gitops/docs/gpu-k8s-role.md

GPU Kubernetes Role

This document describes how to use the gpu-k8s role to deploy a simple Kubernetes cluster with NVIDIA GPU support.

Overview

The role performs three main tasks:

1. Create the Kubernetes cluster using sealos. It runs the provided sealos run command to bootstrap the master and worker nodes.
2. Install NVIDIA drivers and container runtime on the target hosts so that Kubernetes can access GPU resources.
3. Verify GPU access by deploying the official NVIDIA device plugin and running a small CUDA workload.

The following command is used to create the cluster (example with one master and one worker):

sealos run \
  registry.cn-shanghai.aliyuncs.com/labring/kubernetes:v1.29.9 \
  registry.cn-shanghai.aliyuncs.com/labring/cilium:v1.13.4 \
  registry.cn-shanghai.aliyuncs.com/labring/helm:v3.9.4 \
  --masters 172.16.11.120 \
  --nodes 172.16.11.152 \
  --env '{}' \
  --cmd "kubeadm init --skip-phases=addon/kube-proxy"

After the cluster is running the role installs the NVIDIA device plugin and runs a test pod to ensure nvidia-smi works inside the cluster.

Usage

Add the role to your playbook:

- hosts: all
  roles:
    - gpu-k8s

Example playbook snippet defining the IP lists:

- hosts: all
  vars:
    master_ips:
      - "172.16.11.120"
    node_ips:
      - "172.16.11.152"
  roles:
    - gpu-k8s

The playbook expects master_ips and node_ips variables which are lists of IP addresses. Up to three masters can be specified.

Run the playbook with your inventory that contains the master and node IP addresses.

ansible-playbook -i inventory/hosts/all playbooks/demo_gpu_k8s.yml

The final step prints the output of nvidia-smi from inside a Kubernetes pod, confirming that the GPU is available.