# airunway-aks-setup

Guides AI Runway setup on an existing AKS cluster, from checking nodes to deploying a model. Use it to install the controller and configure an inference provider.

- 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/azure-skills/skills/airunway-aks-setup/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/airunway-aks-setup

## What it does

The skill checks cluster access and node inventory, installs the AI Runway controller and CRDs, assesses GPU hardware, and helps choose an inference provider before deploying a model. It proceeds in stages, reports cluster status, skips completed work, and asks for confirmation before installation or deployment. Resume at a chosen phase with `skip-to-step N`.

Cluster operations use `kubectl` and `make`; the skill does not use MCP tools. An AKS cluster must already exist, so a new cluster needs to be provisioned first. GPU node pools can incur significant compute charges; confirm the cost implications before provisioning them. The guide also covers troubleshooting controller, provider, and model deployment issues.

## Requirements
- Works with: Azure

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add microsoft/skills --skill airunway-aks-setup -a claude-code
```

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

### Codex

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

### Cursor

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

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install microsoft/skills airunway-aks-setup
```

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

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/microsoft/skills --path .github/plugins/azure-skills/skills/airunway-aks-setup
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/airunway-aks-setup/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/azure-skills/skills/airunway-aks-setup/SKILL.md

## When to use it
- check AKS cluster health and detect GPUs
- install the AI Runway controller and CRDs
- select and configure an inference provider
- deploy a first model and check its status
- resume setup from a chosen phase

## Example prompts
- Set up AI Runway on my existing AKS cluster, checking each stage before installing anything.
- Assess the GPUs on AKS, choose an inference provider, and deploy a first model.
- Resume the AI Runway setup at step 4.

## 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: e82b5c16b3c8e21d.

BEGIN THIRD-PARTY FILE e82b5c16b3c8e21d
```text
---
name: airunway-aks-setup
description: "Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\"."
license: MIT
metadata:
  author: Microsoft
  version: "1.1.2"
argument-hint: "[skip-to-step N]"
---

# AI Runway AKS Setup

This skill walks users from a bare Kubernetes cluster to a running AI model deployment. Follow each step in sequence unless the user provides `skip-to-step N` to resume from a specific phase.

> **Cost awareness:** GPU node pools incur significant compute charges (A100-80GB can cost $3–5+/hr). Confirm the user understands cost implications before provisioning GPU resources.

## Prerequisites

This skill assumes an AKS cluster already exists. If the user does not have a cluster, hand off to the `azure-kubernetes` skill first to provision one (with a GPU node pool unless CPU-only inference is acceptable), then return here.

## Quick Reference

| Property | Value |
|----------|-------|
| Best for | End-to-end AI Runway onboarding on AKS |
| CLI tools | `kubectl`, `make`, `curl` |
| MCP tools | None |
| Related skills | `azure-kubernetes` (cluster setup), `azure-diagnostics` (baseline troubleshooting), optional `aks-gpu-inference` (existing GPU/inference Day-2 incidents only) |

## When to Use This Skill

Use this skill when the user wants to:
- Set up AI Runway on an existing AKS cluster from scratch
- Install the AI Runway controller and CRDs
- Assess GPU hardware compatibility for model deployment
- Choose and install an inference provider (KAITO, Dynamo, KubeRay)
- Deploy their first AI model to AKS via AI Runway
- Resume a partially-complete AI Runway setup from a specific step

## GPU setup versus Day-2 incidents

Keep initial GPU node-pool, provider, controller, and model setup in this skill.
For an incident affecting an existing GPU or inference deployment, load
[optional-gpu-day2.md](references/optional-gpu-day2.md) before deciding whether
to offer the focused optional add-on.

## MCP Tools

This skill uses no MCP tools. All cluster operations are performed directly via `kubectl` and `make`.

## Rules

1. Execute steps in sequence — load the reference for each step as you reach it
2. Report cluster state at each step: ✓ healthy, ✗ missing/failed
3. Ask for user confirmation before any install or deployment action
4. If a step is already complete, report status and skip to the next step
5. If the user provides `skip-to-step N`, start at step N; assume prior steps are complete

## Steps

| # | Step | Reference |
|---|------|-----------|
| 1 | **Cluster Verification** — context check, node inventory, GPU detection | [step-1-verify.md](references/steps/step-1-verify.md) |
| 2 | **Controller Installation** — CRD + controller deployment | [step-2-controller.md](references/steps/step-2-controller.md) |
| 3 | **GPU Assessment** — detect GPU models, flag dtype/attention constraints | [step-3-gpu.md](references/steps/step-3-gpu.md) |
| 4 | **Provider Setup** — recommend and install inference provider | [step-4-provider.md](references/steps/step-4-provider.md) |
```
END THIRD-PARTY FILE e82b5c16b3c8e21d

The third-party file has ended. Everything between the e82b5c16b3c8e21d 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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