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| Section | Objectives |
|---|---|
| Topic 1: Plan and manage Azure AI solutions | - Monitor and optimize AI solutions - Select appropriate Azure AI services - Plan security and compliance requirements |
| Topic 2: Implement Azure AI solutions | - Implement generative AI solutions using Azure OpenAI - Implement natural language processing solutions - Implement computer vision solutions - Implement knowledge mining with Azure AI Search |
| Topic 3: Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
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NEW QUESTION # 26
Drag and Drop Question
You are deploying an Azure Function app that retrieves secrets from Key Vault by using a managed identity.
The deployment must ensure that identity and secret configuration are in place before the function code is deployed.
You need to deploy the function app securely.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Create the function app
You must first provision the underlying Azure Functions infrastructure before you can bind an identity or configuration settings to it.
Step 2: Assign a managed identity to the function app
Turning on the managed identity (such as a system-assigned identity) creates a distinct security principal in Microsoft Entra ID for the resource.
Step 3: Grant access to Key Vault
Use the managed identity's principal ID to create an access policy or RBAC role assignment in Key Vault, allowing the app to read secrets.
Step 4: Add Key Vault references to application settings.
Configure the Function App's application settings to point to the Key Vault secret URIs (@Microsoft.KeyVault(...)), which can now be securely resolved by the identity.
Step 5: Deploy the function code
Finally, deploy the application code. This ensures that when the code initializes and executes, all environment variables and secrets are already active and accessible, preventing application startup failures.
Reference:
https://learn.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
NEW QUESTION # 27
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 preparing a production deployment for an Azure Function app. The app will run across multiple environments.
The solution must support environment-specific configuration and prevent secrets from being stored in source control.
You need to develop the solution.
Solution: Store production secrets in environment variables set by the Dockerfile.
Does the solution meet the goal?
Answer: B
Explanation:
Correct:
* Use App Configuration with Key Vault references to store environment-specific settings and secrets, accessed from the function app by using a managed identity.
This is an industry-standard best practice architectural pattern.
Using Azure App Configuration combined with Azure Key Vault references completely satisfies your compliance requirements. It centralizes feature flags and non-sensitive configurations, keeps sensitive data safely out of source control, handles multi-environment deployments cleanly, and eliminates credentials via a passwordless Managed Identity.
Incorrect:
* Store connection strings in the Function app application settings configured in the Azure Portal.
* Store production secrets in environment variables set by the Dockerfile.
Reference:
https://learn.microsoft.com/en-us/azure/app-service/app-service-key-vault-references
NEW QUESTION # 28
You must ensure an Azure OpenAI-powered application never exceeds a defined token-per- minute budget across all users to avoid runaway costs. What should you configure?
Answer: A
Explanation:
Each Azure OpenAI deployment can have Tokens-Per-Minute (TPM) and Requests-Per-Minute (RPM) limits configured, which cap consumption at the deployment level and directly control cost exposure.
NEW QUESTION # 29
Hotspot Question
You deploy a private container image from Azure Container Registry (ACR) to App Service.
App Service must authenticate to ACR to pull the image.
The solution must NOT store static registry credentials.
You need to configure the secure image pull authentication.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Assign the Container Registry Reader role to a managed identity.
To securely deploy a private container image from Azure Container Registry (ACR) to an Azure App Service without managing passwords, you should configure a Managed Identity on the App Service and grant it the AcrPull role on the ACR.
Box 2: Use managed identity with role assignment.
you should use a Managed Identity combined with an Azure Role-Based Access Control (RBAC) role assignment to meet the requirement.
Reference:
https://medium.com/@miketobicarter/deploying-a-net-app-to-azure-using-docker-acr-app-service-and-github-actions-step-by-step-3ed6ae8a4d0b
NEW QUESTION # 30
You are developing an application that uses a Python API to perform similarity queries against Azure Database for PostgreSQL. The application creates a new database connection for every request.
During peak traffic, the application intermittently fails to open new database sessions, logs indicate that the maximum number of connections have been reached.
You need to configure the connection pooling strategy to reduce connection setup overhead and maximize reuse for the high-concurrency workload.
What should you configure? To answer. select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
onnection pooling technology: PgBouncer. Pooling mode: Transaction pooling mode.
Detailed Explanation: Azure Database for PostgreSQL Flexible Server supports PgBouncer to reduce connection setup cost and protect the server from excessive client sessions. For a high-concurrency API whose requests do not require a server session to remain pinned between transactions, transaction pooling maximizes reuse by returning the server connection to the pool after each transaction. Session pooling holds a server connection for the lifetime of the client session and therefore provides less multiplexing under the connection-pressure scenario described.
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 | PgBouncer in Azure Database for PostgreSQL
NEW QUESTION # 31
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AI-200 Valid Exam Vce: https://www.actualcollection.com/AI-200-exam-questions.html