65 lines
1.8 KiB
Markdown
65 lines
1.8 KiB
Markdown
# GPU Kubernetes Role
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This document describes how to use the `gpu-k8s` role to deploy a simple Kubernetes cluster with NVIDIA GPU support.
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## Overview
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The role performs three main tasks:
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1. **Create the Kubernetes cluster** using [sealos](https://github.com/labring/sealos). It runs the provided `sealos run` command to bootstrap the master and worker nodes.
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2. **Install NVIDIA drivers and the NVIDIA container toolkit** on the target hosts so that Kubernetes can access GPU resources.
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3. **Verify GPU access** by deploying the official NVIDIA device plugin and running a small CUDA workload.
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The following command is used to create the cluster (example with one master and one worker):
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```bash
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sealos run \
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registry.cn-shanghai.aliyuncs.com/labring/kubernetes:v1.29.9 \
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registry.cn-shanghai.aliyuncs.com/labring/cilium:v1.13.4 \
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registry.cn-shanghai.aliyuncs.com/labring/helm:v3.9.4 \
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--masters 172.16.11.120 \
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--nodes 172.16.11.152 \
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--env '{}' \
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--cmd "kubeadm init --skip-phases=addon/kube-proxy"
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```
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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.
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## Usage
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Add the role to your playbook:
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```yaml
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- hosts: all
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roles:
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- gpu-k8s
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```
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Example playbook snippet defining the IP lists:
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```yaml
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- hosts: all
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vars:
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master_ips:
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- "172.16.11.120"
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node_ips:
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- "172.16.11.152"
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roles:
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- gpu-k8s
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```
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The playbook expects `master_ips` and `node_ips` variables which are lists of IP addresses. Up to
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three masters can be specified.
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Run the playbook with your inventory that contains the master and node IP addresses.
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```bash
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ansible-playbook -i inventory/hosts/all playbooks/demo_gpu_k8s.yml
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```
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The final step prints the output of `nvidia-smi` from inside a Kubernetes pod, confirming that the GPU is available.
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