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/airunway-aks-setup

@b3c238e
by microsoftmicrosoft/skills3.1k stars
351

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".

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Use this Skill: https://skilld.dev/gh/microsoft/skills/airunway-aks-setup

This session only. Nothing lands on disk.

referencesgpu-profiles.md

≈642 tokens on demand. Your agent reads this file only when SKILL.md points to it.

GPU Compatibility Reference

This reference is used by the airunway-aks-setup skill during Step 3 — GPU Assessment to match detected GPU hardware to known compatibility profiles and surface constraints before model deployment.

GPU Profiles

GPU Model VRAM (GB) bfloat16 float16 Attention Backends Compute Capability Notes
T4 16 No Yes XFORMERS 7.5 No bfloat16 — must use float16 or float32.
V100 (16 GB) 16 No Yes XFORMERS 7.0 Limited flash attention. Prefer xformers.
V100 (32 GB) 32 No Yes XFORMERS 7.0 Same dtype constraints as 16 GB variant.
A10 24 Yes Yes FLASH_ATTN, XFORMERS 8.6 Single-slot Ampere GPU.
A10G 24 Yes Yes FLASH_ATTN, XFORMERS 8.6 Good general-purpose GPU. Common in AWS.
L4 24 Yes Yes FLASH_ATTN, XFORMERS 8.9 Inference-optimized. Common in GCP and Azure.
L40S 48 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 8.9 Ada Lovelace. Growing availability on Azure.
A100 (40 GB) 40 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 8.0 High-performance training and inference.
A100 (80 GB) 80 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 8.0 Recommended for large models (70B+).
H100 80 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 9.0 Highest single-GPU performance.
H200 (SXM) 141 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 9.0 Maximum memory (HBM3e).
H20 96 Yes Yes FLASH_ATTN, TRITON_ATTN, XFORMERS 9.0 China-market H100 derivative. 96 GB HBM3.

Attention Backends

Backend Description Min Compute Capability
FLASH_ATTN FlashAttention-2 — fastest, lowest memory 8.0 (Ampere+)
TRITON_ATTN Triton-based attention — good performance 8.0 (Ampere+)
XFORMERS Memory-efficient attention — works on older GPUs 7.0 (Volta+)

Compatibility Warnings

Surface these warnings when the following GPUs are detected:

T4

Warning: T4 GPUs do not support bfloat16. You must configure --dtype float16 in serving arguments. Failure to do so causes errors or silent dtype casting.

V100

Warning: V100 GPUs do not support bfloat16 and have limited flash attention support. Use xformers backend and --dtype float16.

Model Sizing & Recommendations

For VRAM sizing estimates and starter model recommendations, see model-sizing.md.

Source: SKILL.md on GitHub

Third-party checks

No alerts15d3 checks · Risk SAFE
  • Gen Agent Trust Hub15d

    This skill provides a structured walkthrough for setting up AI Runway on Azure Kubernetes Service (AKS). It includes cluster verification, controller installation, hardware assessment, and model deployment using standard tools like kubectl and make. The skill follows secure practices for handling HuggingFace tokens and manages infrastructure transparently within the user's provided Kubernetes context.

  • Socket15d

    No alerts

  • Snyk15d

    Risk: LOW · No issues

Provenance

Signed by skilld at b3c238e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 2 months ago

Capability

metadata
{
  "author": "Microsoft",
  "version": "1.1.1"
}
argument-hint
[skip-to-step N]

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