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Microsoft AI-200 Exam Syllabus Topics:

SectionObjectives
Connect to and consume Azure services- Integrate Azure services
  • 1. Azure SDKs
  • 2. Serverless integration patterns
  • 3. Azure messaging and eventing
  • 4. Event-driven architectures
  • 5. Third-party SDKs
Develop containerized solutions on Azure- Implement containerized applications
  • 1. Manage containerized compute environments
  • 2. Deploy AI workloads in containers
  • 3. Implement scalable hosting patterns
Secure, monitor, troubleshoot Azure solutions- Operate AI cloud solutions
  • 1. Performance optimization
  • 2. Security and secret management
  • 3. Monitoring and observability
  • 4. Troubleshooting Azure solutions
Develop AI solutions by using Azure data management services- Work with Azure data platforms for AI workloads
  • 1. Vector databases
  • 2. Azure data management services
  • 3. Data integration for AI applications

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Microsoft Developing AI Cloud Solutions on Azure Sample Questions (Q34-Q39):

NEW QUESTION # 34
You are developing an Azure Function that calls external APIs by providing an access token for the API. The access token is stored in a secret named token in an Azure Key Vault named mykeyvault. You need to ensure the Azure Function can access the token. Which value should you store in the Azure Functions app configuration?

Answer: B

Explanation:
To securely provide the Azure Function with access to the secret without exposing it in the application code, you should store a Key Vault reference syntax in the Azure Functions app configuration settings.
The exact value you must store depends on whether you wish to target the latest version of the secret automatically or a specific, pinned version.
Target the latest version (Recommended)
Use this syntax to ensure your Function App always fetches the most recent version of the token:
@Microsoft.KeyVault(VaultName= mykeyvault;SecretName=token)
Reference:
https://learn.microsoft.com/en-us/azure/key-vault/general/apps-api-keys-secrets


NEW QUESTION # 35
You are developing a Python application that reads data from Azure Cosmos DB for NoSQL by using the azure-cosmos SDK.
You need to connect to an existing account and run a SQL query against an existing container.
Which four 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:
* Initialize CosmosClient.
* Specify the database name.
* Obtain the container reference.
* Run the query.
The Python Azure Cosmos DB SDK follows the resource hierarchy Account # Database # Container # Items . The first step is to initialize a reusable CosmosClient with the Azure Cosmos DB account endpoint and an appropriate credential. Microsoft identifies CosmosClient as the primary client for interacting with databases in an account.
Next, specify the existing database by calling client.get_database_client(database_name). This returns a DatabaseProxy representing that database. Importantly, DatabaseProxy should not be instantiated directly ; Microsoft explicitly states that it should be obtained through CosmosClient.get_database_client().
From the database reference, obtain the target container by using database.get_container_client (container_name). Microsoft documents this as the standard way to retrieve an existing container reference.
Finally, execute the SQL query through container.query_items() , which accepts the Cosmos DB for NoSQL query and optional parameters and returns an iterable result set.
Therefore, Initialize DatabaseProxy is the distractor: the SDK creates the DatabaseProxy through get_database_client; application code should not construct it directly.
Study Guide references: Azure Cosmos DB for NoSQL # Python SDK; CosmosClient; database and container clients; ContainerProxy.query_items().


NEW QUESTION # 36
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 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.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Store the API key as an App Service application setting configured through the Azure Portal.
Does the solution meet the goal?

Answer: B

Explanation:
Correct:
* Store the API key in Azure Key Vault and reference it from an App Service application setting.
Storing the API key in Azure Key Vault and referencing it via App Service application settings is the recommended, secure approach. This strategy completely removes sensitive credentials from your GitHub repository and Git commit history while injecting them safely into your container environment at runtime.
Incorrect:
* Embed the API key as a hardcoded environment variable in the Dockerfile.
* Store the API key as a GitHub repository secret.
* Store the API key as an App Service application setting configured through the Azure Portal.
Reference:
https://www.qservicesit.com/full-stack-applications-on-azure


NEW QUESTION # 37
Hotspot Question
A company uses Azure Monitor Application Insights to monitor application behavior, including incoming requests and dependencies.
You must identify failed requests from the last hour. You must also calculate the average duration of failed request dependency calls, grouped by operation name.
You need to analyze telemetry in Application Insights.
Which operators 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: where
Filter telemetry rows
The where operator filters a table to rows that satisfy a specific predicate. Both box 1 and box 2 require filtering telemetry data to the last hour (timestamp > ago(1h)).
Box 2: where
In the Kusto Query Language (KQL), the where operator filters a table to rows that satisfy a specific predicate or condition. Inside the inner subquery, you need to filter the dependencies telemetry table to only include records from the last hour (timestamp > ago(1)) Box 3: summarize Aggregate calculated data The summarize operator produces a table that aggregates the content of the input table. It is used here with the avg() aggregation function to calculate the average duration grouped by the operation_Name.
Reference:
https://tryhackme.com/room/kqlkustobasicqueries


NEW QUESTION # 38
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: Store the API key as an App Service application setting configured through the Azure Portal.
Does the solution meet the goal?

Answer: B


NEW QUESTION # 39
......

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