Skip to content
Back to skills

Nvidia Ai Operations Day2

ASecurity

Use this skill when reviewing day-2 operations of NVIDIA GPU fleets — DCGM exporter and DCGM-Diag posture, GPU telemetry into Prometheus/Grafana, MIG partitioning lifecycle, GPU health and Xid error response, fleet upgrade paths, and incident response for GPU-failure modes. Trigger when the user asks how a GPU fleet is monitored, whether DCGM is wired, whether Xid signatures map to runbooks, or whether the deployment meets NCP-AIO certification expectations.

  • 23 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added May 29, 2026
devopsgonodegitsecuritydocumentation

Works with

  • cli

Security analysis

A100/100

Scanned May 29, 2026

npx -y skills add Raishin/vanguard-frontier-agentic --skill nvidia-ai-operations-day2 --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Nvidia Ai Operations Day2?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Nvidia Ai Operations Day2
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/raishin-nvidia-ai-operations-day2/badge)](https://www.skillsdirectory.com/skills/raishin-nvidia-ai-operations-day2)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: nvidia-ai-operations-day2
description: Use this skill when reviewing day-2 operations of NVIDIA GPU fleets — DCGM exporter and DCGM-Diag posture, GPU telemetry into Prometheus/Grafana, MIG partitioning lifecycle, GPU health and Xid error response, fleet upgrade paths, and incident response for GPU-failure modes. Trigger when the user asks how a GPU fleet is monitored, whether DCGM is wired, whether Xid signatures map to runbooks, or whether the deployment meets NCP-AIO certification expectations.
allowed-tools: Read Grep Glob
metadata:
  author: "github: Raishin"
  version: "0.1.0"
  updated: "2026-05-10"
  category: observability
---

# NVIDIA AI Operations (Day-2) Review

## Purpose

Review operational posture of NVIDIA GPU fleets against the NCP-AIO body of knowledge: DCGM and DCGM-Exporter coverage, MIG partitioning lifecycle, Xid error classification and runbooks, fleet driver/firmware upgrade orchestration, and GPU-aware incident response.

## Lean operating rules

- Prefer live evidence (`dcgmi diag`, `dcgmi health`, `nvidia-smi --query-gpu=...`, Prometheus DCGM metrics) when the active client exposes it; otherwise fall back to NVIDIA DCGM documentation, sanitized dashboards, and Xid reference tables.
- Separate confirmed facts from inference. If DCGM coverage, alerting rules, or Xid classification was not directly queried, say so.
- Treat absence of DCGM exporter on production GPU nodes as a high finding — fleet is operationally blind.
- Treat ungated driver/firmware rolling upgrade (no pre-drain, no canary, no rollback path) as a high finding.
- Treat undocumented Xid signature → runbook mapping as a medium finding — incidents will be triaged from scratch.
- Treat GPU-Operator / device-plugin running with default permissive securityContext on multi-tenant clusters as a high finding.
- Treat MIG re-partitioning performed live without workload drain as a medium finding (running contexts are killed).
- Treat alerting that does not cover ECC double-bit errors, NVLink errors, or row-remapping pending as a medium finding.

## Response minimum

Return, at minimum:
- the scoped target (cluster/fleet, exporter version) and evidence level,
- DCGM exporter coverage and alert posture,
- MIG partitioning lifecycle posture,
- Xid → runbook coverage,
- driver/firmware upgrade discipline,
- safe next actions and assumptions or blockers.

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…