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Microsoft AI-200 Exam Syllabus Topics:

Microsoft Developing AI Cloud Solutions on Azure Sample Questions:

1. 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.

2. Your team wants to track token usage, latency, and error rates for an Azure OpenAI-backed application in production, with alerting on anomalies. What should you configure?

A) Azure AI Search analytics
B) Prompt flow variant comparison
C) Azure Monitor with diagnostic settings and metric alerts on the Azure OpenAI resource
D) Azure AI Vision image analysis

3. A container in an AKS cluster repeatedly restarts.
Pod events show probe failures, although node-level CPU and memory metrics are normal.
You need to diagnose the cause of the repeating restarts.
What should you do first?

A) Scale the deployment to more replicas.
B) Drain and reboot the node hosting the pod.
C) Decrease the initialDelaySeconds for the container liveness probe.
D) Inspect the pod events and container logs.

4. Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You plan to deploy a container to an Azure App Service API app named api1. You host the source code for api1 in a GitHub repository. The container uses the API key at runtime to connect to a backend service.
The container must be able to retrieve the API key at runtime without exposing it in the source repository or Git commit history.
You need to ensure that the API key remains outside of Git commit history and is available to the container at runtime.
Solution: Embed the API key as a hardcoded environment variable in the Dockerfile.
Does the solution meet the goal?

A) No
B) Yes

5. Your application stores conversation history so a multi-turn chatbot can reference earlier turns, but the context window is limited. You need to keep the most relevant history within token limits.
What should you implement?

A) Summarize older turns and retain recent turns verbatim
B) Store history only in the client and never send it to the model
C) Increase max_tokens for output only
D) Truncate all history after 2 turns

Solutions: