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…

Azure Monitor is valuable for production observability, but it is not the appropriate mechanism for the stated development-time requirement: manually inspecting individual prompt-flow executions and comparing prompt variants with their inputs, outputs, token consumption, and latency. Prompt flow provides purpose-built run outputs and tracing. Microsoft documents that after a flow execution, the Outputs experience exposes detailed flow inputs and outputs. When tracing is enabled, the Trace view provides execution duration and token information and lets the developer expand individual steps to inspect their inputs and execution details. Prompt flow also directly supports variants and batch/evaluation runs. Multiple variants can be executed and compared, while the run details expose per-test-case inputs, outputs, token counts, duration, and evaluation results. Microsoft explicitly states that multiple runs can be selected to compare their metrics and outputs. Azure Monitor/Application Insights can collect operational metrics such as token consumption and flow or node latency for deployed applications, but that telemetry is primarily intended for monitoring and troubleshooting rather than the interactive prompt-variant evaluation workflow described here. Therefore, the proposed solution does not meet the goal. Study Guide Reference: Implement generative AI quality assurance and observability --- prompt evaluation, tracing, debugging, token consumption, latency, and prompt-variant comparison.