Agent Skills › microsoft/azure-skills › aks-gpu-inference

aks-gpu-inference

GitHub

用于诊断 AKS GPU 和 KAITO 相关故障的只读分析技能，涵盖调度、显存 OOM、模型加载及自动伸缩等问题。

.github/plugins/aks-skills/skills/aks-gpu-inference/SKILL.md microsoft/azure-skills

Trigger Scenarios

GPU pod Pending Insufficient nvidia.com/gpu KAITO Workspace not ready model-load OOM

Install

npx skills add microsoft/azure-skills --skill aks-gpu-inference -g -y

More Options

Non-standard path

npx skills add https://github.com/microsoft/azure-skills/tree/main/.github/plugins/aks-skills/skills/aks-gpu-inference -g -y

Use without installing

npx skills use microsoft/azure-skills@aks-gpu-inference

指定 Agent (Claude Code)

npx skills add microsoft/azure-skills --skill aks-gpu-inference -a claude-code -g -y

安装 repo 全部 skill

npx skills add microsoft/azure-skills --all -g -y

预览 repo 内 skill

npx skills add microsoft/azure-skills --list

SKILL.md

Frontmatter

{
    "name": "aks-gpu-inference",
    "license": "MIT",
    "metadata": {
        "author": "Microsoft",
        "version": "1.1.1"
    },
    "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)."
}

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

Bind subscription, cluster, kube context, pool, and affected resource.
Capture exact events/status and observed gpuProfile; state which reads ran.
Route to scheduling, observability, KAITO, or scaling.
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.
For KAITO not-ready, warn that Workspace deletion leaves its GPU pools; cleanup is separate and needs explicit authorization.
Report evidence, confidence, missing evidence, and owner handoff.

Require explicit authorization before scaling, cordon/drain, deletion, add-on enablement, or monitoring mutation.

Error Handling

Condition	Response
Missing/contradictory evidence	Mark unconfirmed; request the owner/read
Unknown profile	Preserve evidence; do not prescribe stack repair
Mutation required	Propose separately and wait for authorization

Version History

cf79ce8 Current 2026-10-19 11:53

Metadata

Files: 0
Version: cf79ce8
Hash: 0968850f
Indexed: 2026-10-19 11:53

aks-gpu-inference