ai infrastructure

A Bash-first, distro-agnostic guide to building a budget-friendly AI Infrastructure Lab on Linux: install base tools, Docker, and NVIDIA Container Toolkit; build GPU-ready PyTorch containers; share data via NFS; optionally orchestrate multi-node workloads with k3s; monitor and benchmark with nvtop and simple tests; includes per-distro commands, a two-node example, and scripts for reproducibility, portability, and cost control.

Build a Linux AI infrastructure dashboard fast with Prometheus, Node Exporter, and Grafana: install on a monitoring host and nodes via Bash-friendly, distro‑agnostic steps; wire scrape targets; import ready-made Grafana dashboards; optionally add NVIDIA DCGM GPU, job, and storage metrics; then harden, alert, and tune retention—so you can spot CPU, RAM, disk, network bottlenecks and boost GPU utilization.

Practical, Bash-first Linux playbook to validate AI infrastructure: install fio, iperf3, nvme-cli, nvtop/htop, sysstat, Podman via apt/dnf/zypper, then run five repeatable checks—node inventory, NVMe throughput/IOPS (fio), east–west bandwidth (iperf3), GPU PyTorch smoke test with live monitoring, and container parity. Includes snapshot script, NVIDIA/AMD notes, and tips to catch PCIe, disk, MTU, and throttling issues across nodes.