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| Section | Weight | Objectives |
|---|---|---|
| Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Integrate backend services and build event-driven architectures | 25% | - Build serverless APIs and workflows
|
| Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
|
| Develop containerized AI solutions on Azure | 25% | - Implement container hosting environments
|
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NEW QUESTION # 55
Drag and Drop Question
A Python API running in ACA must send distributed traces to Azure Monitor.
The API creates spans. However, no traces appear in Azure Monitor.
You need to configure the OpenTelemetry SDK pipeline to export traces to Azure Monitor.
What should you do? To answer, move the appropriate actions to the correct requirements. You may use each action 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:
Box 1: Create the Azure Monitor component that sends trace data
To register a global TracerProvider in OpenTelemetry, you must call the SetTracerProvider method on the global tracer provider object, passing in your fully configured TracerProvider instance.
Box 2: Configure a span processor to send spans to the exporter
To export OpenTelemetry traces to Azure Monitor using the Python SDK, you must configure a span processor (such as BatchExportSpanProcessor), pass your initialized Azure Monitor trace exporter to it, and register that span processor with your global tracer provider.
Box 3: Initialize the application's TracerProvider for tracing
Box 4: Call tracer.start_as_current_span()
Acquire your tracer and create spans. Example code (continued from box 2 above):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("hello-aca-span")
Reference:
https://learn.microsoft.com/en-us/azure/durable-task/sdks/durable-task-scheduler-opentelemetry-tracing
https://learn.microsoft.com/en-us/python/api/overview/azure/monitor-opentelemetry-exporter-readme
NEW QUESTION # 56
You are troubleshooting a production Azure OpenAI service that is experiencing intermittent connectivity issues. All telemetry is sent to a Log Analytics workspace.
You must write a KQL query that analyzes the AppRequests table. The query must filter for requests that occurred within the last 30 minutes and have a failed status.
The final output must display the total number of failures for each unique operation.
You need to select the KQL operators required to filter the time range and aggregate the failure counts.
Which two operators should you use? Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: A,C
NEW QUESTION # 57
You have an existing AKS cluster and a container image stored in Azure Container Registry.
You must deploy a new version by using a Deployment manifest that supports rolling updates without interrupting traffic.
You need to perform a rolling update by using a manifest file.
Which three 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:
NEW QUESTION # 58
You deploy a new revision of an app in Azure Container Apps.
You need to gradually shift production traffic to the revision while monitoring performance. In addition, you need to be able to quickly roll back. Which two actions should you perform?
Each correct answer presents part of the solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: C,E
Explanation:
Detailed Explanation: Gradual production rollout requires more than one revision to remain active and a mechanism to divide traffic between them. Multiple revision mode permits concurrent active revisions, and traffic splitting lets a specified percentage of requests flow to the new revision while the remainder stays on the proven revision. This also enables rapid rollback by returning traffic to the prior revision. Increasing replicas or restarting a revision changes capacity or process state, not release traffic distribution.
Study Guide Alignment: Containerized Azure workloads: registry builds, App Service containers, Container Apps revision/scaling behavior, and AKS deployment choices.
Official Microsoft Learn References: AI-200 Study Guide | Azure Container Apps revisions
NEW QUESTION # 59
You are implementing an Azure solution that uses Azure Cosmos DB and the latest Azure Cosmos DB SDK.
You add a change feed processor to a new container instance.
You attempt to read a batch of 100 documents. The process fails when reading one of the documents. The solution must monitor the progress of the change feed processor instance on the new container as the change feed is read. You must prevent the change feed processor from retrying the entire batch when one document cannot be read.
You need to implement the change feed processor to read the documents.
Which features should you use? To answer, move the appropriate features to the correct requirements. Each feature may be used 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 # 60
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