AI-102 Implement generative AI solutions Practice Question
You are building a generative AI solution using Azure AI Foundry. The solution must meet compliance requirements that require all model inputs and outputs to be auditable for a minimum of one year. What should you enable?
⚠ Common exam trap
Candidates often confuse monitoring features (alerts, metrics, workbooks) with data retention capabilities, assuming any Azure Monitor feature can satisfy audit requirements without understanding that only diagnostic settings provide the raw log capture needed for compliance.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Diagnostic settings to capture request and response logs and store them in a storage account.
Enabling diagnostic settings for the Azure AI Foundry resource allows you to capture detailed request and response logs for all model interactions. By routing these logs to a storage account, you retain the data for the required one-year audit period, meeting compliance needs for full traceability of inputs and outputs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Monitor alerts for unusual activity.
Why it's wrong here
Alerts notify but do not store content for auditing.
- ✗
Azure Monitor metrics for the Azure AI Foundry resource.
Why it's wrong here
Metrics provide performance data, not input/output content.
- ✗
Azure Monitor workbooks to visualize usage.
Why it's wrong here
Workbooks visualize metrics, not raw data.
- ✓
Diagnostic settings to capture request and response logs and store them in a storage account.
Why this is correct
Diagnostic settings can log full request/response data for auditing.
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