airunway-aks-setuplisted

# 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) | ## 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 ## MCP Tools This skill uses no MCP tools. All cluster operations are performed directly via `kubectl` and `make`. ## Rules 1. Execute steps in sequence — l