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Free AZ-400 Exam Braindumps (page: 24)

Page 23 of 128
PDF with 556 Questions

You have an Azure DevOps organization named Contoso and an Azure subscription. The subscription contains an Azure virtual machine scale set named VMSS1 and an Azure Standard Load Balancer named LB1. LB1 distributes incoming requests across VMSS1 instances.

You use Azure DevOps to build a web app named App1 and deploy App1 to VMSS1. App1 is accessible via HTTPS only and configured to require mutual authentication by using a client certificate.
You need to recommend a solution for implementing a health check of App1. The solution must meet the following requirements:
-Identify whether individual instances of VMSS1 are eligible for an upgrade operation.
-Minimize administrative effort.

What should you include in the recommendation?

  1. an Azure Load Balancer health probe
  2. Azure Monitor autoscale
  3. the Custom Script Extension
  4. the Application Health extension

Answer(s): D

Explanation:

Monitoring your application health is an important signal for managing and upgrading your deployment. Azure virtual machine scale sets provide support for rolling upgrades including automatic OS-image upgrades, which rely on health monitoring of the individual instances to upgrade your deployment.
You can also use health extension to monitor the application health of each instance in your scale set and perform instance repairs using automatic instance repairs.


Reference:

https://docs.microsoft.com/en-us/azure/virtual-machine-scale-sets/virtual-machine-scale-sets-health-extension



HOTSPOT (Drag and Drop is not supported)
You have an application named App1 that has a custom domain of app.contoso.com. You create a test in Azure Application Insights as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box 1: every five minutes at a random location
Test frequency: Sets how often the test is run from each test location. With a default frequency of five minutes and five test locations, your site is tested on average every minute.

Box 2:
Parse dependent requests: Test requests images, scripts, style files, and other files that are part of the web page under test. The recorded response time includes the time taken to get these files. The test fails if any of these resources cannot be successfully downloaded within the timeout for the whole test.


Reference:

https://docs.microsoft.com/en-us/azure/azure-monitor/app/monitor-web-app-availability



You have a build pipeline in Azure Pipelines that occasionally fails.

You discover that a test measuring the response time of an API endpoint causes the failures. You need to prevent the build pipeline from failing due to the test.
Which two actions should you perform? Each correct answer presents part of the solution.

NOTE: Each correct selection is worth one point.

  1. Set Flaky test detection to Off.
  2. Clear Flaky tests included in test pass percentage.
  3. Enable Test Impact Analysis (TIA).
  4. Manually mark the test as flaky.
  5. Enable test slicing.

Answer(s): B,D

Explanation:

D: You can mark or unmark a test as flaky based on analysis or context, by choosing Flaky.
To configure flaky test management, choose Project settings, and select Test management in the Pipelines section.
B:
Slide the On/Off button to On.


Reference:

https://docs.microsoft.com/en-us/azure/devops/pipelines/test/flaky-test-management



Your company hosts a web application in Azure. The company uses Azure Pipelines for the build and release management of the application. Stakeholders report that the past few releases have negatively affected system performance.
You configure alerts in Azure Monitor.

You need to ensure that new releases are only deployed to production if the releases meet defined performance baseline criteria in the staging environment first.

What should you use to prevent the deployment of releases that fall to meet the performance baseline?

  1. an Azure Scheduler job
  2. a trigger
  3. a gate
  4. an Azure function

Answer(s): C

Explanation:

Scenarios and use cases for gates include:
Quality validation. Query metrics from tests on the build artifacts such as pass rate or code coverage and deploy only if they are within required thresholds.

Use Quality Gates to integrate monitoring into your pre-deployment or post-deployment. This ensures that you are meeting the key health/performance metrics (KPIs) as your applications move from dev to production and any differences in the infrastructure environment or scale is not negatively impacting your KPIs.

Note: Gates allow automatic collection of health signals from external services, and then promote the release when all the signals are successful at the same time or stop the deployment on timeout. Typically, gates are used in connection with incident management, problem management, change management, monitoring, and external approval systems.


Reference:

https://docs.microsoft.com/en-us/azure/azure-monitor/continuous-monitoring https://docs.microsoft.com/en-us/azure/devops/pipelines/release/approvals/gates?view=azure-devops






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