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| Section | Objectives |
|---|---|
| Topic 1: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 2: Connect to and consume Azure services | - Integrate Azure services
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Develop containerized solutions on Azure | - Implement containerized applications
|
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NEW QUESTION # 111
You deploy an AI application across multiple Azure regions.
The application must be able to view writes across all regions within a predictable time window.
You need to determine the appropriate consistency level.
What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: B,C
NEW QUESTION # 112
You are provisioning and configuring a Service Bus processor for AI batch jobs.
The processor must connect to an existing queue, register handlers for message and error processing, and then begin receiving messages.
You need to provision and configure the Service Bus processor for message and error handling.
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:
Verified answer: 1) Create the Service Bus client; 2) create the queue processor/receiver; 3) register message and error handlers; 4) start the message processor.
Detailed Explanation: The processor depends on a namespace client/connection, so the client is created first.
Next, the queue-specific processor or receiver is created from that client. Message and error callbacks must be registered before processing starts so incoming messages and failures have defined handlers. Starting the processor is therefore the final step. Dead-lettering failed messages is an optional application settlement decision and is not a prerequisite for constructing and starting the processor.
Study Guide Alignment: Azure service integration: Service Bus, Event Grid, Azure Functions triggers
/bindings, and event-driven processing.
Official Microsoft Learn References: AI-200 Study Guide | Service Bus message transfers, locks, and settlement
NEW QUESTION # 113
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.
Answer:
Explanation:
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
NEW QUESTION # 114
You need to configure vector embedding updates according to the business and technical requirements.
Which information should you use? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified answer: Identify document changes: Change feed processor. Scale out vectorization processing:
Lease container.
Detailed Explanation: The change feed processor is designed to react to inserts and updates in a monitored Cosmos DB container, which directly matches the requirement to generate embeddings for new or changed documents. Its lease container stores processing state and coordinates work across multiple workers, allowing the processing workload to scale out without duplicating ownership of change-feed ranges. A periodic full scan would consume unnecessary RUs, and neither strong consistency nor container RU throughput is the coordination mechanism for distributed change-feed workers.
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 | Azure Cosmos DB change feed processor
NEW QUESTION # 115
You are reviewing secret access patterns used by an AI application that retrieves credentials from Key Vault.
You need to evaluate the security impact of each implementation approach.
What is the outcome of each approach? To answer, move the appropriate outcomes to the correct implementations. You may use each outcome 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.
Answer:
Explanation:
Explanation:
NEW QUESTION # 116
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