Interface RX/TX Error Spikes Correlate with AI Job Performance Degradation

Abnormal interface RX/TX errors or discards (detected via anomaly scoring) in AI cluster fabrics directly impact distributed training job completion time (JCT). Even minor physical layer issues cause step-time jitter and GPU idle time, as AI frameworks cannot tolerate packet loss like traditional TCP workloads. CloudVision CV UNO correlates interface health with AI job metrics for root cause analysis.

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