k3d#
rancher/k3d 
常用命令#
k3d cluster list
kubectl config get-contexts
k3d kubeconfig get cluster-1 > ~/.kube/cluster-1
chmod 600 ~/.kube/cluster-1
k3d kubeconfig get cluster-2 > ~/.kube/cluster-2
chmod 600 ~/.kube/cluster-2
k3d kubeconfig get cluster-3 > ~/.kube/cluster-3
chmod 600 ~/.kube/cluster-3
k3d kubeconfig get cluster-4 > ~/.kube/cluster-4
chmod 600 ~/.kube/cluster-4
k3d kubeconfig get cluster-5 > ~/.kube/cluster-5
chmod 600 ~/.kube/cluster-5
k3d kubeconfig get cluster-6 > ~/.kube/cluster-6
chmod 600 ~/.kube/cluster-6
k3d kubeconfig get cluster-7 > ~/.kube/cluster-7
chmod 600 ~/.kube/cluster-7
k3d kubeconfig get cluster-8 > ~/.kube/cluster-8
chmod 600 ~/.kube/cluster-8
k3d kubeconfig get cluster-9 > ~/.kube/cluster-9
chmod 600 ~/.kube/cluster-9
cat <<'EOF' >> ~/.bashrc
alias kctx='kubectl config use-context'
alias c1='kctx k3d-cluster-1'
alias c2='kctx k3d-cluster-2'
alias c3='kctx k3d-cluster-3'
alias c4='kctx k3d-cluster-4'
alias k1='KUBECONFIG=~/.kube/cluster-1 kubectl'
alias k2='KUBECONFIG=~/.kube/cluster-2 kubectl'
alias k3='KUBECONFIG=~/.kube/cluster-3 kubectl'
alias k4='KUBECONFIG=~/.kube/cluster-4 kubectl'
EOF
# 安装 k3d
wget -q -O - https://raw.githubusercontent.com/k3d-io/k3d/main/install.sh | bash
# https://hub.docker.com/r/rancher/k3s/tags
cat << 'EOF' > k3d-config-cluster-1.yaml
apiVersion: k3d.io/v1alpha5
kind: Simple
metadata:
name: cluster-1
image: rancher/k3s:v1.35.1-k3s1
servers: 1
agents: 2
kubeAPI:
host: "127.0.0.1"
hostIP: "0.0.0.0"
hostPort: "8521"
registries:
config: |
mirrors:
"docker.io":
endpoint:
- https://hub.kingye.me
EOF
k3d cluster create --config k3d-config-cluster-1.yaml --verbose
安装配置#
# 跑多个 k3s，要提高 inotify + file limit
sudo tee /etc/sysctl.d/99-k3d-inotify.conf >/dev/null <<'EOF'
fs.inotify.max_user_instances = 4048
fs.inotify.max_user_watches = 1048576
fs.inotify.max_queued_events = 65536
fs.file-max = 2097152
EOF
sudo sysctl --system
GPU#
k3s-gpu#
# 为 Docker daemon 配置代理（永久生效）
sudo mkdir -p /etc/systemd/system/docker.service.d
sudo tee /etc/systemd/system/docker.service.d/http-proxy.conf > /dev/null <<'EOF'
[Service]
Environment="HTTP_PROXY=http://218.16.121.13:1080"
Environment="HTTPS_PROXY=http://218.16.121.13:1080"
Environment="NO_PROXY=localhost,127.0.0.1"
EOF
sudo systemctl daemon-reload
sudo systemctl restart docker
# https://hub.docker.com/r/nvidia/cuda/tags
cat << 'DOCKERFILE_EOF' > Dockerfile
FROM nvidia/cuda:12.8.1-base-ubuntu24.04
ARG DEBIAN_FRONTEND=noninteractive
# 版本参数
ARG K3S_VERSION="v1.35.1+k3s1"
ARG KUBECTL_VERSION="v1.35.1"
ARG CRICTL_VERSION="v1.35.0"
# 下载代理前缀（可为空）
# 例如:
# "https://proxy.kingye.me/proxy/"
# 或者置空 "" 走直连
ARG DOWNLOAD_PROXY_PREFIX="https://proxy.kingye.me/proxy/"
SHELL ["/bin/bash", "-o", "pipefail", "-c"]
ENV PATH="/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin"
# 1) 基础工具 + containerd(带 ctr) + CNI plugins + NVIDIA Container Toolkit + fuse-overlayfs
RUN set -eux; \
apt-get update; \
apt-get install -y --no-install-recommends \
ca-certificates curl gnupg tar \
iptables iproute2 \
iputils-ping conntrack ethtool \
containernetworking-plugins \
fuse-overlayfs \
containerd; \
\
# NVIDIA Container Toolkit repo
mkdir -p /usr/share/keyrings; \
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
| gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg; \
curl -fsSL https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
| sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
> /etc/apt/sources.list.d/nvidia-container-toolkit.list; \
apt-get update; \
apt-get install -y --no-install-recommends \
nvidia-container-toolkit \
nvidia-container-runtime \
libnvidia-container-tools; \
\
# 把发行版 CNI 插件软链到 k3s 常用路径
mkdir -p /opt/cni/bin; \
for d in /usr/lib/cni /usr/libexec/cni; do \
if [ -d "$d" ]; then \
find "$d" -maxdepth 1 -type f -exec ln -sf {} /opt/cni/bin/ \; ; \
fi; \
done; \
\
# 基础 sanity checks（build 阶段没有 daemon，失败允许）
command -v ctr; \
ctr version || true; \
command -v nvidia-container-runtime; \
nvidia-container-runtime --version || true; \
\
rm -rf /var/lib/apt/lists/*
# 2) 安装 k3s / kubectl / crictl（二进制下载，统一重试逻辑）+ crictl 默认配置
RUN set -eux; \
dl() { \
local url="$1"; \
local out="$2"; \
curl -fL --retry 5 --retry-delay 1 --retry-connrefused \
-o "$out" "${DOWNLOAD_PROXY_PREFIX}${url}"; \
}; \
\
# k3s
dl "https://github.com/k3s-io/k3s/releases/download/${K3S_VERSION}/k3s" /bin/k3s; \
chmod +x /bin/k3s; \
/bin/k3s --version; \
\
# kubectl
dl "https://dl.k8s.io/release/${KUBECTL_VERSION}/bin/linux/amd64/kubectl" /bin/kubectl; \
chmod +x /bin/kubectl; \
/bin/kubectl version --client=true --output=yaml; \
\
# crictl（避免 Ubuntu 24.04 上 cri-tools 包问题）
dl "https://github.com/kubernetes-sigs/cri-tools/releases/download/${CRICTL_VERSION}/crictl-${CRICTL_VERSION}-linux-amd64.tar.gz" /tmp/crictl.tgz; \
tar -C /usr/local/bin -xzf /tmp/crictl.tgz crictl; \
rm -f /tmp/crictl.tgz; \
command -v crictl; \
/usr/local/bin/crictl --version; \
\
# crictl endpoint 固化（稳定，不依赖 deprecated 自动探测）
mkdir -p /etc; \
cat > /etc/crictl.yaml <<'EOF'
runtime-endpoint: unix:///run/k3s/containerd/containerd.sock
image-endpoint: unix:///run/k3s/containerd/containerd.sock
timeout: 10
debug: false
EOF
RUN set -eux; \
cat > /usr/local/bin/ctr <<'EOF'
#!/usr/bin/env bash
set -euo pipefail
REAL_CTR="/usr/bin/ctr"
K3S_SOCK="/run/k3s/containerd/containerd.sock"
DEFAULT_NS="k8s.io"
has_addr=0
has_ns=0
for ((i=1; i<=$#; i++)); do
arg="${!i}"
case "$arg" in
-a|--address)
has_addr=1
;;
-n|--namespace)
has_ns=1
;;
--address=* )
has_addr=1
;;
--namespace=* )
has_ns=1
;;
esac
done
args=()
# 默认指向 k3s 内嵌 containerd（除非用户自己指定了 -a/--address）
if [[ $has_addr -eq 0 && -S "$K3S_SOCK" ]]; then
args+=(-a "$K3S_SOCK")
fi
# 默认 namespace = k8s.io（除非用户自己指定了 -n/--namespace）
if [[ $has_ns -eq 0 ]]; then
args+=(-n "$DEFAULT_NS")
fi
exec "$REAL_CTR" "${args[@]}" "$@"
EOF
RUN chmod +x /usr/local/bin/ctr; \
chmod 0644 /etc/crictl.yaml
# 3) 写 entrypoint（运行时创建 /run 下的兼容软链接）
RUN set -eux; \
cat > /usr/local/bin/entrypoint.sh <<'ENTRYPOINT_EOF'
#!/usr/bin/env bash
set -euo pipefail
# ---- runtime fixes for tooling ----
# /run 是运行时目录；这里创建兼容路径和软链接，方便 ctr/nerdctl 默认地址使用
mkdir -p /run/containerd /run/k3s/containerd 2>/dev/null || true
ln -sf /run/k3s/containerd/containerd.sock /run/containerd/containerd.sock || true
# -----------------------------------
# 无参数：默认跑 k3s server
if [[ $# -eq 0 ]]; then
exec /bin/k3s server --disable=traefik --disable=servicelb
fi
case "$1" in
server|agent)
exec /bin/k3s "$@"
;;
k3s)
shift
exec /bin/k3s "$@"
;;
kubectl)
shift
exec /bin/kubectl "$@"
;;
ctr|crictl)
exec "$@"
;;
--help|-h)
exec /bin/k3s --help
;;
*)
# 调试入口：bash / sh / nvidia-smi / cat ...
exec "$@"
;;
esac
ENTRYPOINT_EOF
RUN chmod +x /usr/local/bin/entrypoint.sh
ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
CMD ["server", "--disable=traefik", "--disable=servicelb"]
DOCKERFILE_EOF
# 构建与推送（建议带 --pull，确保基底镜像更新）
docker build --pull -t ikingye/k3s-gpu:v1.35.1-k3s1-cuda12.8.1 .
docker push ikingye/k3s-gpu:v1.35.1-k3s1-cuda12.8.1
# 依赖
sudo apt-get update
sudo apt-get install -y curl ca-certificates gnupg
# 添加仓库 key
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
| sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
# 添加 repo 列表
curl -fsSL https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
| sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
| sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list > /dev/null
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker
# 验证 GPU 容器
docker run --rm --gpus all nvidia/cuda:12.8.1-base-ubuntu24.04 nvidia-smi
docker run --rm --gpus all ikingye/k3s-gpu:v1.35.1-k3s1-cuda13.1.0 nvidia-smi
docker run --rm --gpus all rancher/k3s:v1.35.1-k3s1 nvidia-smi
docker run --rm --gpus all ikingye/k3s-gpu:v1.35.1-k3s1-cuda12.8.1 nvidia-smi
docker exec -it k3d-cluster-1-agent-0 ctr -n k8s.io images ls
docker exec -it k3d-cluster-1-agent-0 crictl images
# 先在宿主机 pull 下来
docker pull lmsysorg/sglang:v0.5.9-cu129-amd64
docker pull envoyproxy/gateway-helm:v0.0.0-latest
docker pull envoyproxy/ai-gateway-crds-helm:v0.0.0-latest
docker pull envoyproxy/ai-gateway-helm:v0.0.0-latest
# 导入到整个集群（server+agents）
k3d image import -c cluster-1 lmsysorg/sglang:v0.5.9-cu129-amd64
# 只导入到指定节点（可多次 --nodes）
k3d image import -c cluster-1 --nodes k3d-cluster-1-agent-0 lmsysorg/sglang:v0.5.9-cu129-amd64
# 导入多个镜像
k3d image import -c cluster-1 lmsysorg/sglang:v0.5.9-cu129-amd64 envoyproxy/gateway-helm:v0.0.0-latest envoyproxy/ai-gateway-crds-helm:v0.0.0-latest envoyproxy/ai-gateway-helm:v0.0.0-latest
k3d image import -c cluster-3 ccr-241y349u-pub.cnc.bj.baidubce.com/ecs-public/sglang:4090-0.5.8-cu126
cat << 'CREATE_EOF' > create_k3s.sh
#!/usr/bin/env bash
set -euo pipefail
usage() {
cat <<'USAGE'
Usage:
bash create_k3s.sh <start> <end> [options]
bash create_k3s.sh --range A:B [options]
bash create_k3s.sh --start A --end B [options]
Options:
--start N Start cluster index (e.g. 1)
--end N End cluster index (e.g. 4)
--range A:B Shortcut for --start A --end B
--image IMAGE k3s image
--servers N servers count (default: 1)
--agents N agents count (default: 2)
--hostport-base N kubeAPI hostPort = base + i (default: 8520)
--state-root PATH per-node k3s state root on host (default: /mnt/data1/k3d-data)
--data HOST:CONTAINER bind mount into ALL nodes; repeatable
e.g. --data=/mnt/data1:/mnt/data1 --data=/mnt/data2:/mnt/data2
--tls-san IP repeatable, applied to servers (default: 124.237.232.51 + 172.16.16.63)
--device-plugin-url URL nvidia device plugin manifest URL
--no-preflight skip docker run nvidia-smi preflight
-h|--help show help
Examples:
bash create_k3s.sh 1 4 --state-root /mnt/data1/k3d-data \
--data=/mnt/data1:/mnt/data1 --data=/mnt/data2:/mnt/data2
bash create_k3s.sh --range 5:5 --agents 3 --servers 1 \
--state-root /mnt/nvme/k3d-data \
--data=/mnt/nvme:/mnt/nvme
USAGE
}
is_int() { [[ "${1:-}" =~ ^[0-9]+$ ]]; }
# ---------------- defaults ----------------
start=""
end=""
IMAGE="${IMAGE:-ikingye/k3s-gpu:v1.35.1-k3s1-cuda12.6.3}"
SERVERS="${SERVERS:-1}"
AGENTS="${AGENTS:-2}"
HOSTPORT_BASE="${HOSTPORT_BASE:-8520}"
STATE_ROOT="${STATE_ROOT:-/mnt/data1/k3d-data}"
DEVICE_PLUGIN_URL="${DEVICE_PLUGIN_URL:-https://raw.githubusercontent.com/NVIDIA/k8s-device-plugin/v0.18.2/deployments/static/nvidia-device-plugin.yml}"
# repeatable args
DATA_MOUNTS=() # host:container
TLS_SANS=() # IPs
NO_PREFLIGHT=0
# default TLS sans (if user doesn't pass any --tls-san)
TLS_SANS_DEFAULT=("124.237.232.51" "172.16.16.63")
# ---------------- arg parsing ----------------
positional=()
while [[ $# -gt 0 ]]; do
case "$1" in
--start)
start="${2:-}"; shift 2;;
--end)
end="${2:-}"; shift 2;;
--range)
r="${2:-}"; shift 2
start="${r%%:*}"
end="${r##*:}"
;;
--range=*)
r="${1#*=}"; shift
start="${r%%:*}"
end="${r##*:}"
;;
--image)
IMAGE="${2:-}"; shift 2;;
--image=*)
IMAGE="${1#*=}"; shift;;
--servers)
SERVERS="${2:-}"; shift 2;;
--servers=*)
SERVERS="${1#*=}"; shift;;
--agents)
AGENTS="${2:-}"; shift 2;;
--agents=*)
AGENTS="${1#*=}"; shift;;
--hostport-base)
HOSTPORT_BASE="${2:-}"; shift 2;;
--hostport-base=*)
HOSTPORT_BASE="${1#*=}"; shift;;
--state-root)
STATE_ROOT="${2:-}"; shift 2;;
--state-root=*)
STATE_ROOT="${1#*=}"; shift;;
--data)
DATA_MOUNTS+=("${2:-}"); shift 2;;
--data=*)
DATA_MOUNTS+=("${1#*=}"); shift;;
--tls-san)
TLS_SANS+=("${2:-}"); shift 2;;
--tls-san=*)
TLS_SANS+=("${1#*=}"); shift;;
--device-plugin-url)
DEVICE_PLUGIN_URL="${2:-}"; shift 2;;
--device-plugin-url=*)
DEVICE_PLUGIN_URL="${1#*=}"; shift;;
--no-preflight)
NO_PREFLIGHT=1; shift;;
-h|--help)
usage; exit 0;;
--)
shift; break;;
-*)
echo "Unknown option: $1" >&2
usage; exit 1;;
*)
positional+=("$1"); shift;;
esac
done
# positional start/end fallback
if [[ -z "${start}" && ${#positional[@]} -ge 1 ]]; then start="${positional[0]}"; fi
if [[ -z "${end}" && ${#positional[@]} -ge 2 ]]; then end="${positional[1]}"; fi
# validations
if [[ -z "${start}" || -z "${end}" ]]; then
echo "ERROR: start/end required." >&2
usage; exit 1
fi
if ! is_int "${start}" || ! is_int "${end}" || ! is_int "${SERVERS}" || ! is_int "${AGENTS}" || ! is_int "${HOSTPORT_BASE}"; then
echo "ERROR: start/end/servers/agents/hostport-base must be integers." >&2
exit 1
fi
if (( start > end )); then
echo "ERROR: start(${start}) > end(${end})." >&2
exit 1
fi
if (( SERVERS < 1 || AGENTS < 0 )); then
echo "ERROR: servers must be >=1 and agents must be >=0." >&2
exit 1
fi
# default TLS sans if none provided
if [[ ${#TLS_SANS[@]} -eq 0 ]]; then
TLS_SANS=("${TLS_SANS_DEFAULT[@]}")
fi
preflight() {
if (( NO_PREFLIGHT == 1 )); then
echo "==> Preflight skipped (--no-preflight)"
return 0
fi
echo "==> Preflight GPU: docker run nvidia-smi"
docker run --rm --gpus all "${IMAGE}" nvidia-smi >/dev/null
}
gen_k3d_config() {
local i="$1"
local cfg="k3d-config-cluster-${i}.yaml"
local hostPort="$((HOSTPORT_BASE + i))"
cat > "${cfg}" <<EOF
apiVersion: k3d.io/v1alpha5
kind: Simple
metadata:
name: cluster-${i}
image: ${IMAGE}
servers: ${SERVERS}
agents: ${AGENTS}
kubeAPI:
host: "127.0.0.1"
hostIP: "0.0.0.0"
hostPort: "${hostPort}"
# 关键：把每个节点的 /var/lib/rancher/k3s 单独挂到 state-root
volumes:
EOF
# per-server state
for ((s=0; s<SERVERS; s++)); do
cat >> "${cfg}" <<EOF
- volume: ${STATE_ROOT}/cluster-${i}/server-${s}:/var/lib/rancher/k3s
nodeFilters:
- server:${s}
EOF
done
# per-agent state
for ((a=0; a<AGENTS; a++)); do
cat >> "${cfg}" <<EOF
- volume: ${STATE_ROOT}/cluster-${i}/agent-${a}:/var/lib/rancher/k3s
nodeFilters:
- agent:${a}
EOF
done
# shared mounts from --data
for m in "${DATA_MOUNTS[@]}"; do
cat >> "${cfg}" <<EOF
- volume: ${m}
nodeFilters:
- server:*
- agent:*
EOF
done
cat >> "${cfg}" <<'EOF'
options:
runtime:
gpuRequest: all
k3s:
extraArgs:
# 避免每个 Pod 都写 runtimeClassName
- arg: "--default-runtime=nvidia"
nodeFilters:
- agent:*
- arg: "--node-taint=node-role.kubernetes.io/control-plane=true:NoSchedule"
nodeFilters:
- server:*
- arg: "--disable=traefik"
nodeFilters:
- server:*
- arg: "--disable=servicelb"
nodeFilters:
- server:*
- arg: "--kubelet-arg=image-gc-high-threshold=99"
nodeFilters:
- server:*
- agent:*
- arg: "--kubelet-arg=image-gc-low-threshold=95"
nodeFilters:
- server:*
- agent:*
- arg: "--kubelet-arg=eviction-hard=imagefs.available<1%,nodefs.available<1%"
nodeFilters:
- server:*
- agent:*
EOF
# tls sans (repeatable)
for ip in "${TLS_SANS[@]}"; do
cat >> "${cfg}" <<EOF
- arg: --tls-san=${ip}
nodeFilters:
- server:*
EOF
done
cat >> "${cfg}" <<'EOF'
kubeconfig:
updateDefaultKubeconfig: true
switchCurrentContext: true
registries:
config: |
mirrors:
"docker.io":
endpoint:
- "https://hub.kingye.me"
"ghcr.io":
endpoint:
- "https://ghcr.kingye.me"
"gcr.io":
endpoint:
- "https://gcr.kingye.me"
"k8s.gcr.io":
endpoint:
- "https://k8sgcr.kingye.me"
"registry.k8s.io":
endpoint:
- "https://k8s.kingye.me"
"quay.io":
endpoint:
- "https://quay.kingye.me"
"mcr.microsoft.com":
endpoint:
- "https://mcr.kingye.me"
"docker.elastic.co":
endpoint:
- "https://elastic.kingye.me"
"nvcr.io":
endpoint:
- "https://nvcr.kingye.me"
EOF
}
ensure_dirs() {
local i="$1"
local base="${STATE_ROOT}/cluster-${i}"
mkdir -p "${base}"
for ((s=0; s<SERVERS; s++)); do
mkdir -p "${base}/server-${s}"
done
for ((a=0; a<AGENTS; a++)); do
mkdir -p "${base}/agent-${a}"
done
chmod 755 "${base}" || true
for p in "${base}"/*; do
[[ -e "$p" ]] && chmod 755 "$p" || true
done
}
wipe_state() {
local i="$1"
local base="${STATE_ROOT}/cluster-${i}"
for ((s=0; s<SERVERS; s++)); do
[[ -d "${base}/server-${s}" ]] && find "${base}/server-${s}" -mindepth 1 -maxdepth 1 -exec rm -rf {} + || true
done
for ((a=0; a<AGENTS; a++)); do
[[ -d "${base}/agent-${a}" ]] && find "${base}/agent-${a}" -mindepth 1 -maxdepth 1 -exec rm -rf {} + || true
done
}
install_device_plugin() {
kubectl apply -f "${DEVICE_PLUGIN_URL}"
# 幂等 patch：runtimeClassName + nodeSelector
kubectl patch ds -n kube-system nvidia-device-plugin-daemonset --type='merge' -p '{
"spec": {
"template": {
"spec": {
"runtimeClassName": "nvidia",
"nodeSelector": { "accelerator": "nvidia" }
}
}
}
}' || true
kubectl set env -n kube-system ds/nvidia-device-plugin-daemonset FAIL_ON_INIT_ERROR=false
kubectl rollout status -n kube-system ds/nvidia-device-plugin-daemonset --timeout=180s
kubectl get pods -n kube-system -l name=nvidia-device-plugin-ds -o wide || true
}
create_cluster() {
local i="$1"
echo
echo "=============================="
echo "==> cluster-${i} (servers=${SERVERS}, agents=${AGENTS})"
echo " state-root=${STATE_ROOT}"
echo " data-mounts=${#DATA_MOUNTS[@]}"
echo "=============================="
gen_k3d_config "${i}"
ensure_dirs "${i}"
k3d cluster delete "cluster-${i}" || true
wipe_state "${i}"
docker network rm "k3d-cluster-${i}" 2>/dev/null || true
k3d cluster create --config "k3d-config-cluster-${i}.yaml" --verbose
kubectl config use-context "k3d-cluster-${i}"
kubectl get nodes -o wide
kubectl get runtimeclass || true
# 给所有 agent 打标签
for ((a=0; a<AGENTS; a++)); do
kubectl label node "k3d-cluster-${i}-agent-${a}" accelerator=nvidia --overwrite
done
install_device_plugin
kubectl get nodes -o jsonpath='{range .items[*]}{.metadata.name}{"\tallocatable="}{.status.allocatable.nvidia\.com/gpu}{"\tcapacity="}{.status.capacity.nvidia\.com/gpu}{"\n"}{end}' || true
}
main() {
preflight
for ((i=start; i<=end; i++)); do
create_cluster "${i}"
done
}
main "$@"
CREATE_EOF
bash create_k3s.sh
bash create_k3s.sh --range 5:5 --servers 1 --agents 2 \
--state-root /home/k3d-data --data=/home:/home \
--tls-san 1.180.13.251 --tls-san 1.180.13.251 172.16.48.74
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