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| Section | Objectives |
|---|---|
| Topic 1: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 2: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Connect to and consume Azure services | - Integrate Azure services
|
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NEW QUESTION # 87
You are building a multi-agent solution in Azure AI Foundry where one agent handles scheduling and another handles billing questions, and a request may need both. What should you implement?
Answer: C
Explanation:
Multi-agent orchestration patterns use a coordinating (orchestrator) agent to decompose a request, delegate sub-tasks to specialized agents, and aggregate their outputs -- this is more maintainable and accurate than one broad prompt or model trying to cover disparate domains.
NEW QUESTION # 88
You are deploying a model in Azure AI Foundry and must ensure the endpoint can handle unpredictable bursts of traffic while keeping cost low during idle periods.
Which deployment type should you choose?
Answer: A
Explanation:
Choose a Standard pay-as-you-go deployment . Microsoft Foundry documentation identifies Standard deployments as appropriate for low-to-medium volume workloads with high burstiness . Standard uses pay-per-token billing , so charges are based on actual inference consumption rather than continuously reserved model capacity. This makes it well suited to workloads whose traffic varies significantly and may have long idle periods.
By contrast, Provisioned Throughput Units (PTUs) reserve model-processing capacity and are designed for sustained, predictable high-throughput workloads where consistent latency is important. Microsoft states that PTUs are billed based on deployed capacity even when that capacity is not actively serving requests.
Consequently, PTU deployments can be economically inefficient when the endpoint is frequently idle or traffic is highly variable.
A Batch deployment is optimized for asynchronous, non-latency-sensitive processing and is not appropriate for an interactive endpoint receiving unpredictable live traffic. Dedicated managed compute with fixed capacity introduces continuously allocated infrastructure and therefore does not align with the requirement to minimize idle-period cost.
Microsoft also recommends Standard or Global Standard for variable, bursty traffic , while provisioned types are recommended for consistent high-volume workloads.
Study Guide references: Microsoft Foundry Models # Standard deployments; pay-per-token billing; bursty workloads; provisioned throughput; batch processing.
NEW QUESTION # 89
Hotspot Question
You plan to deploy a web app to App Service on Linux. You create an App Service plan. You create and push a custom Docker image that contains the web app to Azure Container Registry.
You need to access the console logs generated from inside the container in real-time.
How should you complete the Azure CLI command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: config
Modifies the logging configuration settings for the specified Web App.
Box 2: --docker-container-logging
--docker-container-logging: The explicit parameter that defines where or how Docker container console logs are saved (e.g., filesystem).
Configure Logging:
az webapp log config --name ContosoWeb --resource-group ContosoDevRg --web-server-logging filesystem Box 3: webapp webapp specifies the group identifier within the az CLI execution context.
Box 4: tail
tail: Initiates a live, real-time diagnostic log stream directly from the active Linux container.
Reference:
https://learn.microsoft.com/en-gb/answers/questions/2225551/mis-show-azure-container-app-logs
NEW QUESTION # 90
You need to secure an Azure OpenAI resource so that it is only reachable from your virtual network and not from the public internet. What should you configure?
Answer: A
Explanation:
Private Link/private endpoints assign the Azure OpenAI resource a private IP within your VNet and allow disabling public network access, ensuring traffic stays on the Microsoft backbone network and isn't reachable from the public internet.
NEW QUESTION # 91
Hotspot Question
You develop an application that sells AI generated images based on user input. You recently started a marketing campaign that displays unique ads every second day.
Sales data is stored in Azure Cosmos DB with the date of each sale being stored in a property named 'whenFinished'.
The marketing department requires a view that shows the number of sales for each unique ad.
You need to implement the query for the view.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: count(c.whenFinished)
For the number of sales we need to use the count function.
Box 2: DateTimeBin(c.whenFinished, 'day', 2)
Box 3: DateTimeBin(c.whenFinished, 'day', 2)
Reference:
https://learn.microsoft.com/en-us/cosmos-db/query/datetimebin
NEW QUESTION # 92
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