Airunway Aks Setup

You've got an AKS cluster and want to run LLMs on it. This walks you through the full setup: verifying the cluster, installing the AI Runway controller and CRDs, checking what GPUs you have, picking an inference provider like KAITO or vLLM, and deploying your first model. It's structured as six sequential steps with references for each, and you can skip ahead if you're resuming mid-setup. The main thing to watch is GPU cost, an A100 node can run you $3 to $5 an hour, so don't just click through without noticing. Good for first-time AI Runway setups where you need the full walkthrough instead of hunting through docs.

skills.sh installs: 452K
GitHub stars: 1.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add microsoft/azure-skills --skill airunway-aks-setup --agent claude-code

Installs into .claude/skills of the current project.

Files

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)