Option B preserves the historical evidence needed to diagnose the regression. The Lakeflow Jobs UI provides run history, duration information, task details, links to the compute resource, and task metrics. Comparing several slow and normal runs shows whether the increase is consistent or intermittent. Cluster metrics such as CPU utilization, memory pressure, disk I/O, and network activity can then reveal resource spikes or bottlenecks that correlate with the longer runs. Automatically increasing cluster size before diagnosis could hide the cause and increase cost. Archiving old runs or resetting a baseline removes useful comparison data. Rerunning the job once does not make seven days of historical information irrelevant and cannot establish a trustworthy new baseline. Therefore, comparing run-history and cluster metrics, as stated in option B, is the appropriate troubleshooting action.

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