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| Section | Objectives |
|---|---|
| Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Develop containerized solutions on Azure | - Implement containerized applications
|
| Connect to and consume Azure services | - Integrate Azure services
|
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問題 #59
Drag and Drop Question
You are developing a serverless Java application on Azure. You create a new Azure Key Vault to work with secrets from a new Azure Functions application.
The application must meet the following requirements:
- Reference the Azure Key Vault without requiring any changes to the
Java code.
- Dynamically add and remove instances of the Azure Functions host
based on the number of incoming application events.
- Ensure that instances are perpetually warm to avoid any cold starts.
- Connect to a VNet.
- Authentication to the Azure Key Vault instance must be removed if the Azure Functions application is deleted.
You need to grant the Azure Functions application access to the Azure Key Vault.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
答案：
解題說明：
Explanation:
Step 1: Create the Azure Functions app with a Premium plan type
Perpetually Warm & VNet: The Premium plan type is the only serverless-scale hosting option that satisfies requirement 3 (keeping instances warm to eliminate cold starts) and requirement 4 (native regional VNet integration). The Consumption plan type does not keep instances warm and does not support VNet injection.
Event-Driven Scaling: It fulfills requirement 2 by dynamically adding and removing host instances using the event-driven scale controller.
Step 2: Create a system-assigned managed identity for the application
Lifecycle Coupling: It directly satisfies requirement 5. A system-assigned managed identity is tied strictly to the lifecycle of the Azure Functions resource. If the Functions application is deleted, Azure automatically removes the identity and its authentication token, ensuring that access to the Key Vault is immediately revoked. A user-assigned identity exists as an independent resource and would persist after the application's deletion.
Step 3: Create an access policy in Azure Key Vault for the application identity Granting Permissions: This step completes the access requirements. By adding an access policy (or an Azure RBAC role assignment) in Azure Key Vault specifically for the created system- assigned managed identity, you grant the runtime environment the necessary permissions to retrieve secrets.
No Code Changes: Combining the managed identity with an App Setting configured as an Azure Key Vault Reference allows the Functions platform to fetch secrets automatically at runtime, keeping your Java source code unchanged Reference:
https://learn.microsoft.com/en-us/azure/azure-functions/functions-best-practices
問題 #60
You deploy a GPT-4o model in Azure AI Foundry. Users report inconsistent completions for the same prompt. You need to make outputs more deterministic without changing the prompt. What should you do?
答案：A
解題說明：
Temperature controls randomness in token selection. Setting it near 0 makes the model consistently choose the highest-probability next token, producing more deterministic and repeatable output for identical prompts.
問題 #61
You are developing a serverless Java application on Azure. You create a new Azure Key Vault to work with secrets from a new Azure Functions application.
The application must meet the following requirements:
Reference the Azure Key Vault without requiring any changes to the Java code.
Dynamically add and remove instances of the Azure Functions host based on the number of incoming application events.
Ensure that instances are perpetually warm to avoid any cold starts.
Connect to a VNet.
Authentication to the Azure Key Vault instance must be removed if the Azure Function application is deleted.
You need to grant the Azure Functions application access to the Azure Key Vault.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
答案：
解題說明：
Explanation:
Step 1: Create the Azure Functions app with a Consumption plan type.
Use the Consumption plan for serverless.
Step 2: Create a system-assigned managed identity for the application.
Create a system-assigned managed identity for your application.
Key Vault references currently only support system-assigned managed identities. User-assigned identities cannot be used.
Step 3: Create an access policy in Key Vault for the application identity.
Create an access policy in Key Vault for the application identity you created earlier. Enable the " Get " secret permission on this policy. Do not configure the " authorized application " or applicationId settings, as this is not compatible with a managed identity.
Reference:
https://docs.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
問題 #62
You store embeddings in a property named embedding in an Azure Cosmos DB for NoSQL container.
You must construct a vector similarity query that orders documents by similarity to the input embedding and returns only the top five results.
You need to construct the similarity query.
What should you do?
答案：C
解題說明：
The query should limit the number of returned results by using TOP 5 together with ORDER BY VectorDistance(...) . Azure Cosmos DB for NoSQL provides the VectorDistance() system function for comparing a stored vector with an input query vector. Microsoft documents that a vector similarity query should order the results by VectorDistance so that the nearest matches are returned first.
A representative query is:
SELECT TOP 5
c.id,
VectorDistance(c.embedding, @embedding) AS SimilarityScore
FROM c
ORDER BY VectorDistance(c.embedding, @embedding)
Microsoft specifically recommends using a TOP N clause for vector search queries because returning more results than necessary increases RU consumption and latency. In this scenario, TOP 5 directly satisfies the requirement to return only the five most similar documents.
GROUP BY is used for aggregation and does not rank vectors by similarity. DISTINCT removes duplicate projected values but does not restrict results to the five nearest vectors. Offset pagination is unnecessary and can introduce additional query cost when only the highest-ranked five results are required.
Therefore, the correct action is to limit the number of results .
Study Guide references: Azure Cosmos DB for NoSQL # VectorDistance() ; vector search; ORDER BY ; TOP N ; RU and latency optimization.
問題 #63
You need to add a custom voice that matches your company's brand for a text-to-speech feature, distinct from any standard neural voice. What should you use?
答案：B
解題說明：
Custom Neural Voice lets you train a unique synthetic voice from recorded voice samples, producing a brand-specific voice rather than using one of the standard prebuilt neural voices.
問題 #64
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