## 金融行业
– 挑战：安全合规要求高、交易延迟低、系统可靠性要求高
– 解决方案：使用高可用Kubernetes集群、实施严格的安全措施、优化网络性能

## 医疗行业
– 挑战：数据隐私保护、系统可靠性、合规要求
– 解决方案：使用加密存储、实施访问控制、定期备份数据

## 零售行业
– 挑战：流量波动大、季节性需求、实时数据分析
– 解决方案：使用自动扩缩容、实施缓存策略、实时监控系统

## 制造业
– 挑战：边缘计算需求、设备连接、实时数据处理
– 解决方案：使用Kubernetes边缘集群、实施IoT集成、实时数据处理

## 教育行业
– 挑战：资源有限、多校区部署、安全性要求
– 解决方案：使用混合云架构、实施资源配额、集中管理

## 政府行业
– 挑战：安全合规要求高、数据主权、系统可靠性
– 解决方案：使用私有云部署、实施严格的安全措施、定期审计

## 媒体行业
– 挑战：高带宽需求、内容分发、实时转码
– 解决方案：使用CDN集成、实施缓存策略、优化存储

## 电商行业
– 挑战：高并发、大流量、订单处理
– 解决方案：使用自动扩缩容、实施负载均衡、优化数据库

## 电信行业
– 挑战：网络可靠性、服务质量、多租户管理
– 解决方案：使用高可用集群、实施网络策略、多租户隔离

## 能源行业
– 挑战：远程设备管理、实时监控、数据安全
– 解决方案：使用边缘计算、实施实时监控、数据加密

## 交通行业
– 挑战：实时数据处理、设备连接、系统可靠性
– 解决方案：使用边缘计算、实时数据处理、高可用架构

## 物流行业
– 挑战：实时追踪、供应链管理、系统集成
– 解决方案：使用微服务架构、实时数据处理、系统集成

## 架构设计
– 高可用集群：部署多控制平面节点和etcd节点
– 网络设计：使用高性能网络，确保低延迟
– 存储设计：使用高可靠存储，确保数据安全
– 安全设计：实施多层次安全措施

## 安全措施
– 网络隔离：使用网络策略限制Pod间通信
– 访问控制：实施RBAC，严格控制权限
– 加密：对数据传输和存储进行加密
– 审计：实施全面的审计日志
– 合规：满足PCI DSS等合规要求

## 性能优化
– 网络优化：使用高性能网络插件，配置合适的网络参数
– 存储优化：使用高速存储，配置合适的存储参数
– 资源配置：根据应用需求配置合适的资源请求和限制
– 调度优化：使用节点亲和性和Pod亲和性，优化Pod调度

## 监控与告警
– 实时监控：部署Prometheus和Grafana，实时监控系统状态
– 告警策略：配置合理的告警策略，及时发现和解决问题
– 日志管理：使用ELK Stack，集中管理日志
– 追踪：使用Jaeger等工具，追踪请求链路

## 灾备策略
– 跨区域部署：在多个区域部署集群，实现灾备
– 数据备份：定期备份etcd数据和应用数据
– 故障转移：配置自动故障转移机制
– 演练：定期进行灾备演练，确保灾备方案有效

## 架构设计
– 高可用集群：确保系统的可靠性
– 网络设计：确保网络的安全性和稳定性
– 存储设计：使用高可靠存储，确保数据安全
– 合规设计：满足HIPAA等合规要求

## 数据隐私保护
– 数据加密：对敏感数据进行加密存储和传输
– 访问控制：实施严格的访问控制，确保只有授权用户可以访问数据
– 审计日志：记录所有数据访问操作，便于审计
– 数据脱敏：对敏感数据进行脱敏处理

## 应用部署
– 微服务架构：将应用拆分为微服务，提高系统的可维护性和可扩展性
– 容器化：将应用容器化，确保环境一致性
– 自动化部署：使用CI/CD工具，实现自动化部署
– 版本管理：实施严格的版本管理，确保应用的可追溯性

## 监控与告警
– 系统监控：监控集群和应用的运行状态
– 安全监控：监控系统的安全状态，及时发现安全威胁
– 合规监控：监控系统的合规状态，确保符合合规要求
– 告警策略：配置合理的告警策略，及时发现和解决问题

## 灾备策略
– 数据备份：定期备份医疗数据，确保数据安全
– 灾备部署：在不同地点部署灾备系统
– 故障转移：配置自动故障转移机制
– 演练：定期进行灾备演练，确保灾备方案有效

## 架构设计
– 弹性集群：根据流量自动调整集群规模
– 微服务架构：将应用拆分为微服务，提高系统的可维护性和可扩展性
– 边缘计算：在门店部署边缘节点，提高响应速度
– 混合云架构：结合私有云和公有云，提高系统的弹性

## 流量处理
– 自动扩缩容：根据流量自动调整应用实例数量
– 负载均衡：使用负载均衡器分发流量
– 缓存策略：实施缓存策略，提高响应速度
– CDN集成：使用CDN加速静态资源分发

## 数据处理
– 实时数据分析：使用流处理技术，实时分析销售数据
– 数据集成：集成各种数据源，提供全面的数据视图
– 数据存储：使用适合的存储方案，满足不同类型数据的存储需求
– 数据安全：确保数据的安全性和隐私性

## 监控与告警
– 实时监控：监控系统的运行状态和性能
– 业务监控：监控业务指标，如销售额、订单量等
– 告警策略：配置合理的告警策略，及时发现和解决问题
– 分析工具：使用分析工具，分析系统性能和业务数据

## 灾备策略
– 数据备份：定期备份业务数据，确保数据安全
– 灾备部署：在不同地点部署灾备系统
– 故障转移：配置自动故障转移机制
– 演练：定期进行灾备演练，确保灾备方案有效

## 1. 边缘集群部署
# 部署边缘节点
$ kubectl label nodes edge-node1 node-role.kubernetes.io/edge=

# 配置边缘节点污点
$ kubectl taint nodes edge-node1 node-role.kubernetes.io/edge:NoSchedule

# 部署边缘应用
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: edge-app namespace: default spec: replicas: 1 selector: matchLabels: app: edge-app template: metadata: labels: app: edge-app spec: containers: - name: edge-app image: fgedu/edge-app:v1 resources: requests: cpu: "100m" memory: "256Mi" limits: cpu: "500m" memory: "512Mi" ports: - containerPort: 8080 nodeSelector: node-role.kubernetes.io/edge: "" tolerations: - key: "node-role.kubernetes.io/edge" operator: "Exists" effect: "NoSchedule" EOF ## 2. IoT集成 # 部署MQTT broker $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: mosquitto namespace: default spec: replicas: 1 selector: matchLabels: app: mosquitto template: metadata: labels: app: mosquitto spec: containers: - name: mosquitto image: eclipse-mosquitto:latest resources: requests: cpu: "100m" memory: "256Mi" limits: cpu: "500m" memory: "512Mi" ports: - containerPort: 1883 volumeMounts: - name: mosquitto-config mountPath: /mosquitto/config volumes: - name: mosquitto-config configMap: name: mosquitto-config EOF # 创建ConfigMap $ kubectl create configmap mosquitto-config --from-file=mosquitto.conf ## 3. 实时数据处理 # 部署Kafka $ helm repo add bitnami https://charts.bitnami.com/bitnami $ helm install kafka bitnami/kafka --namespace default # 部署Spark $ helm repo add spark-operator https://googlecloudplatform.github.io/spark-on-k8s-operator $ helm install spark-operator spark-operator/spark-operator --namespace default # 部署数据处理应用 $ kubectl apply -f - << EOF apiVersion: sparkoperator.k8s.io/v1beta2 kind: SparkApplication metadata: name: data-processing namespace: default spec: type: Java mode: cluster image: fgedu/spark-app:v1 mainClass: com.fgedu.data.ProcessingApp mainApplicationFile: local:///opt/spark/app.jar sparkVersion: 3.2.0 restartPolicy: type: Never driver: cores: 1 memory: 1g executor: cores: 2 instances: 2 memory: 2g EOF ## 4. 监控与告警 # 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 --namespace monitoring # 部署Node Exporter $ kubectl apply -f https://raw.githubusercontent.com/prometheus/node_exporter/master/examples/kubernetes/node-exporter-daemonset.yaml # 配置告警规则 $ kubectl apply -f - << EOF apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: manufacturing-alerts namespace: monitoring spec: groups: - name: manufacturing rules: - alert: HighTemperature expr: temperature > 80
for: 5m
labels:
severity: warning
annotations:
summary: “高温警报”
description: “设备温度超过80度”
– alert: LowPressure
expr: pressure < 10 for: 5m labels: severity: warning annotations: summary: "低压警报" description: "设备压力低于10" EOF

## 1. 混合云架构部署
# 私有云集群部署
$ sudo kubeadm init –control-plane-endpoint “192.168.1.100:6443” –pod-network-cidr=10.244.0.0/16

# 公有云集群部署（以AWS EKS为例）
$ aws eks create-cluster –name fgedu-eks-cluster –role-arn arn:aws:iam::123456789012:role/eks-cluster-role –resources-vpc-config subnetIds=subnet-12345678,subnet-87654321,securityGroupIds=sg-12345678

# 配置集群联邦
$ kubefedctl init fed –host-cluster-context=private-cloud –addons-repo=https://github.com/kubernetes-sigs/kubefed/tree/master/addons
$ kubefedctl join private-cloud –cluster-context=private-cloud –host-cluster-context=private-cloud
$ kubefedctl join public-cloud –cluster-context=public-cloud –host-cluster-context=private-cloud

## 2. 多校区部署
# 创建校区命名空间
$ kubectl create namespace campus1
$ kubectl create namespace campus2
$ kubectl create namespace campus3

# 配置校区资源配额
$ kubectl apply -f – << EOF apiVersion: v1 kind: ResourceQuota metadata: name: campus1-quota namespace: campus1 spec: hard: requests.cpu: "2" requests.memory: "4Gi" limits.cpu: "4" limits.memory: "8Gi" pods: "10" services: "5" EOF ## 3. 应用部署 # 部署学习管理系统 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: lms namespace: campus1 spec: replicas: 2 selector: matchLabels: app: lms template: metadata: labels: app: lms spec: containers: - name: lms image: fgedu/lms:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 8080 EOF # 部署视频点播系统 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: vod namespace: campus1 spec: replicas: 1 selector: matchLabels: app: vod template: metadata: labels: app: vod spec: containers: - name: vod image: fgedu/vod:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 volumes: - name: video-storage persistentVolumeClaim: claimName: video-pvc EOF ## 4. 安全配置 # 配置网络策略 $ kubectl apply -f - << EOF apiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: campus1-network-policy namespace: campus1 spec: podSelector: matchLabels: {} policyTypes: - Ingress - Egress ingress: - from: - podSelector: matchLabels: {} egress: - to: - podSelector: matchLabels: {} EOF # 配置RBAC权限 $ kubectl create role campus1-admin --namespace=campus1 --verb=* --resource=* $ kubectl create rolebinding campus1-admin-binding --namespace=campus1 --role=campus1-admin --user=admin

## 1. 私有云部署
# 部署私有云Kubernetes集群
$ sudo kubeadm init –control-plane-endpoint “192.168.1.100:6443” –pod-network-cidr=10.244.0.0/16

# 配置高可用
$ kubeadm join 192.168.1.100:6443 –token abcdef.0123456789abcdef –discovery-token-ca-cert-hash sha256:0123456789abcdef0123456789abcdef0123456789abcdef0123456789abcdef –control-plane

## 2. 安全配置
# 配置网络策略
$ kubectl apply -f – << EOF apiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: government-network-policy namespace: default spec: podSelector: matchLabels: {} policyTypes: - Ingress - Egress ingress: - from: - ipBlock: cidr: 192.168.1.0/24 egress: - to: - ipBlock: cidr: 192.168.1.0/24 EOF # 配置RBAC权限 $ kubectl create clusterrole government-admin --verb=* --resource=* $ kubectl create clusterrolebinding government-admin-binding --clusterrole=government-admin --user=admin # 配置Pod安全策略 $ kubectl apply -f - << EOF apiVersion: policy/v1beta1 kind: PodSecurityPolicy metadata: name: restricted annotations: seccomp.security.alpha.kubernetes.io/allowedProfileNames: '学习交流加群风哥QQ113257174docker/default' apparmor.security.beta.kubernetes.io/allowedProfileNames: 'runtime/default' seccomp.security.alpha.kubernetes.io/defaultProfileName: 'docker/default' apparmor.security.beta.kubernetes.io/defaultProfileName: 'runtime/default' spec: privileged: false allowPrivilegeEscalation: false requiredDropCapabilities: - ALL volumes: - 'configMap' - 'emptyDir' - 'projected' - 'secret' - 'downwardAPI' - 'persistentVolumeClaim' hostNetwork: false hostIPC: false hostPID: false runAsUser: rule: 'MustRunAsNonRoot' seLinux: rule: 'RunAsAny' supplementalGroups: rule: 'MustRunAs' ranges: - min: 1 max: 65535 fsGroup: rule: 'MustRunAs' ranges: - min: 1 max: 65535 readOnlyRootFilesystem: false EOF ## 3. 应用部署 # 部署政务服务系统 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: gov-service namespace: default spec: replicas: 3 selector: matchLabels: app: gov-service template: metadata: labels: app: gov-service spec: containers: - name: gov-service image: fgedu/gov-service:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 8080 securityContext: runAsNonRoot: true runAsUser: 1000 runAsGroup: 1000 EOF # 部署数据管理系统 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: data-management namespace: default spec: replicas: 2 selector: matchLabels: app: data-management template: metadata: labels: app: data-management spec: containers: - name: data-management image: fgedu/data-management:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 securityContext: runAsNonRoot: true runAsUser: 1000 runAsGroup: 1000 EOF ## 4. 监控与审计 # 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 --namespace monitoring # 部署Auditd $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: DaemonSet metadata: name: auditd namespace: kube-system spec: selector: matchLabels: app: auditd template: metadata: labels: app: auditd spec: containers: - name: auditd image: fgedu/auditd:v1 securityContext: privileged: true volumeMounts: - name: audit-log mountPath: /var/log/audit volumes: - name: audit-log hostPath: path: /var/log/audit EOF

# 1. 部署媒体内容管理系统
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: media-cms namespace: default spec: replicas: 3 selector: matchLabels: app: media-cms template: metadata: labels: app: media-cms spec: containers: - name: media-cms image: fgedu/media-cms:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 2. 部署CDN集成 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: cdn-edge namespace: default spec: replicas: 5 selector: matchLabels: app: cdn-edge template: metadata: labels: app: cdn-edge spec: containers: - name: cdn-edge image: fgedu/cdn-edge:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 80 EOF # 3. 部署内容分发服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: content-delivery namespace: default spec: replicas: 2 selector: matchLabels: app: content-delivery template: metadata: labels: app: content-delivery spec: containers: - name: content-delivery image: fgedu/content-delivery:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 4. 部署存储服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: storage-service namespace: default spec: replicas: 2 selector: matchLabels: app: storage-service template: metadata: labels: app: storage-service spec: containers: - name: storage-service image: fgedu/storage-service:v1 resources: requests: cpu: "1" memory: "4Gi" limits: cpu: "2" memory: "8Gi" ports: - containerPort: 8080 volumes: - name: media-storage persistentVolumeClaim: claimName: media-pvc EOF # 5. 配置负载均衡 $ kubectl apply -f - << EOF apiVersion: v1 kind: Service metadata: name: media-service namespace: default spec: selector: app: media-cms ports: - port: 80 targetPort: 8080 type: LoadBalancer EOF # 6. 测试系统 # 访问媒体内容管理系统 $ curl http://media-service.fgedu.net.cn { "status": "ok", "message": "Media CMS is running" } # 上传媒体文件 $ curl -X POST -F "file=@video.mp4" http://media-service.fgedu.net.cn/upload { "status": "ok", "message": "File uploaded successfully", "url": "http://cdn.f更多学习教程公众号风哥教程itpux_comgedu.net.cn/video.mp4" } # 访问CDN加速的媒体文件 $ curl -I http://cdn.fgedu.net.cn/video.mp4 HTTP/1.1 200 OK Content-Type: video/mp4 Content-Length: 104857600 Server: nginx/1.21.0

# 1. 部署前端服务
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: frontend namespace: default spec: replicas: 5 selector: matchLabels: app: frontend template: metadata: labels: app: frontend spec: containers: - name: frontend image: fgedu/frontend:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 80 EOF # 2. 部署API服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: api-service namespace: default spec: replicas: 3 selector: matchLabels: app: api-service template: metadata: labels: app: api-service spec: containers: - name: api-service image: fgedu/api-service:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 3. 部署订单服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: order-service namespace: default spec: replicas: 2 selector: matchLabels: app: order-service template: metadata: labels: app: order-service spec: containers: - name: order-service image: fgedu/order-service:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 4. 部署支付服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: payment-service namespace: default spec: replicas: 2 selector: matchLabels: app: payment-service template: metadata: labels: app: payment-service spec: containers: - name: payment-service image: fgedu/payment-service:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 8080 EOF # 5. 部署数据库服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: StatefulSet metadata: name: mysql namespace: default spec: serviceName: mysql replicas: 3 selector: matchLabels: app: mysql template: metadata: labels: app: mysql spec: containers: - name: mysql image: mysql:8.0 resources: requests: cpu: "1" memory: "4Gi" limits: cpu: "2" memory: "8Gi" ports: - containerPort: 3306 env: - name: MYSQL_ROOT_PASSWORD value: "fgedu123" - name: MYSQL_DATABASE value: "fgedudb" volumeMounts: - name: mysql-data mountPath: /var/lib/mysql volumeClaimTemplates: - metadata: name: mysql-data spec: accessModes: ["ReadWriteOnce"] resources: requests: storage: 50Gi EOF # 6. 配置自动扩缩容 $ kubectl autoscale deployment frontend --cpu-percent=50 --min=5 --max=10 $ kubectl autoscale deployment api-service --cpu-percent=50 --min=3 --max=6 # 7. 测试系统 # 访问电商平台 $ curl http://frontend.fgedu.net.cn

Welcome to E-Commerce Platform

# 模拟高并发访问
$ ab -n 1000 -c 100 http://frontend.fgedu.net.cn/

# 查看自动扩缩容
$ kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
frontend Deployment/frontend 80%/50% 5 10 8 10m
api-service Deployment/api-service 60%/50% 3 6 4 10m

# 1. 部署核心业务系统
$ kubectl apply -f – << EOF apiVersion: apps/v1 kind: Deployment metadata: name: core-service namespace: default spec: replicas: 3 selector: matchLabels: app: core-service template: metadata: labels: app: core-service spec: containers: - name: core-service image: fgedu/core-service:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 2. 部署网络服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: network-service namespace: default spec: replicas: 2 selector: matchLabels: app: network-service template: metadata: labels: app: network-service spec: containers: - name: network-service image: fgedu/network-service:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 3. 部署计费服务 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: billing-service namespace: default spec: replicas: 2 selector: matchLabels: app: billing-service template: metadata: labels: app: billing-service spec: containers: - name: billing-service image: fgedu/billing-service:v1 resources: requests: cpu: "1" memory: "2Gi" limits: cpu: "2" memory: "4Gi" ports: - containerPort: 8080 EOF # 4. 配置多租户管理 # 创建租户命名空间 $ kubectl create namespace tenant1 $ kubectl create namespace tenant2 # 配置租户资源配额 $ kubectl apply -f - << EOF apiVersion: v1 kind: ResourceQuota metadata: name: tenant1-quota namespace: tenant1 spec: hard: requests.cpu: "2" requests.memory: "4Gi" limits.cpu: "4" limits.memory: "8Gi" pods: "10" services: "5" EOF # 配置租户网络策略 $ kubectl apply -f - << EOF apiVersion: networking.k8s.io/v1 kind: NetworkPolicy metadata: name: tenant1-network-policy namespace: tenant1 spec: podSelector: matchLabels: {} policyTypes: - Ingress - Egress ingress: - from: - podSelector: matchLabels: {} egress: - to: - podSelector: matchLabels: {} EOF # 5. 部署租户应用 $ kubectl apply -f - << EOF apiVersion: apps/v1 kind: Deployment metadata: name: tenant1-app namespace: tenant1 spec: replicas: 2 selector: matchLabels: app: tenant1-app template: metadata: labels: app: tenant1-app spec: containers: - name: tenant1-app image: fgedu/tenant-app:v1 resources: requests: cpu: "500m" memory: "1Gi" limits: cpu: "1" memory: "2Gi" ports: - containerPort: 8080 EOF # 6. 配置监控与告警 $ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts $ helm install prometheus prometheus-community/kube-prometheus-stack --namespace monitoring # 7. 测试系统 # 访问核心业务系统 $ curl http://core-service.fgedu.net.cn { "status": "ok", "message": "Core service is running" } # 访问租户应用 $ curl http://tenant1-app.tenant1.fgedu.net.cn { "status": "ok", "message": "Tenant1 app is running" } # 查看多租户隔离 $ kubectl get pods --namespace=tenant1 NAME READY STATUS RESTARTS AGE tenant1-app-6799fc88d8-2q4x2 1/1 Running 0 5m tenant1-app-6799fc88d8-5b678 1/1 Running 0 5m