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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop containerized AI solutions on Azure | 25% | - Monitor and troubleshoot containerized workloads
|
| Topic 2: Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Topic 3: Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
|
| Topic 4: Develop AI solutions using Azure data services | 30% | - Design and optimize data access and retrieval
|
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질문 # 55
You are configuring sampling for a distributed application that sends traces to Azure Monitor. The solution must:
* Preserve upstream sampling decisions across distributed traces
* Capture all spans during local testing.
* Sample 10 percent of traces in production.
You need to apply the appropriate sampling configuration for each requirement.
What should you do? To answer, move the appropriate configurations to the correct requirements. You may use each configuration 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.
정답：
설명：
Explanation:
Verified Answer: Preserve parent sampling decisions: ParentBasedSampler. Capture all spans locally:
AlwaysOnSampler. Sample 10% in production: TraceIdRatioBasedSampler(0.1).
Detailed Explanation: Parent-based sampling propagates the sampling decision from the upstream parent, preventing broken sampling decisions across a distributed trace. AlwaysOnSampler records every span, which is suitable for local test environments where complete trace visibility is more important than telemetry volume. TraceIdRatioBasedSampler with 0.1 selects approximately ten percent of traces based on trace identifiers, providing deterministic fixed-ratio sampling for production. A batch span processor and an exporter control processing/export, not the sampling decision itself.
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 | OpenTelemetry sampling in Azure Monitor | Enable Azure Monitor OpenTelemetry
질문 # 56
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.
정답：
설명：
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().
질문 # 57
Hotspot Question
You plan to configure an Event Grid subscription for AI inference events.
The solution must:
- Filter events by payload data.
- Retain undelivered events.
- Limit retry attempts.
You need to configure the Event Grid.
Which configurations should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
정답：
설명：
Explanation:
Box 1: Advanced filter
You must use an Advanced filter to filter Azure Event Grid events by payload data.
Payload-level access: Advanced filters allow you to filter on fields within the data object of the event schema, which contains the specific payload of your AI inference event.
Complex operators: It supports advanced comparisons like StringContains, NumberGreaterThan, or BoolEquals against specific JSON payload paths.
Box 2: Dead-letter destination
You should use a dead-letter destination because it is the native Azure mechanism designed to retain undelivered events when delivery attempts fail or are dropped.
Purpose: Captures events that cannot be delivered to your AI inference endpoint due to errors, timeouts, or bad payloads.
Storage Requirement: Requires an Azure Storage account container to securely hold the undelivered message blobs.
Retention Policy: Events stored in the dead-letter container are retained for 14 days by default, giving you time to investigate.
Box 3: Maximum delivery attempts
Maximum delivery attempts is the feature to use to limit retry attempts in an Event Grid subscription.
Use this setting to set a hard cap on how many times Event Grid tries to send an event. You can lower this number from the default value to stop retrying sooner.
Reference:
https://learn.microsoft.com/en-us/azure/data-manager-for-agri/how-to-use-events
https://learn.microsoft.com/en-us/azure/event-grid/subscriber-operations
질문 # 58
A development team wants to compare multiple prompt variations against the same test dataset and visualize which prompt performs best. What should they use in Azure AI Foundry?
정답：B
설명：
Prompt flow variants allow you to define multiple versions of a prompt/node, run them against the same evaluation dataset, and compare results side-by-side to identify the best-performing variant.
질문 # 59
A company has an Azure Cosmos DB for NoSQL account. The account is configured for session consistency.
Data is written to a single Azure region and data can be read from three Azure regions.
An application that will access the Azure Cosmos DB for NoSQL container data using an SDK has the following requirements:
* Roads from the application must return the most recent committed version of an Item from any Azure region.
The container items should not automatically be deleted.
You need to implement the changes to the Azure Cosmos DB for NoSQL account. What should you do? To answer, select the appropriate options in the answer area.
정답：
설명：
Explanation:
질문 # 60
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