airunway-aks-setup

Topics in the source

• AI Runway AKS Setup
• Prerequisites
• Quick Reference
• When to Use This Skill
• GPU setup versus Day-2 incidents
• MCP Tools
• Rules
• Steps

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. 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. | 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) | 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 fi

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