112 lines
4.1 KiB
Bash
112 lines
4.1 KiB
Bash
#!/bin/bash
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# offline-download.sh
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# 在有互联网的机器上执行，将所有依赖打包供离线部署使用
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set -e
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apt install podman-docker
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export WORKDIR=/tmp/k8s-offline
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for d in packages,images,k8s-binaries,helm,nvidia,gpu-operator,kubevirt
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do
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mkdir -p $WORKDIR/$d
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done
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cd $WORKDIR
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echo "=== 下载 Kubernetes 二进制文件 ==="
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K8S_VERSION=v1.29.6
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ARCH=amd64
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curl -L --retry 3 https://dl.k8s.io/${K8S_VERSION}/bin/linux/${ARCH}/kubeadm -o k8s-binaries/kubeadm
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curl -L --retry 3 https://dl.k8s.io/${K8S_VERSION}/bin/linux/${ARCH}/kubelet -o k8s-binaries/kubelet
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curl -L --retry 3 https://dl.k8s.io/${K8S_VERSION}/bin/linux/${ARCH}/kubectl -o k8s-binaries/kubectl
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chmod +x k8s-binaries/*
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echo "=== 下载 containerd ==="
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CONTAINERD_VERSION=1.7.16
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curl -L --retry 3 https://github.com/containerd/containerd/releases/download/v${CONTAINERD_VERSION}/containerd-${CONTAINERD_VERSION}-linux-amd64.tar.gz -o packages/containerd.tar.gz
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echo "=== 下载 runc ==="
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RUNC_VERSION=v1.1.13
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curl -L --retry 3 https://github.com/opencontainers/runc/releases/download/${RUNC_VERSION}/runc.amd64 -o packages/runc && chmod +x packages/runc
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echo "=== 下载 CNI 插件 ==="
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CNI_VERSION=v1.4.1
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curl -L --retry 3 https://github.com/containernetworking/plugins/releases/download/${CNI_VERSION}/cni-plugins-linux-amd64-${CNI_VERSION}.tgz -o packages/cni-plugins.tgz
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echo "=== 下载 Helm ==="
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HELM_VERSION=v3.13.3
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curl -L --retry 3 https://get.helm.sh/helm-${HELM_VERSION}-linux-amd64.tar.gz -o helm/helm.tar.gz
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echo "=== 下载 NVIDIA Driver（仅元信息，实际需手动获取）==="
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echo "注意：NVIDIA 驱动无法直接 wget，请从官网下载："
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echo "https://www.nvidia.com/Download/index.aspx?lang=en-us"
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echo "选择 A100-SXM4 / Data Center Driver for Linux x86_64"
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echo "保存为: nvidia/NVIDIA-Linux-x86_64-535.161.08.run"
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echo "=== 下载 NVIDIA Container Toolkit 依赖（通过 apt 离线包）==="
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# 使用 docker pull + save 方式更可靠
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echo "准备构建本地 apt repo 或使用 .deb 包方式"
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# 推荐方法：在一台联网 Ubuntu 22.04 上执行：
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cat > prepare-debs.sh << 'EOF'
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#!/bin/bash
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mkdir -p /tmp/debs
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apt update
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apt install -y --download-only curl conntrack socat ipvsadm iptables bridge-utils ethtool git wget tar
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apt install -y --download-only nfs-utils nfs-common
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apt install -y --download-only nvidia-driver-535 nvidia-utils-535 nvidia-dkms-535
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apt install -y --download-only nvidia-container-toolkit
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cp /var/cache/apt/archives/*.deb /path/to/offline/nvidia/
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EOF
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echo "请运行 prepare-debs.sh 获取 .deb 包"
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echo "=== 拉取 GPU Operator 所需镜像 ==="
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# GPU Operator 会拉取多个镜像，我们预先列出并导出
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cat > gpu-operator-images.txt << 'EOF'
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nvcr.io/nvidia/gpu-operator:v24.9.0
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nvcr.io/nvidia/gpu-feature-discovery:v0.8.0
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nvcr.io/nvidia/driver:535.161.08-ubuntu22.04
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nvcr.io/nvidia/container-toolkit:1.14.2-ubuntu22.04
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nvcr.io/nvidia/dcgm:3.1.7-3-ubuntu22.04
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nvcr.io/nvidia/k8s-device-plugin:0.14.2-ubi8
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nvcr.io/nvidia/k8s-operator-validator:v1.2.0
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EOF
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while read img; do
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echo "Pulling $img"
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docker pull $img || echo "Failed: $img"
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done < gpu-operator-images.txt
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# 保存镜像为 tar 文件
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docker save $(cat gpu-operator-images.txt | tr '\n' ' ') -o images/gpu-operator-images.tar
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echo "=== 拉取 KubeVirt 组件镜像 ==="
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KV_VERSION=v1.1.0
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cat > kubevirt-images.txt << EOF
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quay.io/kubevirt/virt-operator:${KV_VERSION}
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quay.io/kubevirt/virt-api:${KV_VERSION}
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quay.io/kubevirt/virt-controller:${KV_VERSION}
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quay.io/kubevirt/virt-handler:${KV_VERSION}
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quay.io/kubevirt/virt-launcher:${KV_VERSION}
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quay.io/kubevirt/cdi-operator:v1.50.0
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quay.io/kubevirt/cdi-apiserver:v1.50.0
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quay.io/kubevirt/cdi-uploadproxy:v1.50.0
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quay.io/kubevirt/cdi-cloner:v1.50.0
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quay.io/kubevirt/cdi-importer:v1.50.0
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quay.io/kubevirt/cdi-uploadserver:v1.50.0
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EOF
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while read img; do
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docker pull $img || echo "Failed: $img"
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done < kubevirt-images.txt
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docker save $(cat kubevirt-images.txt | tr '\n' ' ') -o images/kubevirt-images.tar
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echo "=== 创建最终离线包 ==="
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tar -czf k8s-offline-all.tar.gz .
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echo "✅ 所有离线资源已生成：k8s-offline-all.tar.gz"
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echo "请将其复制到目标环境并解压"
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