Power Platform# – Page 2 – ECELLORS CRM Blog

Hi Folks,

This post is about ALM in Power Platform integrating with a different ecosystem than usual, i.e. using Google Cloud, sounds interesting..? This approach is mainly intended for folks using Google Cloud or GitLab as part of their implementation.

Integrating Google Cloud Build with Power Platform for ALM (Application Lifecycle Management) using GitLab is feasible and beneficial. This integration combines GitLab as a unified DevOps platform with Google Cloud Build for executing CI/CD pipelines, enabling automated build, test, export, and deployment of Power Platform solutions efficiently. This was the core idea for my session on Friday 28 November, at New Zealand Business Applications Summit 2025.

Detailed Steps for this implementation

Create an access token in GitLab for API Access and Read Access

Click on Add new token, you can select at the minimum the below scopes while you were working with CI-CD using GitLab

Create a host connection for the repository in GitLab

Specify the personal access token created in the previous step

Link your repository

The created host connections in the previous step will be shown under Connec ctions drop down

Create Trigger in Google Cloud Build

Click on Create trigger above, provide a name, select a nearest region

Event:

For now, I am choosing Manual invocation for illustration

Specify where the name of the Repository where your YAML in GitLab resides

You can optionally specify the substitution variables which are nothing but parameters you can pass to your pipeline from Google Cloud Build Configuration

You can optionally give this for any approval and choose the service account tagged to your google account in the drop down.

Click on Save.

Next proceed to GitLab YAML

You can find the full code below

	steps:
	– id: "export_managed"
	name: "mcr.microsoft.com/dotnet/sdk:9.0"
	entrypoint: "bash"
	args:
	– "-c"
	– \|
	echo "=== 🏁 Starting Export Process ==="
	# ✅ Define solution name from substitution variable
	SOLUTION_NAME="${_SOLUTION_NAME}"
	# ✅ Install PAC CLI
	mkdir -p "${_HOME}/.dotnet/tools"
	dotnet tool install –global Microsoft.PowerApps.CLI.Tool –version 1.48.2 \|\| true
	# Add dotnet global tools dir to the shell PATH for this step/session (preserve existing PATH)
	export PATH="$_PATH:${_HOME}/.dotnet/tools"
	echo "=== 🔐 Authenticating to Power Platform Environment ==="
	pac auth create –name "manual" –url "https://ecellorsdev.crm8.dynamics.com" –tenant "XXXXX-XXXX-XXXXX-XXXXXX-XXXXX" –applicationId "XXXXXXXXXXXXXX" –clientSecret "XXXXXXXXXXXXXXXX"
	pac auth list

	echo "=== 📦 Exporting Solution: ${_SOLUTION_NAME} ==="
	pac solution export \
	–name "${_SOLUTION_NAME}" \
	–path "/tmp/${_SOLUTION_NAME}.zip" \
	–managed true \
	–environment "${_SOURCE_ENV_URL}"

	echo "=== ✅ Solution exported to /tmp/${_SOLUTION_NAME}.zip ==="
	echo "=== 🔐 Authenticating to Target Environment ==="
	pac auth create \
	–name "target" \
	–url "https://org94bd5a39.crm.dynamics.com" \
	–tenant "XXXXXXXXXXXXXXXXXXXXXXXX" \
	–applicationId "XXXX-XXXXX-XXXXX-XXXXXX" \
	–clientSecret "xxxxxxxxxxxxxxxxxxxx"
	echo "=== 📥 Importing Solution to Target Environment ==="
	pac solution import \
	–path "/tmp/${_SOLUTION_NAME}.zip" \
	–environment "${_TARGET_ENV_URL}" \
	–activate-plugins \
	–publish-changes
	echo "=== 🎉 Solution imported successfully! ==="

	options:
	logging: CLOUD_LOGGING_ONLY

	substitutions:
	_SOLUTION_NAME: "PluginsForALM_GitLab"
	_SOURCE_ENV_URL: "https://org.crm.dynamics.com"
	_TARGET_ENV_URL: "https://org.crm.dynamics.com"
	_TENANT_ID: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
	_CLIENT_ID: "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
	_CLIENT_SECRET: "xxxxxxxxxxxxxxxxxxxxxxxxxxxx"
	_SOLUTIONS_DIR: "/workspace/Plugins/08112025"

view raw GitLabDemo.yaml hosted with ❤ by GitHub

Solution from Source Environment

Now lets run the trigger which will export the solution from the source environment and import to the target environment….we have manual trigger, automatic trigger whenever there is an commit to the repo in GitLab etc., you may pick whatever suits your needs best.

Solution imported to the target environment using Google Cloud Build

The below table illustrates key differences between Google Cloud Build and Azure Devops….

Aspect	Google Cloud Build	Azure DevOps Build Pipelines
Pricing Model	Pay-as-you-go with per-second billing	Per-minute billing with tiered pricing
Cost Optimization	Sustained use discounts, preemptible VMs	Reserved capacity and enterprise agreements
Build Environment	Serverless, container-native, managed by Google Cloud	Requires self-hosted or paid hosted agents
Free Tier	Available with build minutes and credits	Available but more limited
Operational Overhead	Low, no need to manage build agents	Higher, managing agents or paying for hosted agents
Ideal For	Variable, short, or containerized workloads	Large Microsoft-centric organizations
Integration Cost Impact	Tightly integrated with Google Cloud serverless infrastructure	Integrated with Microsoft ecosystem but may incur additional licensing costs

Conclusion:

PAC CLI is a powerful command-line tool that automates authentication, environment, and solution management within Power Platform ALM, enabling consistent and repeatable deployment workflows. It integrates smoothly with DevOps tools like GitLab and Google Cloud Build, helping teams scale ALM practices efficiently while maintaining control and visibility over Power Platform environments. Just note, my intention was showcase the power of PAC CLI with wider ecosystem, not only with Microsoft.

Cheers,

PMDY

The Solution blueprint review is covers all required topics. The workshop can also be conducted remotely. When the workshop is done remotely, it is typical to divide the review into several sessions over several days.

The following sections cover the top-level topics of the Solution blueprint review and provide a sampling of the types of questions that are covered in each section.

Program strategy

Program strategy covers the process and structures that will guide the implementation. It also reviews the approach that will be used to capture, validate, and manage requirements, and the plan and schedule for creation and adoption of the solution.