airunway-aks-setup

SKILL.md

End-to-end AI Runway setup on AKS from bare cluster to running model deployment.

Walks through six sequential steps: cluster verification, controller installation, GPU assessment, inference provider setup, first model deployment, and summary

Includes cost awareness warnings for GPU node pools and error handling for common deployment failures

Supports resuming from any step via skip-to-step N argument if setup is partially complete

Uses only kubectl and make CLI tools; no MCP tools required

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 (troubleshooting)