A developer's blog post discusses observability for AI infrastructure, emphasizing the need to monitor beyond traditional CPU and memory metrics. The post outlines four layers of AI observability—Kube…
AI agents cannot see real-time GPU utilization, VRAM, temperatures, or active processes without a GPU-aware MCP server, creating an operational bottleneck for autonomous infrastructure operations. The…
A GPU training pipeline at a major AI company breached its SLA despite showing 97% GPU utilization across all monitoring tools (Datadog, Grafana, nvidia-smi). Using eBPF kernel tracing, an SRE identif…
NVIDIA released an open-source GPU Usage Monitor that provides real-time visibility into GPU allocation, compute utilization, memory consumption, and pod status across Kubernetes clusters. The tool in…