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| Section | Objectives |
|---|---|
| Plan and manage Azure AI solutions | - Monitor and optimize AI solutions - Plan security and compliance requirements - Select appropriate Azure AI services |
| Implement Azure AI solutions | - Implement computer vision solutions - Implement knowledge mining with Azure AI Search - Implement natural language processing solutions - Implement generative AI solutions using Azure OpenAI |
| Implement and monitor AI workloads | - Monitor performance and troubleshoot issues - Deploy AI models and services |
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NEW QUESTION # 112
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: B
NEW QUESTION # 113
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 # 114
You are using the Python SDK to develop a containerized AI application that retrieves the value of a runtime setting stored in an Azure App Configuration resource. The application will run in Azure in the security context of a managed identity.
The application must work in a local development environment without any code changes.
You need to complete the code that implements the retrieval.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified Answer: var1 = DefaultAzureCredential(); retrieval call = get_configuration_setting(...).
Detailed Explanation: DefaultAzureCredential is designed to support the same application code across local development and Azure-hosted environments. Locally it can use developer credentials, while in Azure it can use the workload's managed identity. The App Configuration client's get_configuration_setting method retrieves a specific key/label pair, which matches the code shown. Using ManagedIdentityCredential directly would not provide the same local-development credential chain without code or environment-specific handling.
Study Guide Alignment: Security and operations: Key Vault, App Configuration, managed identity, OpenTelemetry, Azure Monitor, and KQL-based troubleshooting.
Official Microsoft Learn References: AI-200 Study Guide | Azure App Configuration Python client | Managed identities for Azure resources
NEW QUESTION # 115
You have an Azure web app that uses Azure Cosmos DB as a data store. You create a Cosmos DB container by running the following PowerShell script:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The question maps directly to the AI-200 objective "Develop AI solutions by using Azure Cosmos DB for NoSQL," which includes running queries and optimizing query performance and Request Unit (RU) consumption.
Statement 1: No - The minimum throughput is not 400 RU/s.
The PowerShell command provisions the container with:
-AutoscaleMaxThroughput 5000
Azure Cosmos DB autoscale operates between approximately 10% and 100% of the configured maximum throughput . Microsoft documentation specifically gives the example of an autoscale container provisioned with 5,000 RU/s scaling between 500 RU/s and 5,000 RU/s . Therefore, for this container, the minimum operating autoscale throughput is 500 RU/s , not 400 RU/s.
Therefore:
"The minimum throughput for the container is 400 RU/s." # No
Statement 2: No - The first query is not an in-partition query.
The container uses:
/EmployeeId
as its partition key.
The first query is:
SELECT * FROM c WHERE c.EmployeeId > ' 12345 '
Although the query references the partition key, it uses a range predicate ( > ) , not an equality predicate.
Microsoft explicitly states that a range filter on a partition key is not scoped to a single physical partition .
To qualify as an in-partition query, the filter must identify the applicable partition, typically through an equality predicate such as:
WHERE c.EmployeeId = ' 12345 '
Microsoft ' s documentation provides essentially the same example: a query using DeviceId > ... against a container partitioned by DeviceId is not an in-partition query .
Therefore:
"The first query statement is an in-partition query." # No
Statement 3: Yes - The second query is a cross-partition query.
The second query is:
SELECT * FROM c WHERE c.UserId = ' 12345 '
The container ' s partition key is /EmployeeId, not /UserId. Because the query contains no filter on the partition key , Azure Cosmos DB cannot route it to one logical partition. It must fan out the query across the applicable physical partitions and combine the results.
Microsoft describes this behavior directly: when a query does not contain a filter on the partition key, it must execute across the partitions.
Therefore:
"The second query statement is a cross-partition query." # Yes
NEW QUESTION # 116
An AI application uses a database. The database credential rotates every 30 days.
The application currently requires a manual update each time the credential rotates.
You need to ensure that the application always uses the latest secret version without manual updates.
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
Explanation:
Configure a Key Vault rotation policy to automate periodic credential generation and updates.
Retrieve secrets without a version identifier (versionless reference) so the app automatically resolves the newest active version.
Incorrect:
[Not B]
To stop manual updates, you should not retrieve secrets by specifying a version identifier, because locking in a version stops the application from seeing newer updates.
Reference:
https://learn.microsoft.com/en-us/azure/key-vault/secrets/secure-secrets
NEW QUESTION # 117
......
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