AI-102 Implement agentic AI solutions Practice Question
A company is deploying an agent built with Azure AI Foundry Agent Service to production. The agent must log all interactions for auditing and compliance. The team needs to capture the full conversation history, including tool calls and their results. Which approach should they use?
⚠ Common exam trap
The trap here is relying on the agent's built-in conversation history for auditing, but that history is session-scoped and not designed for compliance logging.
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
✓
Enable diagnostic settings on the Azure AI Foundry resource to send logs to Azure Monitor and Log Analytics.
Enabling diagnostic settings to send logs to Azure Monitor and Log Analytics is the correct approach because it provides a centralized, durable, and queryable audit trail of all agent interactions, including tool calls. Other methods are either local, manual, or incomplete, and do not meet compliance needs for production auditing.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the agent's built-in conversation history feature and periodically export it manually via the portal.
Why it's wrong here
The built-in conversation history is designed for maintaining context during a session, not for long-term auditing. Manual exports are error-prone and not automated, making them unreliable for compliance. This approach does not capture tool calls and results comprehensively and lacks the durability of a logging service.
- ✗
Configure the agent to write conversation logs to a local file on the client application.
Why it's wrong here
Writing logs to a local file on the client application is not suitable for centralized auditing and compliance. It is prone to loss, tampering, and does not scale. It also lacks the ability to capture server-side tool calls and results. For production auditing, a centralized logging solution is required.
- ✗
Instruct the agent to include a summary of each interaction in its response for the user to save.
Why it's wrong here
Instructing the agent to summarize interactions in its response does not create a reliable audit log. Users might not save the summaries, and the summaries may omit critical details like tool calls. This approach is not tamper-proof and does not meet compliance requirements for comprehensive logging.
- ✓
Enable diagnostic settings on the Azure AI Foundry resource to send logs to Azure Monitor and Log Analytics.
Why this is correct
Enabling diagnostic settings on the Azure AI Foundry resource allows you to stream logs, including agent interactions and tool calls, to Azure Monitor and Log Analytics. This provides a centralized, durable audit trail. You can then query and analyze logs for compliance. This is the recommended approach for auditing agent interactions in production.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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