AZ-400 Questions and Answers

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.

Every request made against a storage service must be authorized, unless the request is for a blob or container resource that has been made available for public or signed access. One option for authorizing a request is by using Shared Key.

Scenario: The mobile applications must be able to call the share pricing service of the existing retirement fund management system. Until the system is upgraded, the service will only support basic authentication over HTTPS.

The investment planning applications suite will include one multi-tier web application and two iOS mobile application. One mobile application will be used by employees; the other will be used by customers.

Box 1: Reader

Members of a group named Developers must be able to install packages.

Feeds have four levels of access: Owners, Contributors, Collaborators, and Readers. Owners can add any type of identity-individuals, teams, and groups-to any access level.

Box 2: Owner

Members of a group named Team Leaders must be able to create new packages and edit the permissions of package feeds.

Scenario: Visual Studio App Center must be used to centralize the reporting of mobile application crashes and device types in use.

In order to use App Center, you need to opt in to the service(s) that you want to use, meaning by default no services are started and you will have to explicitly call each of them when starting the SDK.

Insert the following line to start the SDK in your app ' s App Delete class in the didFinishLaunchingWithOptions method.

MSAppCenter.start( " {Your App Secret} " , withServices: [MSAnalytics.self, MSCrashes.self])

Every request made against a storage service must be authorized, unless the request is for a blob or container resource that has been made available for public or signed access. One option for authorizing a request is by using Shared Key.

Scenario: The mobile applications must be able to call the share pricing service of the existing retirement fund management system. Until the system is upgraded, the service will only support basic authentication over HTTPS.

The investment planning applications suite will include one multi-tier web application and two iOS mobile application. One mobile application will be used by employees; the other will be used by customers.

Box 1: A source control system

A source control system, also called a version control system, allows developers to collaborate on code and track changes. Source control is an essential tool for multi-developer projects.

Box 2: A hosted service

To build and deploy Xcode apps or Xamarin.iOS projects, you ' ll need at least one macOS agent. If your pipelines are in Azure Pipelines and a Microsoft-hosted agent meets your needs, you can skip setting up a self-hosted macOS agent.

Scenario: The investment planning applications suite will include one multi-tier web application and two iOS mobile applications. One mobile application will be used by employees; the other will be used by customers.

Unattended config:

The agent can be set up from a script with no human intervention. You must pass --unattended and the answers to all questions.

To configure an agent, it must know the URL to your organization or collection and credentials of someone authorized to set up agents. All other responses are optional.

The commit-msg hook is invoked by git-commit and git-merge, and can be bypassed with the --no-verify option.

Box 1: Get-AzResource

Use the following command to examine the access control mode for all workspaces in the subscription:

PowerShell

Get-Az Resource –Resource Type Microsoft. Operational Insights/workspaces –Expand Properties | for each {s.Name + " : " + $_.Properties.features.enableLogAccessUsingOnlyResourcePermissions

Box 2: -Resource Type

SonarQube is a set of static analyzers that can be used to identify areas of improvement in your code. It allows you to analyze the technical debt in your project and keep track of it in the future. With Maven and Gradle build tasks, you can run SonarQube analysis with minimal setup in a new or existing Azure DevOps Services build task.

SonarQube is a set of static analyzers that can be used to identify areas of improvement in your code. It allows you to analyze the technical debt in your project and keep track of it in the future. With Maven and Gradle build tasks, you can run SonarQube analysis with minimal setup in a new or existing Azure DevOps Services build task.

" Build and test with a multi-stage Dockerfile: build and tests execute inside the container using a multi-stage Docker file, as such test results are not published back to the pipeline. " https://docs.microsoft.com/en-us/azure/devops/pipelines/tasks/test/p ublish-test-results?view=azure- devops & tabs=trx% 2Cyaml

App1 Canary and App2 rolling

App1 Canary would minimize app downtime for the first app, as it would only deploy new code when the canary has confirmed that it is functional - and if there are any issues, it would roll back to the previous version of the code.

App2 rolling would be the second option, as it would allow for frequent deployments of new code, while still giving the developers enough time to fix any issues that may have been introduced during new code deployments.

A task group in Azure DevOps is a collection of tasks that can be reused across multiple pipelines. You can create a task group that contains the three specific tasks that you need to execute during pipeline execution, and then reference that task group in all new pipelines in Project1. This way, you can ensure that the three specific tasks are executed in all new pipelines without having to manually add them to each pipeline.

You can create a service hook for Azure DevOps Services and TFS with Jenkins.

Performing user interface (UI) testing as part of the release pipeline is a great way of detecting unexpected changes, and need not be difficult. Selenium can be used to test your website during a continuous deployment release and test automation.

Instead implement continuous integration.

Note: WhiteSource is the leader in continuous open source software security and compliance management. WhiteSource integrates into your build process, irrespective of your programming languages, build tools, or development environments. It works automatically, continuously, and silently in the background, checking the security, licensing, and quality of your open source components against WhiteSource constantly-updated definitive database of open source repositories.

Box 1: requests

Failed requests (requests/failed):

The count of tracked server requests that were marked as failed.

Kusto code:

requests

| where success == ' False '

Box 2: success == false

You can configure a Conditional Access policy that requires MFA for access from untrusted networks.

A feature typically represents a shippable component of software.

Features, examples:

Add view options to the new work hub

Add mobile shopping cart

Support text alerts

Refresh the web portal with new look and feel

User Stories and Tasks are used to track work. Teams can choose how they track bugs, either as requirements or as tasks

Woodgrove Bank plans to implement the following changes to the DevOps environment:

Migrate all the source code from TFS1 to GitHub.

The Git-TFS tool is a two-way bridge between Team Foundation Version Control and Git, and can be used to perform a migration.

Scenario: Deploy App2 to an Azure virtual machine named VM1.

A personal access token (PAT) is used as an alternate password to authenticate into Azure DevOps.

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Woodgrove Bank identifies the following technical requirements:

The Azure DevOps dashboard must display the metrics shown in the following table:

Box 1: Velocity

Velocity displays your team velocity. It shows what your team delivered as compared to plan.

Box 2: Release pipeline overview

Release pipeline overview shows the status of environments in a release definition.

Box 3: Query tile

Query tile displays the total number of results from a query.

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Box 1: Azure Boards

Azure Boards can be used to track work with Kanban boards, backlogs, team dashboards, and custom reporting

You can create multiple Trello boards, which are spaces to store tasks (for different work contexts, or even private boards)

You can easily share Trello boards with another person.

Box 2: Azure Pipelines

You can use Bamboo to implement CI/CD (Continuous Integration and Continuous Delivery) for a simple Azure function app using Atlassian Bamboo. Bamboo does continuous delivery of the project from source code to deployment. It has stages including Build, Test and Deploy.

Software teams in every industry are upgrading their continuous delivery pipeline with Bamboo. Easy build import from popular open source tools, user and group import from JIRA, seamless integration with Bitbucket, and native support for Git, Hg, and SVN means you ' ll be building and deploying like a champ.

Box 3: GitHub repositories

Bitbucket can be used as the Git repository, but you can use any other Git repository (Like TFS Git) for source control of the code.

Scenario: Access to Azure DevOps must be restricted to specific IP addresses.

Azure DevOps is authenticated through Azure Active Directory. You can use Azure AD ' s conditional access to prevent logins from certain geographies and address ranges.

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Setting 1: Threshold value

Set to 80 %

Scenario: An Azure Monitor alert for VM1 must be configured to meet the following requirements:

Be triggered when average CPU usage exceeds 80 percent for 15 minutes.

Calculate CPU usage averages once every minute.

Setting 2: Aggregation granularity

Set to 15 minutes.

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

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.

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.

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.

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.

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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.

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Woodgrove Bank plans to implement the following changes to the identity environment:

Configure App1 to use a service principal.

Scenario:

The Register-AzureRmAutomationDscNode cmdlet registers an Azure virtual machine as an APS Desired State Configuration (DSC) node in an Azure Automation account.

Scenario: The Azure DevOps organization includes:

The Docker extension

A deployment pool named Pool7 that contains 10 Azure virtual machines that run Windows Server 2016

To create an instance of Azure Application Insights namedaz400-38443478-mainand configure it to receive telemetry data from an Azure web app with the same name, you’ll need to follow these steps:

Create a Log Analytics Workspace:

Go to theAzure Portal.

Search for Log Analytics Workspaces and select Add.

Select a Subscription and either use an existing Resource Group or create a new one.

Provide a unique name for your Log Analytics workspace.

Choose the Region that is appropriate for you.

Review the settings and then selectCreate1.

Create an Azure Application Insights Instance:

In the Azure Portal, navigate to Application Insights.

Click on + Create.

Fill in the instance details, ensuring the name isaz400-38443478-main.

Link the instance to the Log Analytics workspace you created in the previous step.

Review and create the Application Insights instance2.

Configure the Azure Web App to Send Telemetry Data:

Go to the Azure Web Appaz400-38443478-main.

Under Monitoring, selectApplication Insights.

Choose to use an existing resource and select the Application Insights instance you created.

Follow the prompts to set up the connection, which may involve adding the appropriate SDK to your web app and configuring the connection string or instrumentation key.

Verify Telemetry Data Reception:

After setting up, send some test traffic to your web app.

Then, go to the Application Insights instance and check the Overview or Performance sections to see if telemetry data is being received.

Remember to replace placeholder names with the actual names of your resources where necessary. These steps will help you set up Azure Application Insights to monitor your web app effectively.

anation:

1. In the Azure portal, navigate to the az400-9940427-main app ' s management page. In the app ' s left menu, click Configuration > Application settings.

2. Click New Application settings

3. Enter the following:

Name: MAX_ITEMS

Value: 50

To configure your Azure Functionaz400-38443478-functto 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 theAzure/functions-actionto deploy to your Azure Function App.

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

Generate Deployment Credentials:

In the Azure Portal, navigate to your Function Appaz400-38443478-funct.

Download the publish profile from theOverviewsection by clicking onGet publish profile.

Store the Publish Profile as a GitHub Secret:

In your GitHub repository, go toSettings > 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 theapp-namewith the name of your Azure Function App and ensure the Python version and dependencies match your application’s requirements.

By following these steps, yourAzure 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.

To enable streaming of diagnostic telemetry for asingle or a pooled database, follow these steps:

1. Go to Azure SQL database resource.

2. Select Diagnostics settings.

3. Select Turn on diagnostics if no previous settings exist, or select Edit setting to edit a previous setting. You can create up to three parallel connections to stream diagnostic telemetry.

4. Select Add diagnostic setting to configure parallel streaming of diagnostics data to multiple resources.

5. Enter a setting name for your own reference.

6. Select a destination resource for the streaming diagnostics data: Archive to storage account, Stream to an event hub, or Send to Log Analytics.

7. For the standard, event-based monitoring experience, select the following check boxes for database diagnostics log telemetry: Query Store Runtime Statistics

8. For an advanced, one-minute-based monitoring experience, select the check box for Basic metrics.

9. Select Save.

Step 1: Access Azure DevOps

Open your browser and navigate to https://aex.dev.azure.com .

You will be prompted to sign in. Enter the following credentials:

Username: UserUser1-48901628@cxamUsers.com

Password: aFpJ2j-6M!

Click Next or Sign in to proceed.

Note: If you see any Microsoft security challenge (like phone or email verification), follow the instructions to complete it.

Step 2: Sign Up for Azure DevOps

After signing in, you’ll see a prompt to sign up for Azure DevOps.

Use the default settings provided by Azure DevOps for the sign-up process (region, default name, etc.).

Click Continue or Start free with Azure DevOps.

An Azure DevOps Organization is a container for your projects and resources. Default settings are usually fine for new organizations.

Step 3: Create the Organization

Enter a name for your organization. Azure DevOps will suggest a default name (like yourname or org-name), but you can change it if you prefer.

Verify the region is correct.

Click Continue to create the organization.

Your Azure DevOps organization is now created. It’s the top-level container for all your projects.

Step 4: Create a Private Project Named Project1

In your Azure DevOps portal, find the " New Project " button and click it.

Enter the following details:

Project Name: Project1

Description: (optional)

Visibility: Private

Click Create.

A private project means that only users you add can see or access it. This is important for security and privacy.

Step 5: Enforce Maximum File Size for Repositories

By default, Azure DevOps allows files up to 100 MB to be pushed. To ensure the maximum file size for repositories in Project1 is 2 MB, you can enforce this using a pipeline validation.

Azure DevOps does not provide a direct setting for file size limits. However, you can create a pipeline to validate file size on pull requests and block changes if a file exceeds 2 MB.

Here’s how to do it:

Option 1: Enforce with a pipeline validation for pull requests

In your Project1, create a new pipeline.

Use the following YAML for the pipeline:

yaml

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trigger: none

pr:

branches:

include:

- " * "

jobs:

- job: CheckFileSize

pool:

vmImage: ' ubuntu-latest '

steps:

- script: |

echo " Checking file sizes in the PR... "

git fetch origin +refs/pull/*/merge:refs/remotes/origin/pr/*

large_files=$(git diff --cached --name-only | xargs -I{} du -b {} | awk ' $1 > 2097152 {print $2} ' )

if [ -n " $large_files " ]; then

echo " Error: The following files exceed 2 MB: "

echo " $large_files "

exit 1

fi

displayName: ' Check file sizes in PR '

This pipeline will:

Run on pull requests only.

Check the size of all files in the pull request.

If any file is larger than 2 MB (2,097,152 bytes), it will fail the pipeline and block the PR.

Option 2: Local Git configuration (for each developer)

On each developer’s machine, run this command in their local repository:

bash

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git config --local core.bigFileThreshold 2M

This limits the file threshold for checkout, but does not prevent large files from being pushed. Using the pipeline validation (Option 1) is more secure for team environments.

Task 6: Create a Service Connection for Resource Group Deployment using Managed Identity and Workload Identity Federation

Step 1: Understand the Requirements

You want to deploy resources in the RGHod489Q1628 resource group.

The service connection must:

Use the ManagedJd1 managed identity.

Use workload identity federation (OIDC-based authentication for enhanced security).

Step 2: Verify Prerequisites

You need to ensure:

The ManagedJd1 managed identity exists in your Azure subscription.

Your Azure DevOps project (Project1) is linked to an Azure Active Directory tenant (for OIDC support).

You have the Owner or User Access Administrator role on the RGHod489Q1628 resource group.

Step 3: Assign Role to Managed Identity

Go to the Azure Portal .

In the search bar, type Managed Identities and select Managed Identities .

Locate and click on the ManagedJd1 identity.

In the left menu, click Azure role assignments .

Click + Add role assignment .

Set the following:

Scope: Resource Group

Subscription: Your subscription

Resource Group: RGHod489Q1628

Role: Contributor (or appropriate role)

Click Save .

This step ensures ManagedJd1 has permissions to deploy resources to RGHod489Q1628.

Step 4: Create a Federated Credential for Workload Identity Federation

In the Azure Portal, navigate to the ManagedJd1 managed identity.

In the left menu, click Workload identity federation (preview).

Click + Add a federated credential .

Configure as follows:

Federated credential name: devops-oidc

Issuer: https://vstoken.actions.githubusercontent.com (or use the default https://pipelines.actions.githubusercontent.com for Azure DevOps)

Subject identifier: Use the following format for Azure DevOps:

css

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system:azuredevops:{organizationName}:{projectName}

For example:

css

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system:azuredevops:{YourOrganizationName}:{Project1}

Audience: api://AzureADTokenExchange

Click Add .

This federated credential establishes trust between your Azure DevOps project and the managed identity.

Step 5: Create a Service Connection in Azure DevOps

Go to your Azure DevOps project (Project1) in the browser.

In the left menu, click Project settings .

Under Pipelines , click Service connections .

Click New service connection .

Choose Azure Resource Manager .

Choose the authentication method:

Select Workload identity federation .

Configure the service connection:

Scope level: Resource Group.

Resource Group: RGHod489Q1628.

Subscription: Your subscription.

Authentication method: Managed Identity with workload identity federation.

Managed Identity: Enter the client ID or select ManagedJd1.

Service connection name: e.g., Project1-RGHod489Q1628-Conn.

Grant access permission to all pipelines (recommended).

Click Save .

Step 6: Validate the Service Connection

After creation, click on the new service connection to Verify it.

Ensure the connection test is successful .

You can now use this service connection in your pipelines for deploying resources to RGHod489Q1628.

1. Open Microsoft Azure Portal

2. Log intoyour Azure account and go to App Service and look under Monitoring then you will see Alert.

3. Select Add an alert rule

4. Configure the alert rule as per below and click Ok.

Source: Alert on Metrics

Resource Group: az400-9940427-main

Resource: az400-9940427-main

Threshold: 5

Period: Over the last 5 minutes

Webhook: https://contoso.com/notify

Enable Remote Debugging

Before we start a debugging session to our Azure Function app we need to enable the functionality.

Navigate in the Azure portal to your function app fa-11566895

Go to the “Application settings”

Under “Debugging” set Remote Debugging to On and set Remote Visual Studio version to 2017.

1.Go to the Azure portal, navigate to Traffic Manager profiles and click on the Add button to create a routing profile.

2. In the Create Traffic Manager profile, enter, or select these settings:

Name: az40011566895n1-tm

Routing method: Geographic

Resource group: RG1lod11566895

Note: Traffic Manager profiles can be configured to use the Geographic routing method so that users are directed to specific endpoints (Azure, External or Nested) based on which geographic location their DNS query originates from. This empowers Traffic Manager customers to enable scenarios where knowing a user’s geographic region and routing them based on that is important.

1. In Azure portal navigate to the az400-9940427-main app.

2. Scroll down to the Settings groupin the left navigation.

3. Select Managed identity.

4. Within the System assigned tab, switch Status to On. Click Save.

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Step 1: Navigate to Personal Access Tokens

Sign in to Azure DevOps:

Go to Azure DevOps and sign in with your credentials.

Access User Settings:

Click on your profile picture in the top right corner.

Select User settings.

Open Personal Access Tokens:

In the user settings menu, select Personalaccess tokens.

Step 2: Create a New Personal Access Token

Create a New Token:

Click on + New Token.

Configure the Token:

Name: Enter Token1.

Organization: Select the organization where you want to use the token.

Expiration: Set the expiration to 60 days.

Set Scopes:

Code: Select Read, Write, & Manage.

Build: Select Read & Execute.

Release: Select Read.

Create the Token:

Click on Create.

Step 3: Save the Token

Copy the Token:

Once the token is created, copy it immediately as it will not be displayed again.

Store the token in a secure location.

By following these steps, you will have successfully created a personal access token named Token1 with the specified capabilities and a 60-day expiration

Set up staging environments in Azure App Service

1. Open Microsoft Azure Portal

2. Log into your Azure account, select your app ' s resource page, in the left pane, selectDeployment slots > Add Slot.

3. In the Add a slot dialog box, give the slot a name, and select whether to clone an app configuration from another deployment slot. Select Add to continue.

4. After the slot is added, select Close to close the dialogbox. The new slot is now shown on the Deployment slots page. By default, Traffic % is set to 0 for the new slot, with all customer traffic routed to the production slot.

5. Select the new deployment slot to open that slot ' s resource page.

6. Change TRAFFIC % to 10

Step 1: Write the KQL Query

Open Azure Data Explorer:

Navigate to Azure Data Explorer and sign in with your credentials.

Access the Securitylogs Database:

Open the Securitylogs database.

Write the Query:

Use the following KQL query tocount the number of inbound requests for each source IP address:

InboundBrowsing

| where Timestamp between (datetime(2021-10-01) .. datetime(2021-12-31))

| summarize NumberOfRequests = count() by SourceIP

| project SourceIP, NumberOfRequests

Step 2: Export the Query Results

Run the Query:

Execute the query in Azure Data Explorer.

Export the Results:

Once the query results are displayed, click on the Export button.

Choose the export format (e.g., CSV) and specify the export path as C:\Samples.

By following these steps, you will have successfully written a KQL query to count the number of inbound requests for each source IP address during the last three months of 2021 and exported the results to C:\Samples

Step 1: Initialize the Default Main Branch

Navigate to Azure DevOps:

Go to Azure DevOps and sign in with your credentials.

Select Your Project:

Choose Project1 from your list of projects.

Initialize the Main Branch:

Go to Repos  >  Files.

If themain branch does not exist, you will see an option to initialize it. Click on Initialize and follow the prompts to create the main branch.

Step 2: Implement an Approval Process for the Main Branch

Navigate to Branch Policies:

Go to Repos  >  Branches.

Findthe main branch and click on the … (ellipsis) next to it.

Select Branch policies.

Enable Required Reviewers:

Under Policies, enable Minimum number of reviewers.

Set the minimum number of reviewers to 2 to enforce the four-eyes principle.

Add RequiredReviewers:

Add the users who should review the changes. Ensure that at least one approval is required on every iteration.

Enable Reset Code Reviewer Votes:

Enable the Reset code reviewer votes when there are new changes option to ensure that any new changes require re-approval.

Save Changes:

Click on Save changes to apply the policies.

Step 3: Verify the Approval Process

Create a Pull Request:

Make a change in a branch and create a pull request to merge it into the main branch.

Review and Approve:

Ensurethat the pull request requires at least two reviewers to approve it before it can be merged.

By following these steps, you will have successfully initialized themain branch and implemented an approval process that adheres to the four-eyes principle, ensuring that every iteration has at least one approval

Step 1: Understand the Requirements

You need to create a self-hosted agent for Azure Pipelines.

It will be hosted in a pod (for example, in Kubernetes).

All pipelines in Project1 should be able to use this agent pool named Pool1 .

Step 2: Create the Agent Pool in Azure DevOps

Go to your Azure DevOps organization : https://dev.azure.com/{YourOrganizationName}

In the bottom-left corner, click on the Organization settings gear icon.

In the left menu, click on Agent pools .

Click on Add pool .

Provide the following:

Pool name: Pool1

Pool type: Self-hosted

Grant access permission to all pipelines: Checked (so that all Project1 pipelines can use this pool)

Click Create .

Now you have an empty agent pool named Pool1 .

Step 3: Prepare the Self-hosted Agent as a Pod

You need to deploy an Azure Pipelines agent container as a pod . Here’s how to do it:

Option 1: Using Kubernetes directly (YAML deployment)

Create a Kubernetes deployment YAML file for the agent pod:

apiVersion: apps/v1

kind: Deployment

metadata:

name: azure-pipelines-agent

labels:

app: azure-pipelines-agent

spec:

replicas: 1

selector:

matchLabels:

app: azure-pipelines-agent

template:

metadata:

labels:

app: azure-pipelines-agent

spec:

containers:

- name: agent

image: mcr.microsoft.com/azure-pipelines/vsts-agent:latest

env:

- name: AZP_URL

value: " https://dev.azure.com/{YourOrganizationName} "

- name: AZP_TOKEN

valueFrom:

secretKeyRef:

name: azure-pipelines-token

key: token

- name: AZP_POOL

value: " Pool1 "

- name: AZP_AGENT_NAME

value: " agent-pod "

Create a Kubernetes secret for the personal access token (PAT) :

kubectl create secret generic azure-pipelines-token --from-literal=token= < your-PAT >

Note:

Replace < your-PAT > with a PAT that has “Agent Pools (Read & manage)” scope.

Replace {YourOrganizationName} with your actual Azure DevOps organization.

Deploy the pod:

bash

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kubectl apply -f azure-pipelines-agent.yaml

Step 4: Validate the Agent Connection

Go back to Organization Settings > Agent pools > Pool1 in Azure DevOps.

You should see the agent pod connected and listed as online .

Step 5: Use the Pool in Pipelines

By default, all pipelines in Project1 will now have access to the Pool1 agent pool because you granted access during the pool creation.

In your pipeline YAML files, specify the pool name to use the self-hosted agent:

yaml

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pool:

name: Pool1

1. Sign in to the portal,

2. Choose template Deploy-lod9940427

3. Select Edit template, andthen paste your JSON template code into the code window.

4. Change the ASddressPrefixes to 10.0.0.0/24 in order to support only 256 total IP addresses.

addressSpace " :{ " addressPrefixes " : [ " 10.0.0.0/24 " ]},

5. Change the firstSubnet addressprefix to 10.0.0.0/26 to support only 64 total IP addresses.

" subnets " :[

{

" name " : " firstSubnet " ,

" properties " :{

" addressPrefix " : " 10.0.0.0/24 "

}

6. Select Save.

7. Select Editparameters, provide values for the parameters that are shown, and then select OK.

8 Select Subscription. Choose the subscription you want to use, and then select OK.

9. Select Resource group. Choose an existing resource group or create a new one, and then select OK.

10. Select Create. A new tile on the dashboard tracks the progress of your template deployment.

To ensure that your Azure Web App namedaz400-38443478-mainsupports rolling upgrades and only 10 percent of users connect to the updated version of the app, you can use deployment slots with the followingsteps:

Create a Deployment Slot:

Navigate to the Azure Portal.

Go to your Web Appaz400-38443478-main.

SelectDeployment slotsin the menu.

Click onAdd 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 forTraffic %.

Set the traffic percentage to10%for thestagingslot1.

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

Deploy the Updated App to the Staging Slot:

Deploy yourupdated application to thestagingslot.

Test the application in thestagingslot to ensure it’s working as expected.

Complete the Rolling Upgrade:

Once you’re satisfied with the performance and stability of the app in thestagingslot, you can graduallyincrease the percentage of traffic until you’re ready to swap with the production slot.

To swap slots, go to theDeployment slotsmenu and click onSwapwith 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.

1. Open Microsoft Azure Portal

2. Log into your Azure account, select App Services in the Azure portal left navigation, and then select configureaz400-9940427-func1.

3. On the app page, select Deployment Center in the left menu.

4. On the Build provider page, select Azure Pipelines (Preview), and then select Continue.

5. On the Configure page, in the Code section:

For GitHub, drop down and select the Organization, Repository, and Branch you want to deploy continuously.

6. Select Continue.

7. On the Test page, choose whether to enable load tests, and then select Continue.

8. Depending on your App Service plan pricing tier, you may see a Deployto staging page. Choose whether to enable deployment slots, and then select Continue.

9. After you configure the build provider, review the settings on the Summary page, and then select Finish.

Step 1: Create an instance of Azure Application Insights

1. Open Microsoft Azure Portal

2. Log into your Azure account, Select Create a resource > Developer tools > Application Insights.

3. Enter the following settings, and then select Review + create.

Name: az400-9940427-main

Step 2: Configure App Insights SDK

4. Open your ASP.NET Core Web App project in Visual Studio > Right-click on the AppName in theSolution Explorer > Select Add > Application Insights Telemetry.

5. Click the Get Started button

6. Select your account and subscription > Select the Existing resource you created in the Azure portal > Click Register.

To ensure that your Azure Web App namedaz400-38443478-maincan retrieve secrets from an Azure Key Vault namedaz400-3844J478-kv1using a system managed identity with the principle of least privilege, follow these detailed steps:

Enable a System Managed Identity for the Azure Web App:

Navigate to the Azure Portal.

Go to the Azure Web Appaz400-38443478-main.

SelectIdentityunder theSettingssection.

In theSystem assignedtab, switch theStatustoOn.

ClickSaveto apply the changes.

Grant the Web App Access to the Key Vault:

Go to the Azure Key Vaultaz400-3844J478-kv1.

SelectAccess policiesunder theSettingssection.

Click onAdd Access Policy.

ChooseSecret permissionsand selectGetandList. This grants the app the ability to read secrets, adhering to the principle of least privilege.

Click onSelect principal, search for your Web App nameaz400-38443478-main, and select it.

ClickAddto add the policy.

Don’t forget to clickSaveto save the access policy changes.

Retrieve Secrets in the Web App Code:

In your Web App’s code, use the Azure SDK to retrieve the secrets.

For example, in a .NET application,you can use theAzure.IdentityandAzure.Security.KeyVault.Secretsnamespaces.

Utilize theDefaultAzureCredentialclass which will automatically use the system managed identity when running on Azure.

using Azure.Identity;

usingAzure.Security.KeyVault.Secrets;

var client = new SecretClient(new Uri( " https://az400-3844J478-kv1.vault.azure.net/ " ), new DefaultAzureCredential());

KeyVaultSecret secret = await client.GetSecretAsync( " my-secret-name " );

string secretValue =secret.Value;

Replace " my-secret-name " with the actual name of the secret you want to retrieve.

By following these steps, your Azure Web App will be able to securely retrieve secrets from the Azure Key Vault using a system managed identity, without needingto store credentials in the code, and adhering to the principle of least privilege. Remember to replace the placeholder names with the actual names of your Web App and Key Vault.