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| Section | Objectives |
|---|---|
| Plan and manage Azure AI solutions | - Select appropriate Azure AI services - Plan security and compliance requirements - Monitor and optimize AI solutions |
| Implement Azure AI solutions | - Implement natural language processing solutions - Implement computer vision solutions - Implement generative AI solutions using Azure OpenAI - Implement knowledge mining with Azure AI Search |
| Implement and monitor AI workloads | - Deploy AI models and services - Monitor performance and troubleshoot issues |
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NEW QUESTION # 47
Drag and Drop Question
You are developing a new page for a website that uses Azure Cosmos DB for data storage. The feature uses documents that have the following format:
You must display data for the new page in a specific order. You create the following query for the page:
You need to configure an Azure Cosmos DB policy to support the query.
How should you configure the policy? To answer, drag the appropriate JSON segments to the correct locations. Each JSON segment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: compositeIndexes
Azure Cosmos DB requires a defined composite index for any query utilizing an ORDER BY clause with multiple properties.
Box 2: descending
In an ORDER BY clause, properties without an explicit direction default to ascending order. Your query ORDER BY p.name, p.city DESC translates to an ascending sort on /name and a descending sort on /city.
Reference:
https://docs.azure.cn/en-us/cosmos-db/index-policy
NEW QUESTION # 48
Hotspot Question
A Python web API uses OpenTelemetry for tracing. The call_downstream_service function makes an outbound HTTP request by using the requests library.
The following code is the only OpenTelemetry configuration in the application:
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:
Box 1: Yes
This code will successfully create a local span for the process_request function, but it will not automatically create or propagate spans for the outbound HTTP request made by the requests library.
Box 2: No
Manual tracing only: Your current configuration only creates a span for the code wrapped inside the with tracer.start_as_current_span(...) context manager.
Box 3: Yes
Missing instrumentation: The standard requests library does not natively know about OpenTelemetry. It requires an external instrumentation package to hook into its network calls.
Reference:
https://learn.microsoft.com/en-us/python/api/overview/azure/core-tracing-opentelemetry-readme
NEW QUESTION # 49
You are investigating high latency in an AI search application that processes millions of requests daily.
Telemetry is stored in Azure Monitor Logs.
You must create a KQL query that correlates information from the AppRequests table and the AppDependencies table. The query must meet the following requirements:
* Include only data from the last 24 hours.
* Filter for failed requests only.
* Calculate the average duration of dependencies, grouped by operation.
The query must follow best practice to optimize the performance by minimizing the initial data scan.
You need to create the query.
In which order should 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:
Verified Answer: 1) Select the requests table; 2) apply the 24-hour time filter; 3) filter failed requests; 4) join the dependencies table; 5) summarize average dependency duration by operation.
Detailed Explanation: KQL performs best when high-selectivity filters are applied as early as possible, especially the time predicate that limits the amount of data scanned. Starting from AppRequests, restricting to the last 24 hours, and then filtering failures reduces the left-side dataset before the join. The dependency table is then correlated with those requests, and aggregation is performed last to calculate average dependency duration by operation. Joining or summarizing before the time and failure filters would process more data than necessary.
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 | Optimize log queries in Azure Monitor
NEW QUESTION # 50
Hotspot Question
You are using 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:
Box 1: DefaultAzureCredential
This class from the azure-identity library provides an automated, sequenced token authentication flow. When running locally, it automatically falls back to your local development environment credentials (such as Azure CLI, environment variables, or VS Code login). Once deployed to Azure, it seamlessly switches to the environment's managed identity without requiring any code changes.
Box 2: get_configuration_setting
This method belongs to the AppConfigurationClient in the azure-appconfiguration SDK. It is used to fetch a specific configuration key-value pair using its key name ("FeatureX") and an optional label.
Reference:
https://learn.microsoft.com/en-us/azure/developer/python/tutorial-containerize-deploy-python-web-app-azure-04
NEW QUESTION # 51
You need to ensure that responses from your Azure OpenAI application include citations back to the specific source documents used, to support user trust and verification. What should you implement?
Answer: A
Explanation:
Citation support requires passing document metadata (source name, page/section) through the retrieval step and prompting the model to reference that metadata explicitly in its answer -- this is a pipeline and prompt design pattern, not a sampling parameter.
NEW QUESTION # 52
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