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"Developing AI Cloud Solutions on Azure", also known as AI-200 exam, is a Microsoft Certification. With the complete collection of questions and answers, Pass4sureCert has assembled to take you through 144 Q&As to your AI-200 Exam preparation. In the AI-200 exam resources, you will cover every field and category in Azure AI Engineer Associate Certification helping to ready you for your successful Microsoft Certification.
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| Section | Weight | Objectives |
|---|---|---|
| Develop AI solutions using Azure data services | 30% | - Design and optimize data access and retrieval
|
| Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
|
| Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
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.
You need to implement the SDK components required for the application to access and manage data in Azure Cosmos DB for NoSQL.
Which SDK components should you use? To answer, move the appropriate components to the correct requirements. You may use each component 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.

Explanation:
* Initialize the connection by using the account endpoint and key: CosmosClient
* Define shared throughput: Database
* Perform item CRUD operations: Container
The Azure Cosmos DB for NoSQL .NET SDK uses a clear resource hierarchy. CosmosClient is the top-level client object and is responsible for connecting to the Azure Cosmos DB account. Microsoft identifies it as the primary SDK class for accessing account-level resources and databases. It can be initialized by using the account endpoint together with an account key or another supported credential.
A Database represents a database resource within the account. Shared provisioned throughput is configured at the database level , allowing multiple containers within that database to share the same RU/s allocation.
Microsoft documents that setting throughput on the database creates a shared-throughput database.
A Container is the SDK object used to interact with items stored in a Cosmos DB container. Microsoft specifically describes the Container class as the object used for item operations such as creating, reading, updating, deleting, and querying documents.
The Indexing policy option is not used for any of these requirements. It controls how Cosmos DB indexes document properties for query execution, not connectivity, shared throughput, or CRUD access.
Study Guide references: Azure Cosmos DB for NoSQL .NET SDK # CosmosClient; Database; shared throughput; Container; item CRUD operations.
You plan to create a Docker image that runs an ASP.NET Core application named ContosoApp. You have a setup script named setupScript.psl and a series of application files including ContoscApp.dll.
You need to create a Dockerfile document that meets the following requirements:
* Call SQiupScript.psI when the container is built.
* Run CantosoApp.dill when the container starts.
The Dockerfile document must be created in the same folder where ContosoApp.dll and setupScnpt.ps! are stored.

Explanation:
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.
Report generation must be implemented as follows:
Process reports every Sunday at midnight.
Minimize app resources during report generation.
Record metrics in the same location as other containers.
Use the same virtual network as other containers.

Explanation:
You are developing an AI-powered API that retrieves connection strings and API keys from Azure Key Vault.
You must configure a solution that provides the following security functionality:
* The API must authenticate to Key Vault without storing credentials in any application configuration files
* The identity used by the API must have only the minimum permissions necessary to read secrets.
* The configuration must minimize the blast radius if an identity or credential is compromised.
You need to implement a secure access strategy for the API.
Which two actions should you perform? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
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Your organization requires that all prompts and completions sent to Azure OpenAI be retained for zero data logging beyond what ' s required for abuse monitoring, per contractual requirements.
What should you do?
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