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Microsoft Operationalizing Machine Learning and Generative AI Solutions Sample Questions:

1. A team manages an Azure Machine Learning workspace and deploys a model to an endpoint.
A deployed online endpoint shows inconsistent response times during periods of high traffic.
You need to identify potential performance degradation.
Which three metrics should you monitor? Each correct answer presents part of the solution.
Choose three.
NOTE: Each correct selection is worth one point.

A) Connections active
B) Dataset size
C) Request latency
D) Requests per minute
E) Feature count

2. During training, pipelines occasionally fail due to schema mismatch caused by upstream data changes. You need a robust and automated solution that prevents invalid data from reaching training steps. What is the BEST approach?

A) Add a data validation component in pipeline
B) Use larger compute
C) Ignore schema differences
D) Retrain manually when failure occurs

3. A team develops multiple AI applications in Microsoft Foundry that rely on shared prompt templates.
The team requires a centralized way to track, version, and reuse prompt content across projects.
You need to recommend a solution to track and reuse prompt content.
Which approach should you recommend?

A) Embed prompts directly in application configuration files.
B) Persist prompts in Azure Blob Storage with folder-level organization.
C) Register prompts as datasets in the Azure Machine Learning workspace.
D) Store prompts as versioned files in a Git repository.

4. Drag and Drop Question
A team iterates prompts used by a generative AI agent. The team must support internal review before releasing changes.
The team must:
- Track prompt changes with a clear history for audit and rollback.
- Compare prompt variants in parallel without affecting the prompt used in the production environment.
You need to select the appropriate source control approach for each requirement.
What should you use for each requirement? To answer, move the appropriate source controls to the correct requirements. You may use each source control 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.

5. Drag and Drop Question
An organization uses Microsoft Foundry to develop generative AI projects that access shared Azure resources such as storage accounts and vector databases.
The organization s security policy requires eliminating secret key-based authentication and enforcing least-privilege access.
You must configure identity and access so that:
Services authenticate without stored credentials.
Permissions are scoped appropriately across projects and shared resources.
You need to configure the appropriate identity or access mechanism for each requirement.
What should you configure in Microsoft Foundry to meet each requirement? To answer, move the appropriate configuration mechanisms to the correct requirements. You may use each configuration mechanism 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.

Solutions: