# 控制节点硬件要求
– 处理器：至少4核CPU
– 内存：至少8GB RAM
– 存储：至少100GB SSD

# 工作节点硬件要求
– 处理器：至少2核CPU
– 内存：至少4GB RAM
– 存储：至少50GB SSD

# 大规模集群（100+节点）
– 控制节点：8核CPU，16GB RAM，200GB SSD
– 工作节点：4核CPU，8GB RAM，100GB SSD

# 步骤1：安装Linux系统
# 以RHEL 9为例

# 步骤2：安装Docker
$ yum install -y docker
$ systemctl enable –now docker

# 步骤3：安装Kubernetes组件
$ cat < /etc/yum.repos.d/kubernetes.repo
[kubernetes]
name=Kubernetes
baseurl=https://packages.cloud.google.com/yum/repos/kubernetes-el7-x86_64
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://packages.cloud.google.com/yum/doc/yum-key.gpg https://packages.cloud.google.com/yum/doc/rpm-package-key.gpg
EOF

$ yum install -y kubelet kubeadm kubectl
$ systemctl enable –now kubelet

# 步骤4：初始化Kubernetes集群
$ kubeadm init –pod-network-cidr=10.244.0.0/16

# 配置kubectl
$ mkdir -p $HOME/.kube
$ sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
$ sudo chown $(id -u):$(id -g) $HOME/.kube/config

# 安装网络插件
$ kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml

# 加入工作节点
$ kubeadm join 192.168.1.10:6443 –token abcdef.1234567890abcdef \
–discovery-token-ca-cert-hash sha256:1234567890abcdef1234567890abcdef1234567890abcdef1234567890abcdef

# 步骤1：构建Docker镜像
$ cat Dockerfile
FROM python:3.9
WORKDIR /app
COPY requirements.txt .
RUN pip install –no-cache-dir -r requirements.txt
COPY . .
EXPOSE 8000
CMD [“python”, “app.py”]

# 构建镜像
$ docker build -t fgedu/webapp:v1 .

# 步骤2：推送镜像到仓库
$ docker tag fgedu/webapp:v1 registry.fgedu.net.cn/fgedu/webapp:v1
$ docker push registry.fgedu.net.cn/fgedu/webapp:v1

# 步骤3：在Kubernetes中部署应用
$ cat deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: webapp
labels:
app: webapp
spec:
replicas: 3
selector:
matchLabels:
app: webapp
template:
metadata:
labels:
app: webapp
spec:
containers:
– name: webapp
image: registry.fgedu.net.cn/fgedu/webapp:v1
ports:
– containerPort: 8000

—
apiVersion: v1
kind: Service
metadata:
name: webapp-service
spec:
selector:
app: webapp
ports:
– port: 80
targetPort: 8000
type: LoadBalancer

# 应用部署
$ kubectl apply -f deployment.yaml

# 步骤1：配置Jenkins CI/CD流水线
$ cat Jenkinsfile
pipeline {
agent any
stages {
stage(‘Build’) {
steps {
sh ‘docker build -t fgedu/webapp:${BUILD_NUMBER} .’
}
}
stage(‘Test’) {
steps {
sh ‘docker run –rm fgedu/webapp:${BUILD_NUMBER} pytest’
}
}
stage(‘Deploy’) {
steps {
sh ‘docker tag fgedu/webapp:${BUILD_NUMBER} registry.fgedu.net.cn/fgedu/webapp:${BUILD_NUMBER}’
sh ‘docker push registry.fgedu.net.cn/fgedu/webapp:${BUILD_NUMBER}’
sh ‘kubectl set image deployment/webapp webapp=registry.fgedu.net.cn/fgedu/webapp:${BUILD_NUMBER}’
}
}
}
}

# 步骤2：触发流水线
# 通过代码提交或手动触发

# 步骤3：查看部署状态
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
webapp-789012-abcde 1/1 Running 0 5m
webapp-789012-fghij 1/1 Running 0 5m
webapp-789012-klmno 1/1 Running 0 5m

# 部署Prometheus和Grafana
$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm install prometheus prometheus-community/kube-prometheus-stack

# 部署ELK Stack
$ helm repo add elastic https://helm.elastic.co
$ helm install elasticsearch elastic/elasticsearch
$ helm install kibana elastic/kibana
$ helm install filebeat elastic/filebeat

# 查看监控面板
$ kubectl port-forward svc/prometheus-grafana 3000:80

# 查看日志
$ kubectl port-forward svc/kibana-kibana 5601:5601