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| Section | Objectives |
|---|---|
| Topic 1: Implement Azure AI solutions | - Implement natural language processing solutions - Implement computer vision solutions - Implement generative AI solutions using Azure OpenAI - Implement knowledge mining with Azure AI Search |
| Topic 2: Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
| Topic 3: Plan and manage Azure AI solutions | - Select appropriate Azure AI services - Plan security and compliance requirements - Monitor and optimize AI solutions |
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NEW QUESTION # 115
You have an Event Grid subscription that triggers an Azure Function.
You need to prevent loss of events in case the endpoint returns an HTTP 400 response.
Which action should you perform?
Answer: D
Explanation:
Configuring a dead-letter destination is exactly the right step to take.
By default, when an endpoint returns an HTTP 400 (Bad Request) or HTTP 413 (Payload Too Large) response, Azure Event Grid immediately stops delivery attempts and drops the message.
It treats these specific errors as non-transient, client-side issues, meaning it skips its standard 24- hour retry policy.
Configuring a dead-letter destination ensures that these dropped events are safely preserved for future troubleshooting and reprocessing.
Reference:
https://turbo360.com/blog/azure-event-grid-dead-letter-monitoring
NEW QUESTION # 116
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Store the API key as a GitHub repository secret.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* Store the API key in Azure Key Vault and reference it from an App Service application setting.
Storing the API key in Azure Key Vault and referencing it via App Service application settings is the recommended, secure approach. This strategy completely removes sensitive credentials from your GitHub repository and Git commit history while injecting them safely into your container environment at runtime.
Incorrect:
* Embed the API key as a hardcoded environment variable in the Dockerfile.
* Store the API key as a GitHub repository secret.
Reference:
https://www.qservicesit.com/full-stack-applications-on-azure
NEW QUESTION # 117
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You are using Azure Monitor Application Insights to investigate a production API. You open the Logs blade and set the time range to Last 24 hours.
An engineer recommends the following query to count requests by result code and sort the results from most frequent to least frequent:
requests
| summarize request_count = count() by resultCode
| order by request_count desc
You need to determine whether the query returns the number of requests grouped by result code and sorted from most to least frequent.
Solution: The query lists every individual request along with its result code.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* The query returns one row per unique resultCode value with the number of requests in each group.
The Kusto Query Language (KQL) query uses the summarize operator, which acts as a grouping and aggregation mechanism.
summarize request_count = count() by resultCode
This groups all the individual rows in the requests table by their unique resultCode. It then counts the total number of logs within each group and places that value into a new column called request_count.
order by request_count desc: This sorts those aggregated rows so that the resultCode with the highest number of requests appears at the top.
Incorrect:
* The result codes are sorted alphabetically.
* The query lists every individual request along with its result code.
Reference:
https://learn.microsoft.com/en-us/azure/azure-monitor/reference/tables/apprequests
NEW QUESTION # 118
A container in an AKS cluster repeatedly restarts.
Pod events show probe failures, although node-level CPU and memory metrics are normal.
You need to diagnose the cause of the repeating restarts.
What should you do first?
Answer: D
Explanation:
Inspecting the pod events and container logs is the correct first action to take.
Because node-level metrics are normal, the issue is isolated to the specific workload or its individual container boundaries. Pod events will clarify exactly which health probe (liveness or readiness) is triggering the restart, and the logs will reveal why the application inside the container is failing to respond.
Reference:
https://aws.plainenglish.io/why-your-kubernetes-pod-is-crashing-and-how-to-fix-it-5c71f8d2779a?gi=a46b335270ff
NEW QUESTION # 119
You are developing an AI application. The application configuration will depend on a dynamically retrieved value of a designated key stored in an Azure App Configuration resource.
You must deploy the application to the test, staging, and production environments.
You need to be able to set the value differently in each environment.
Which feature of Azure App Configuration resource should you use?
Answer: A
Explanation:
You should use the Label feature of the Azure App Configuration resource.
In Azure App Configuration, keys can optionally include a label, which acts as a dimension or tag to create distinct variants of the same key. This allows you to store environment-specific values (such as test, staging, and production) under a single key name and load the appropriate configuration dynamically based on the current deployment environment.
References:
https://learn.microsoft.com/en-us/answers/questions/2108879/azure-app-configuration-resource-manager-api-is-de
NEW QUESTION # 120
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