AZ-400 Exam Dumps - Microsoft Azure Questions and Answers

Step 1: Create a Desired State Configuration (DSC) configuration file that has an extension of .ps1.

Step 2: Run the Import-AzureRmAutomationDscConfiguration Azure Powershell cmdlet

The Import-AzureRmAutomationDscConfiguration cmdlet imports an APS Desired State Configuration (DSC) configuration into Azure Automation. Specify the path of an APS script that contains a single DSC configuration.

Example:

PS C:\>Import-AzureRmAutomationDscConfiguration -AutomationAccountName "Contoso17"-ResourceGroupName "ResourceGroup01" -SourcePath "C:\DSC\client.ps1" -Force

This command imports the DSC configuration in the file named client.ps1 into the Automation account named Contoso17. The command specifies the Force parameter. If there is an existing DSC configuration, this command replaces it.

Step 3: Run the Start-AzureRmAutomationDscCompilationJob Azure Powershell cmdlet

The Start-AzureRmAutomationDscCompilationJob cmdlet compiles an APS Desired State Configuration (DSC) configuration in Azure Automation.

References:

https://docs.microsoft. com/en-us/powershell/module/azurerm.automation/import-azurermautomationdscconfiguration

https://docs.microsoft.com/en-us/powers hell/module/azurerm.automation/start-azurermautomationdsccompilationjob

Batching CI runs

If you have many team members uploading changes often, you may want to reduce the number of runs you start. If you set batch to true, when a pipeline is running, the system waits until the run is completed, then starts another run with all changes that have not yet been built.

Example:

# specific branch build with batching

trigger:

batch: true

branches:

include:

- master

To clarify this example, let us say that a push A to master caused the above pipeline to run. While that pipeline is running, additional pushes B and C occur into the repository. These updates do not start new independent runs immediately. But after the first run is completed, all pushes until that point of time are batched together and a new run is started.

Scenario: Implement Project3, Project5, Project6, and Project7 based on the planned changes

Step 1: Open the release pipeline editor.

In the Releases tab of Azure Pipelines, select your release pipeline and choose Edit to open the pipeline editor.

Step 2: Enable Gates.

Choose the pre-deployment conditions icon for the Production stage to open the conditions panel. Enable gates by using the switch control in the Gates section.

Step 3: Add Query Work items.

Choose + Add and select the Query Work Items gate.

Configure the gate by selecting an existing work item query.

Note: A case for release gate is:

Incident and issues management. Ensure the required status for work items, incidents, and issues. For example, ensure deployment occurs only if no priority zero bugs exist, and validation that there are no active incidents takes place after deployment.

References:

https://docs.microsoft.com/en-us/azure/devops/pipelines/release/deploy-using-approvals?view=azure-devops#configure-gate

Step 1: Create a repository

A Git repository, or repo, is a folder that you've told Git to help you track file changes in. You can have any number of repos on your computer, each stored in their own folder.

Step 2: Create a branch

Branch policies help teams protect their important branches of development. Policies enforce your team's code quality and change management standards.

Step 3: Add a build validation policy

When a build validation policy is enabled, a new build is queued when a new pull request is created or when changes are pushed to an existing pull request targeting this branch. The build policy then evaluates the results of the build to determine whether the pull request can be completed.

Scenario:

Implement a code flow strategy for Project2 that will:

Enable Team2 to submit pull requests for Project2.

Enable Team2 to work independently on changes to a copy of Project2.

Ensure that any intermediary changes performed by Team2 on a copy of Project2 will be subject to the same restrictions as the ones defined in the build policy of Project2.

References: https://docs.microsoft.com/en-us/azure/devops/repos/git/man age-your-branches

Scenario:

Step 1: Sign in to Azure Develops by using an account that is assigned the Administrator service connection security role.

Note: Under Agent Phase, click Deploy Service Fabric Application. Click Docker Settings and then click Configure Docker settings. In Registry Credentials Source, select Azure Resource Manager Service Connection. Then select your Azure subscription.

Step 2: Create a personal access token..

A personal access token or PAT is required so that a machine can join the pool created with the Agent Pools (read, manage) scope.

Step 3: Install and register the Azure Pipelines agent on an Azure virtual machine.

By running a Azure Pipeline agent in the cluster, we make it possible to test any service, regardless of type.

References:

https://doc s.microsoft.com/en-us/azure/service-fabric/service-fabric-tutorial-deploy-container-app-with-cicd-vsts

https://mohitgoyal.co/2 019/01/10/run-azure-devops-private-agents-in-kubernetes-clusters/

The first thing to do is to declare your Sonar Qube server as a service endpoint in your VSTS/DevOps project settings.

References: https://docs.sonarqube.org/display/SCAN/Analyzing+with+SonarQube+Extension+for+vsts-TFS

Scenario: Implement Project4 and configure the project to push Docker images to Azure Container Registry.

You use Azure Container Registry Tasks commands to quickly build, push, and run a Docker container image natively within Azure, showing how to offload your "inner-loop" development cycle to the cloud. ACR Tasks is a suite of features within Azure Container Registry to help you manage and modify container images across the container lifecycle.

References:

https://do cs.microsoft.com/en-us/azure/container-registry/container-registry-quickstart-task-cli