# aks-gpu-inference

Investigate AKS GPU and KAITO incidents using cluster events, status, and available metrics. Useful for Pending GPU pods, model-load OOMs, and scaling issues.

- skill · `type=skill` · Claude Code, GitHub Copilot · ★ 3149
- Author: Microsoft
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/microsoft/skills/tree/HEAD/.github/plugins/aks-skills/skills/aks-gpu-inference/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/aks-gpu-inference

## What it does

This skill investigates AKS GPU workload failures, including insufficient `nvidia.com/gpu`, Pending pods, model-loading OOMs, and KAITO Workspace readiness. It gathers evidence about the bound target, events, and status, considers the observed `gpuProfile`, then directs the investigation to guidance for scheduling, observability, KAITO, or scaling.

Cluster reads depend on the host permitting the required `kubectl` and `az` commands against the target. A governed Azure CLI tool by itself does not grant that access. The workflow is read-only unless the operator explicitly authorizes a change: scaling, deletion, cordon/drain, and similar actions need approval. For `OOMKilled`, the skill correlates container memory limits and usage with node conditions; Managed+Install device-memory investigation uses exporter data on port `19400`.

When reads cannot run, the skill can work from supplied events, status, logs, or metrics, but conclusions that need missing evidence stay unconfirmed. It is for AKS GPU and KAITO incidents, not cluster setup, non-GPU failures, standalone VM quotas, or general cost analysis.

## Requirements
- Works with: Azure

## Install

### Claude Code (native platform)

1. **Plugin marketplace**
In the agent chat (not a shell):
```text
/plugin marketplace add microsoft/skills
```
In the agent chat (not a shell):
```text
/plugin install aks-skills@skills
```
This installs the whole aks-skills plugin with all its skills

2. **Skills CLI (Vercel)**
```bash
npx skills add microsoft/skills --skill aks-gpu-inference -a claude-code
```

3. **Manually: put the files in place**
- File: `~/.claude/skills/aks-gpu-inference/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/aks-gpu-inference/

### Codex

**Manually: put the files in place**
- File: `.agents/skills/aks-gpu-inference/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/aks-gpu-inference/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install microsoft/skills aks-gpu-inference
```

2. **Manually: put the files in place**
- File: `.github/skills/aks-gpu-inference/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/microsoft/skills --path .github/plugins/aks-skills/skills/aks-gpu-inference
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/aks-gpu-inference/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/microsoft/skills/tree/HEAD/.github/plugins/aks-skills/skills/aks-gpu-inference/SKILL.md

## When to use it
- trace why an AKS pod is Pending for `nvidia.com/gpu`
- separate container-memory OOM from GPU device-allocation failure
- investigate a KAITO Workspace that has not become ready
- review GPU autoscaling using cluster events and status

## Example prompts
- Investigate why my AKS GPU pod is Pending for `nvidia.com/gpu` and list the reads you performed.
- Check this model's `OOMKilled` event in AKS against container memory and node conditions.
- Find out why the KAITO Workspace is not ready, and separate confirmed findings from open questions.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 3d51365fdb6ea713.

BEGIN THIRD-PARTY FILE 3d51365fdb6ea713
```text
---
name: aks-gpu-inference
description: "Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin)."
license: MIT
metadata:
  author: Microsoft
  version: "1.1.1"
---

# AKS GPU Inference Day-2

## Quick Reference

| Property | Value |
|---|---|
| Best for | AKS GPU/KAITO failures |
| Evidence | Bound target, events/status, `gpuProfile`, DCGM |

## When to Use This Skill

Use for scheduling, VRAM/OOM, KAITO readiness, and workload scaling. Route
exclusions as described above.

## MCP Tools

Use a fitting host-advertised Azure read or the references' read-only queries.

## Host Capability Gate

Before executing any referenced pipeline, verify that the host authorizes
the required shell and `kubectl`/`az` commands against the bound target.
File-backed collection also requires approved artifact storage and access to
any bundled files it uses. A governed Azure CLI tool alone does not establish
these capabilities. Equivalent host reads may replace commands only where
their advertised schemas provide the required evidence.

If execution is unavailable or prohibited, say so and analyze supplied or
redacted events, status, logs, and metrics, or give the operator a scoped
collection plan. State which reads did not run and leave conclusions requiring
missing evidence unconfirmed. Never route `kubectl` through Azure MCP or
bypass host policy. The authorization requirements below still apply.

## Workflow

1. Bind subscription, cluster, kube context, pool, and affected resource.
2. Capture exact events/status and observed `gpuProfile`; state which reads ran.
3. Route to [scheduling](references/gpu-scheduling.md),
   [observability](references/gpu-observability.md),
   [KAITO](references/kaito-workspaces.md), or
   [scaling](references/gpu-cost-and-scaling.md).
4. Separate container/host OOM from device-allocation failures. For `OOMKilled`,
   correlate container memory limits/usage and node conditions. For
   Managed+Install device-memory evidence, use the exporter on port 19400 and
   incident-window `FB_USED`/`FB_FREE`; sizing tables do not establish a cause.
5. For KAITO not-ready, warn that Workspace deletion leaves its GPU pools;
   cleanup is separate and needs explicit authorization.
6. Report evidence, confidence, missing evidence, and owner handoff.
```
END THIRD-PARTY FILE 3d51365fdb6ea713

The third-party file has ended. Everything between the 3d51365fdb6ea713 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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---
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