AI factories span an enormous range of interconnected systems, from GPU nodes and NVLink fabric to Spectrum-X Ethernet, job schedulers, workload managers such as Slurm, and active workloads. When an issue occurs, its root cause may originate in one layer but appear as a symptom in another.
By ingesting full-stack telemetry in real time and applying ML-based, topology-aware correlation, NVIDIA Minerva reveals the relationships that matter: how a network anomaly affects GPU utilization or how a scheduler event contributes to degraded job throughput.
Operations teams gain a single, unified view of the AI factory instead of the fragmented, siloed tools that make cross-layer debugging slow and costly.