KubeEdge 边缘计算学习手册

1. KubeEdge 云端部署#

1.1 环境准备#

云端：k8s-allinone 镜像，hostname 为 master
边端：hostname 为 kubeedge-node

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# 云端和边端都配置 /etc/hosts
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172.129.20.14 master
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172.129.20.21 kubeedge-node

1.2 配置 YUM 仓库和 Docker#

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# 云端
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tar -zxvf kubernetes_kubeedge_allinone.tar.gz -C /opt/
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mv /etc/yum.repos.d/* /media/
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cat > /etc/yum.repos.d/local.repo <<EOF
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[docker]
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name=docker
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baseurl=file:///opt/yum
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gpgcheck=0
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enabled=1
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EOF
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# 搭建 FTP 给边端用
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yum -y install vsftpd
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echo "anon_root=/opt" >> /etc/vsftpd/vsftpd.conf
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systemctl enable vsftpd --now

Docker daemon.json（云端和边端相同）：

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{
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  "log-driver": "json-file",
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  "log-opts": { "max-size": "200m", "max-file": "5" },
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  "default-ulimits": {
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    "nofile": { "Name": "nofile", "Hard": 655360, "Soft": 655360 },
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    "nproc": { "Name": "nproc", "Hard": 655360, "Soft": 655360 }
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  },
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  "live-restore": true,
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  "oom-score-adjust": -1000,
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  "max-concurrent-downloads": 10,
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  "max-concurrent-uploads": 10,
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  "insecure-registries": ["0.0.0.0/0"]
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}

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systemctl daemon-reload && systemctl restart docker

1.3 部署 Harbor#

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cd /opt/
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mv docker-compose-Linux-x86_64 /usr/bin/docker-compose
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tar -zxvf harbor-offline-installer-v2.5.0.tgz
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cd harbor && cp harbor.yml.tmpl harbor.yml
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vi harbor.yml  # hostname: 云端IP
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./install.sh
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docker login -u admin -p Harbor12345 master
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# 创建 k8s 命名空间（公开）
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cd /opt/k8simage/ && sh load.sh && sh push.sh

1.4 配置 Pod 亲和性#

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# 修改 flannel，排除边端节点
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kubectl edit daemonset -n kube-system kube-flannel-ds
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# 在 containers 前添加 nodeAffinity，排除 node-role.kubernetes.io/edge
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# 修改 kube-proxy，同上
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kubectl edit daemonset -n kube-system kube-proxy

1.5 初始化云端#

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cd /opt/kubeedge/
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mv keadm /usr/bin/
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mkdir /etc/kubeedge
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tar -zxf kubeedge-1.11.1.tar.gz
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cp -rf kubeedge-1.11.1/build/tools/* /etc/kubeedge/
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cp -rf kubeedge-1.11.1/build/crds/ /etc/kubeedge/
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tar -zxf kubeedge-v1.11.1-linux-amd64.tar.gz
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cp -rf * /etc/kubeedge/
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# 初始化（advertise-address 为 master IP）
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keadm deprecated init --kubeedge-version=1.11.1 --advertise-address=172.129.20.14
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netstat -ntpl | grep cloudcore
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# tcp6 :::10000 LISTEN cloudcore
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# tcp6 :::10002 LISTEN cloudcore

2. KubeEdge 边端部署#

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# 从云端复制工具和配置
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scp /usr/bin/keadm root@kubeedge-node:/usr/local/bin/
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scp -r /etc/kubeedge/* root@kubeedge-node:/etc/kubeedge/
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# 获取 token
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keadm gettoken
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# 边端加入集群
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keadm deprecated join --cloudcore-ipport=172.129.20.14:10000 \
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  --kubeedge-version=1.11.1 --token=<token值>
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# 遇到 yum 报错时
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rm -rf /etc/yum.repos.d/epel*
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systemctl status edgecore
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# 云端验证
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kubectl get nodes

3. 云端监控服务配置#

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export CLOUDCOREIPS="172.129.20.14"
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cd /etc/kubeedge/
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./certgen.sh stream
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# 修改 cloudcore.yaml
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vi /etc/kubeedge/config/cloudcore.yaml
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# cloudStream.enable: true
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# cloudStream.streamPort: 10003
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# router.enable: true
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# router.port: 9443
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# 修改边端 edgecore.yaml
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vi /etc/kubeedge/config/edgecore.yaml
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# edgeStream.enable: true
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# serviceBus.enable: true
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# 重启云端
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kill -9 $(netstat -lntup | grep cloudcore | awk 'NR==1 {print $7}' | cut -d '/' -f 1)
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cp -rfv cloudcore.service /usr/lib/systemd/system/
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systemctl start cloudcore.service
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netstat -lntup | grep 10003
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# 重启边端
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systemctl restart edgecore.service
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# 验证
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kubectl top nodes

4. 云端 Python 环境搭建#

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tar -zxvf gcc-repo.tar.gz
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cat > /etc/yum.repos.d/gcc.repo <<EOF
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[gcc]
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name=gcc
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baseurl=file:///root/gcc-repo
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gpgcheck=0
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enabled=1
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EOF
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yum -y install zlib-devel bzip2-devel openssl-devel ncurses-devel sqlite-devel \
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  readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel libffi-devel gcc
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tar -zxvf volume_packages.tar.gz
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tar -zxvf Python-3.7.3.tar.gz
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mkdir /usr/local/python3
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cd Python-3.7.3/
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./configure --prefix=/usr/local/python3
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make && make install
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yes | mv volume_packages/site-packages/* /usr/local/python3/lib/python3.7/site-packages/
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ln -s /usr/local/python3/bin/python3.7 /usr/bin/python3
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ln -s /usr/local/python3/bin/pip3.7 /usr/bin/pip3
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pip3 list

5. 边端 MongoDB 数据库#

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tar -zxvf mongoRepo.tar.gz -C /opt/
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cat > /etc/yum.repos.d/mongo.repo <<EOF
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[mongo]
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name=mongo
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enabled=1
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gpgcheck=0
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baseurl=file:///opt/mongoRepo
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EOF
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yum -y install mongodb*
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# 修改绑定地址
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vi /etc/mongod.conf
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# bindIp: 0.0.0.0
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systemctl restart mongod && systemctl enable mongod
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netstat -lntup | grep 27017
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# 创建数据库
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mongo
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> use edgesql
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> db.createCollection("users")
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> db.createCollection("ai_data")
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> db.createCollection("ai_model")
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> show collections

6. 边端 Nginx 前端部署#

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yum install -y nginx
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rm -rf /usr/share/nginx/html/*
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mv ydy_cloudapp_front_dist/index.html /usr/share/nginx/html/
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mv ydy_cloudapp_front_dist/static/ /usr/share/nginx/html/

Nginx 反向代理配置：

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server {
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    listen 80;
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    server_name localhost;
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    root /usr/share/nginx/html;
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    location ~ ^/cloudedge/(.*) {
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        proxy_pass http://masterIP:30850/cloudedge/$1;
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        proxy_set_header Host $host;
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        proxy_set_header X-Real-IP $remote_addr;
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        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
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        add_header 'Access-Control-Allow-Origin' '*';
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        add_header 'Access-Control-Allow-Methods' 'GET, POST, OPTIONS';
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        add_header 'Access-Control-Allow-Headers' 'Authorization, Content-Type';
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        add_header 'Access-Control-Allow-Credentials' 'true';
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    }
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}

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nginx -t
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systemctl restart nginx && systemctl enable nginx

7. 云端 FastAPI 微服务#

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# 用户服务（端口 8046）
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cd /root/ydy_cloudapp_backend_framework/fastapi_user/
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python3 main.py &
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# 修改 manager_user.py 中 MongoDBUrl 为边端 IP
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# 云服务（端口 8070）
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cd /root/ydy_cloudapp_backend_framework/fastapi_cloud/
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python3 main.py &
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# 边缘管理服务（端口 8045）
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cd /root/ydy_cloudapp_backend_framework/fastapi_cloud_edge/
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python3 main.py &
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# AI PCB 检测服务（端口 8055）
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cd /root/ydy_cloudapp_backend_framework/fastapi_ai_pcb/
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vi pcb_detect_service.py  # 注释 from pcb_detect import detect_image
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python3 main.py &
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# 网关服务（端口 30850）
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cd /root/ydy_cloudapp_backend_framework/fastapi_gateway/fastapi_gateway_service/
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python3 main.py &

访问地址：

用户服务：http://云端IP:8046/docs
云服务：http://云端IP:8070/docs
边缘管理：http://云端IP:8045/docs
AI 服务：http://云端IP:8055/docs
网关服务：http://云端IP:30850/docs

Windows HOSTS 映射：

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172.129.20.14 localedge

最终访问：http://边端IP/index.html（test/123456）

8. 竞赛真题精选#

8.1 云端部署 KubeEdge cloudcore#

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keadm deprecated init --kubeedge-version=1.11.1 --advertise-address=172.129.20.16
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netstat -lntup | grep cloudcore

8.2 边端加入集群#

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keadm gettoken
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keadm deprecated join --cloudcore-ipport=172.129.20.33:10000 \
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  --kubeedge-version=1.11.1 --token=<token>

8.3 边缘应用部署#

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# 安装 jq、Mariadb（密码 123456）
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# 构建前后端镜像和 AI 镜像
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# 编写 platform_deployment.yaml 部署到 ec-dashboard 命名空间
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# 暴露端口 30080
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# 通过平台部署 AI 应用（名称 analyzer）