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| Section | Objectives |
|---|---|
| Topic 1: Implement Azure AI solutions | - Implement generative AI solutions using Azure OpenAI - Implement natural language processing solutions - Implement knowledge mining with Azure AI Search - Implement computer vision solutions |
| Topic 2: Plan and manage Azure AI solutions | - Monitor and optimize AI solutions - Select appropriate Azure AI services - Plan security and compliance requirements |
| Topic 3: Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
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NEW QUESTION # 75
You are developing a microservices-based application that uses Azure Container Apps The application consists of several containerized services that handle tasks, such as processing orders, managing inventory, and generating reports.
You must secure the container apps. All apps must reside in the same virtual network, share the same Dapr configuration, and share the same logging location.
Apps must support the configuration of the amount of memory and compute resources available to containers.
You need to configure the Azure Container App
How should you complete the CLI command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified Answer: `az containerapp env create ... --enable-workload-profiles`.
Detailed Explanation: The shared boundary for Container Apps is the managed environment. Apps in one environment can share the environment's virtual network integration, observability destination, and Dapr- related environment configuration. Enabling workload profiles provides selectable compute profiles and resource sizing options for workloads in that environment. The CLI must therefore create a Container Apps environment and enable workload profiles. Creating an individual container app alone would not establish the common environment-level network, logging, and resource-profile boundary required by the scenario.
Study Guide Alignment: Containerized Azure workloads: registry builds, App Service containers, Container Apps revision/scaling behavior, and AKS deployment choices.
Official Microsoft Learn References: AI-200 Study Guide | Azure Container Apps environments
NEW QUESTION # 76
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.
Answer:
Explanation:
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
NEW QUESTION # 77
You are designing an Azure Database for PostgreSQL table for semantic search. Queries frequently filter on the created_at column.
The schema must support vector similarity search and reliable date filtering.
You need to ensure that the table meets the requirements.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
NEW QUESTION # 78
A customer support bot built with Azure AI Foundry Agent Service must ground its answers strictly in an internal knowledge base and avoid hallucinating unsupported facts.
What should you implement?
Answer: D
Explanation:
Connect the agent to an Azure AI Search knowledge source and explicitly constrain its instructions to answer from retrieved evidence. Microsoft Foundry Agent Service can use Azure AI Search to retrieve proprietary organizational content and ground model responses in that content. Retrieved documents provide the factual context from which the model generates its answer, and Azure AI Search can return source references for attribution.
Microsoft ' s RAG guidance also specifically recommends using clear system instructions that require the model to stay within retrieved content when hallucination risk must be reduced. If the available evidence does not support an answer, the instructions should direct the agent to state that the information is unavailable rather than inventing facts. Retrieval grounding substantially reduces unsupported generation, although production systems should still evaluate outputs because grounding alone does not mathematically guarantee zero hallucinations.
Increasing temperature would generally increase output variability and is contrary to the objective. A larger context window without retrieval does not give the model access to the organization ' s internal knowledge base. Disabling content filtering weakens safety controls and has no role in factual grounding.
Study Guide references: Microsoft Foundry Agent Service # Azure AI Search tool; RAG grounding; knowledge sources; source attribution; grounding instructions.
NEW QUESTION # 79
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: D
Explanation:
Configure an Azure Private Endpoint through Azure Private Link for the Azure OpenAI resource and disable public network access. A private endpoint assigns the Azure OpenAI service a private IP address from the selected virtual-network subnet, enabling workloads inside the VNet-or connected networks with suitable routing and DNS-to reach the service over private Azure networking rather than through its public endpoint. Microsoft explicitly documents private endpoints as the mechanism for accessing an Azure OpenAI resource after public network access is disabled.
For complete network isolation, creating the private endpoint alone is not sufficient if the resource continues accepting public connections. Microsoft security guidance recommends validating private endpoint connectivity and then disabling public network access , ensuring that permitted application traffic flows through Private Link. Private DNS should also be configured so the normal Azure OpenAI hostname resolves to the private endpoint address from within the VNet.
Azure AI Content Safety controls harmful-content detection rather than network accessibility. API key rotation improves credential hygiene but does not prevent public network connectivity. CORS controls browser-origin behavior and is not a network-isolation boundary.
Therefore, the required network architecture is Private Endpoint + Azure Private Link , with public network access disabled.
Study Guide references: Azure OpenAI networking; Azure Private Link; private endpoints; private DNS; public network access controls.
NEW QUESTION # 80
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