Solution Setup in DevOps

1. Install Power Platform Build Tools

This extension provides Azure DevOps tasks for working with Power Platform and Dataverse. You can install it from the Visual Studio Marketplace:

🔗 Power Platform Build Tools

2. Create a Service Connection

Go to Project Settings > Service Connections > New Service Connection > Power Platform.

You’ll need:

Client ID
Client Secret
Tenant ID
Environment URL

Follow the guide:
📘 Set up a service principal

3. Define Pipeline Structure

Here’s an outline of how the pipeline is structured:

Stage 1: Export Solution from Source Environment

Power Platform Tool Installer
Export Solution Task (Set Export As = Managed)
Upload Artifacts (Store .zip file)

Stage 2: Import Solution into Target Environment

Download Artifacts
Import Solution Task
Publish All Customizations (optional but recommended)

You can also enable "Check Solution" before import for validation.

4. Sample YAML Pipeline Snippet

trigger:
- main

pool:
  vmImage: 'windows-latest'

variables:
  SolutionName: 'MyManagedSolution'
  EnvironmentUrl: 'https://myenv.crm.dynamics.com'

stages:
- stage: ExportSolution
  jobs:
  - job: Export
    steps:
    - task: PowerPlatformToolInstaller@2
    - task: PowerPlatformExportSolution@2
      inputs:
        authenticationType: 'PowerPlatformSPN'
        PowerPlatformSPN: 'MyServiceConnection'
        solutionName: '$(SolutionName)'
        solutionOutputFile: '$(Build.ArtifactStagingDirectory)/$(SolutionName).zip'
        managed: true
    - task: PublishBuildArtifacts@1
      inputs:
        pathToPublish: '$(Build.ArtifactStagingDirectory)'
        artifactName: 'solutionArtifact'

- stage: ImportSolution
  dependsOn: ExportSolution
  jobs:
  - job: Import
    steps:
    - task: DownloadBuildArtifacts@0
      inputs:
        artifactName: 'solutionArtifact'
    - task: PowerPlatformImportSolution@2
      inputs:
        authenticationType: 'PowerPlatformSPN'
        PowerPlatformSPN: 'MyServiceConnection'
        environmentUrl: '$(EnvironmentUrl)'
        solutionInputFile: '$(Pipeline.Workspace)/solutionArtifact/$(SolutionName).zip'

Tips and Best Practices

Use variables/groups for managing credentials and URLs
Split pipelines by environment stages for approvals
Set Async Operations timeout for large solutions
Use PAC CLI locally for troubleshooting before automating

Additional Resources

Here are some helpful links I relied on:

Final Thoughts

This experience really showcased the power of DevOps in enterprise Dynamics 365 development. With a properly set up pipeline, deployments become repeatable, reliable, and consistent. If you're just getting started, I highly recommend playing with PAC CLI locally before configuring your pipelines.

Have you tried DevOps with Dynamics 365? Feel free to share your thoughts or questions!