Essential Metrics for AI Hardware Management
TechTarget, Thursday, July 30th, 2026
Organizations must track compute, network, storage and business metrics to optimize AI infrastructure and manage costs.
AI infrastructure demands comprehensive monitoring across four metric categories to maximize performance and control expenses.
Compute metrics like GPU memory saturation and utilization ensure processors operate efficiently, while network metrics monitor data transfer speeds between GPUs and nodes.
Storage metrics track throughput and latency to prevent bottlenecks that starve GPUs of data. Tools like Datadog, Grafana Cloud, and NVIDIA DCGM Exporter help infrastructure teams collect and analyze these critical performance indicators.