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| Section | Weight | Objectives |
|---|---|---|
| Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
|
| Develop containerized AI solutions on Azure | 25% | - Implement container hosting environments
|
| Integrate backend services and build event-driven architectures | 25% | - Build serverless APIs and workflows
|
| Secure, monitor, and optimize AI solutions | 20% | - Manage security and configuration
|
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NEW QUESTION # 141
You process Azure Service Bus messages that require a dependent external API call.
If the API is temporarily unavailable, you must delay processing of the message without incrementing the delivery count. You need to find a way to process the message when the API is available while keeping the message accessible. Which message action should you perform?
Answer: D
Explanation:
Detailed Explanation: Deferral is intended for a message that cannot be processed now because a particular dependency is temporarily unavailable, while the application wants to keep the message in the main queue for later retrieval by sequence number. Complete would permanently remove it, dead-letter would move it aside as a failed message, and abandon immediately releases the lock for redelivery. Deferral therefore best matches the requirement to postpone the individual message while keeping it available for deliberate later processing.
Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers
/bindings, and event-driven processing.
Official Microsoft Learn References: AI-200 Study Guide | Service Bus message deferral | Service Bus message transfers, locks, and settlement
NEW QUESTION # 142
You are developing a .NET application that uses Azure Cosmos DB for NoSQL to store application data The application uses the Azure Cosmos DB for NoSQL SDK to interact with the database account. The application must perform the following tasks
* Initialize the connection by using the account endpoint and key.
* Define shared throughput.
* Perform create, read, update, and delete (CRUD) operations on items stored in a container
Answer:
Explanation:
Explanation:
Verified answer: Initialize connection: CosmosClient. Define shared throughput: Database. Perform item CRUD: Container.
Detailed Explanation: The Cosmos DB SDK follows the service resource hierarchy. CosmosClient represents the account connection and is initialized with the account endpoint and credential. Shared throughput is configured at the database level when multiple containers share database throughput. Item create, read, update, and delete operations are performed through a container object because containers hold items and define partitioning/indexing behavior. An indexing policy is configuration attached to a container, not the SDK object used for CRUD.
Study Guide Alignment: AI data-management workloads: Cosmos DB, PostgreSQL, caching, vector storage, vector retrieval, consistency, and connection optimization.
Official Microsoft Learn References: AI-200 Study Guide | Cosmos DB databases, containers, and items
NEW QUESTION # 143
Drag and Drop Question
You plan to deploy a web application to AKS.
The solution must:
- Scale out the application by adding more pods during peak CPU usage.
- Expose the application internally within the cluster only.
You need to configure a Kubernetes resource for each requirement.
Which resources should you configure? To answer, move the appropriate resources to the correct requirements. You may use each resource once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: HorizontalPodAutoscaler
Horizontal Pod Autoscaler (HPA) is the AKS feature to use. It automatically scales the number of pods in a deployment based on observed CPU utilization or other metrics.
Box 2: ClusterIP service
Use a ClusterIP service or internal LoadBalancer with annotations to expose your web application internally within an Azure Kubernetes Service (AKS) cluster only.
Reference:
https://learn.microsoft.com/en-us/azure/aks/optimize-aks-costs
https://learn.microsoft.com/en-us/azure/aks/concepts-network-services
NEW QUESTION # 144
You need to ensure that responses from your Azure OpenAI application include citations back to the specific source documents used, to support user trust and verification.
What should you implement?
Answer: B
Explanation:
A retrieval-augmented generation (RAG) architecture is the correct mechanism when generated answers must be traceable to specific source documents. RAG first retrieves relevant document chunks from a search index or other knowledge source, supplies those chunks to the language model as grounding context, and then generates an answer based on that retrieved information. Microsoft specifically documents that RAG enables responses containing citations back to source content .
For reliable citation generation, each retrieved chunk should carry identifying metadata such as a source identifier, document title, section, page, or URL . Microsoft's Azure RAG guidance recommends labeling retrieved chunks and including source metadata with them, then explicitly instructing the model to cite the corresponding sources in its response. This allows users to verify individual claims against the underlying documents.
Modern Azure AI Search agentic retrieval can also return structured references and grounding metadata , specifically designed for citation linking.
Increasing top_p only alters token sampling. Content filtering addresses safety, not provenance. Using a base model without retrieval provides no authoritative document linkage.
Study Guide references: RAG architecture; grounding data; retrieval metadata; Azure AI Search references; prompt engineering for citations.
NEW QUESTION # 145
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. The API key must not be stored in application configuration directly. The API key must be accessed securely from Azure Key Vault.
You need to ensure that the API key is stored securely in Azure Key Vault and is available to the container at runtime without being exposed in source control or Git commit history.
Solution: Embed the API key as a hardcoded environment variable in the Dockerfile.
Does the solution meet the goal?
Answer: B
NEW QUESTION # 146
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