Microsoft Azure AI Engineer Associate AI-102 Practice Question
You administer a multiservice Azure AI resource named contoso-ai. Developers report occasional 5xx responses when calling the resource's REST endpoint, but the Azure portal Metrics chart shows no obvious pattern. You must collect per-request data (operation name, response status, subscription key) for the last 24 hours and query it in your existing Log Analytics workspace. What should you do first?
Enable Application Insights HTTP dependency tracking in each calling application.
Create a diagnostic setting on contoso-ai that streams the RequestLogs category to the Log Analytics workspace.
Enable export of the Azure activity log for the contoso-ai resource group to the Log Analytics workspace.
Configure a Network Watcher connection monitor test that targets the contoso-ai endpoint.
The detailed, per-request information you require is emitted by the Azure AI Services platform as RequestLogs. By creating a diagnostic setting on the contoso-ai resource and selecting the RequestLogs (or AllLogs) category, you can stream those logs directly to an Azure Monitor Log Analytics workspace. Once the diagnostic setting is in place, every call-including its operation name, response code, and the key used-is recorded and becomes immediately queryable with Kusto queries. Exporting the subscription's activity log would only provide control-plane events, not request-level data. Connection Monitor tests and Application Insights dependency tracking would require additional configuration on every client and do not automatically capture the platform-level fields requested.
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Microsoft Azure AI Engineer Associate AI-102
Plan and manage an Azure AI solution
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