Microsoft AZ-400 Exam Questions

Step 1: Initialize the Default Main Branch

Navigate to Azure DevOps:

Go toAzure DevOpsand sign in with your credentials.

Select Your Project:

ChooseProject1from your list of projects.

Initialize the Main Branch:

Go toRepos>Files.

If the main branch does not exist, you will see an option to initialize it.Click onInitializeand follow the prompts to create the main branch1.

Step 2: Install the Microsoft Security DevOps Extension

Navigate to Extensions:

In Azure DevOps, click on theShopping Bagicon in the top right corner and selectBrowse Marketplace.

Search for the Extension:

Search forMicrosoft Security DevOps.

Install the Extension:

Click onGet it free.

Select your organization (User1-42147509) and clickInstall.

Follow the prompts to complete the installation2.

Step 3: Create a New Starter Pipeline

Navigate to Pipelines:

Go toPipelines>New pipeline.

Select the Repository:

ChooseAzure Repos Gitand select the relevant repository.

Configure the Pipeline:

SelectStarter pipelineand replace the default YAML with the following starter code:

trigger:

- starter

pool:

vmImage: 'windows-latest'

steps:

- task: MicrosoftSecurityDevOps@1

inputs:

command: 'run'

policy: 'azuredevops'

publish: true

Save the Pipeline:

Click onSaveand enterstarteras the branch name.

Click onSave and runto save the pipeline to the new branch namedstarter3.

By following these steps, you will have successfully initialized the main branch, installed the Microsoft Security DevOps extension, and created a new starter pipeline namedstarter1that includes the specified task

To ensure that your Azure Web App named az400-38443478-main supports rolling upgrades and only 10 percent of users connect to the updated version of the app, you can use deployment slots with the following steps:

Create a Deployment Slot:

Navigate to the Azure Portal.

Go to your Web App az400-38443478-main.

Select Deployment slots in the menu.

Click on Add Slot.

Name the slot (e.g., staging) and if needed, clone settings from the production slot.

Configure the Traffic Percentage:

In the Deployment Slots menu, you will see a column for Traffic %.

Set the traffic percentage to 10% for the staging slot1.

This will route only 10% of the traffic to the updated version of the app in the staging slot.

Deploy the Updated App to the Staging Slot:

Deploy your updated application to the staging slot.

Test the application in the staging slot to ensure it's working as expected.

Complete the Rolling Upgrade:

Once you're satisfied with the performance and stability of the app in the staging slot, you can gradually increase the percentage of traffic until you're ready to swap with the production slot.

To swap slots, go to the Deployment slots menu and click on Swap with the production slot.

By using deployment slots, you can achieve rolling upgrades with minimal administrative effort, as it allows you to test the new version on a subset of users before fully releasing it. Remember to adjust the traffic percentage and monitor the application's performance throughout the process.

To configure a virtual machine template in your DevTest Labs environment named az400-38443478-dtl1 with Windows Server 2016 Datacenter that includes the Selenium tool and the Google Chrome browser, follow these steps:

Create a Custom Image with Windows Server 2016 Datacenter:

In the Azure Portal, go to your DevTest Lab az400-38443478-dtl1.

Navigate to Configuration and policies > Custom images.

Use an existing VM or create a new one with Windows Server 2016 Datacenter.

After setting up the VM, capture it to create a custom image1.

Install Selenium and Google Chrome on the VM:

Connect to the VM via RDP.

Download and install the Selenium WebDriver for your preferred programming language from the official Selenium website2.

For Google Chrome, download the offline installer from the official website and install it on the VM3.

Generalize the VM:

Run the sysprep command to generalize the VM, which prepares it to be used as a template.

Shut down the VM after sysprep completes.

Capture the Generalized VM to Create a Template:

In the Azure Portal, navigate to the VM and select Capture.

Provide the required details and create the image.

Add Selenium and Google Chrome Artifacts to the Template:

Go back to the DevTest Lab az400-38443478-dtl1.

Select Artifacts and add Selenium and Google Chrome artifacts to the template.

Ensure these artifacts are configured to install during the VM creation process.

Create VMs from the Template:

Now, when you create a new VM in the DevTest Lab, select the custom image you created.

The VM will be provisioned with Windows Server 2016 Datacenter, and the Selenium tool and Google Chrome browser will be installed automatically.

By following these steps, you can ensure that all virtual machines created from this template in your DevTest Lab will have the required operating system, tools, and browser installed. Remember to replace placeholder names with the actual names of your resources where necessary.

To store signed images in an Azure Container Registry (ACR) instance and support your planned images while minimizing costs, you need to modify the SKU of your ACR instance to one that supports content trust and image signing. Here's how you can do it:

Determine the Appropriate SKU:

Content trust and image signing are features of the Premium service tier of Azure Container Registry1.

If cost minimization is a priority, ensure that the Premium tier is necessary for your use case. If you require content trust, the Premium tier is the appropriate choice.

Modify the SKU of the ACR Instance:

Navigate to the Azure Portal.

Go to your ACR instance az40038443478act1.

Select Update from the overview pane.

Choose the Premium SKU from the SKU drop-down menu2.

Review the changes and pricing, then save the configuration.

By upgrading to the Premium SKU, you'll be able to store signed images in your ACR instance. Remember to monitor your usage and costs to ensure they align with your budget and requirements.

To configure your Azure Function az400-38443478-funct to automatically update whenever new code is committed to the main branch of the specified GitHub repository, you can use GitHub Actions for continuous deployment. Here's how to set it up:

Create a GitHub Actions Workflow:

In your GitHub repository, navigate to the .github/workflows/ directory.

Create a new file for your workflow (e.g., azure-function-cd.yml).

Define the Workflow:

In the workflow file, define the steps for the build and deployment process.

Use the Azure/functions-action to deploy to your Azure Function App.

Set up triggers for the main branch to initiate the workflow on every commit.

Generate Deployment Credentials:

In the Azure Portal, navigate to your Function App az400-38443478-funct.

Download the publish profile from the Overview section by clicking on Get publish profile.

Store the Publish Profile as a GitHub Secret:

In your GitHub repository, go to Settings > Secrets and variables > Actions.

Create a new secret (e.g., AZURE_FUNCTIONAPP_PUBLISH_PROFILE) and paste the content of the publish profile.

Configure the Workflow to Use the Secret:

In the workflow file, reference the secret to authenticate the deployment to Azure.

Here's a sample GitHub Actions workflow snippet:

name: Deploy Azure Function

on:

push:

branches:

- main

jobs:

build-and-deploy:

runs-on: ubuntu-latest

steps:

- uses: actions/checkout@v2

- name: Set up Python version

uses: actions/setup-python@v2

with:

python-version: '3.x'

- name: Install dependencies

run: |

pip install -r requirements.txt

- name: Deploy to Azure Functions

uses: Azure/functions-action@v1

with:

app-name: az400-38443478-funct

publish-profile: ${{ secrets.AZURE_FUNCTIONAPP_PUBLISH_PROFILE }}

package: .

Replace the app-name with the name of your Azure Function App and ensure the Python version and dependencies match your application's requirements.

By following these steps, your Azure Function will automatically update whenever new code is pushed to the main branch of the GitHub repository. This setup minimizes manual effort and ensures that your function app is always running the latest code.