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noreferrer"},b=e("figure",null,[e("img",{src:r,alt:"kubeedge_arch",tabindex:"0",loading:"lazy"}),e("figcaption",null,"kubeedge_arch")],-1),v={class:"hint-container tip"},m=e("p",{class:"hint-container-title"},"提示",-1),k={href:"https://docs.kubeedge.io/zh/docs/kubeedge/#components",target:"_blank",rel:"noopener noreferrer"},A=e("p",null,"本教程演示如何将边缘节点添加到集群。",-1),f=e("h2",{id:"准备工作",tabindex:"-1"},[e("a",{class:"header-anchor",href:"#准备工作"},[e("span",null,"准备工作")])],-1),_={href:"https://kubesphere.io/zh/docs/v3.3/pluggable-components/kubeedge/",target:"_blank",rel:"noopener noreferrer"},x=e("li",null,"为了避免兼容性问题，建议安装 v1.21.x 及以下版本的 Kubernetes。",-1),E=e("li",null,"您有一个可用节点作为边缘节点，该节点可以运行 Ubuntu（建议）或 CentOS。本教程以 Ubuntu 18.04 为例。",-1),y=e("li",null,"与 Kubernetes 集群节点不同，边缘节点应部署在单独的网络中。",-1),q=t(`

防止非边缘工作负载调度到边缘节点

由于部分守护进程集（例如，Calico）有强容忍度，为了避免影响边缘节点的正常工作，您需要手动 Patch Pod 以防止非边缘工作负载调度至边缘节点。

#!/bin/bash
+   
+   
+NoShedulePatchJson='{"spec":{"template":{"spec":{"affinity":{"nodeAffinity":{"requiredDuringSchedulingIgnoredDuringExecution":{"nodeSelectorTerms":[{"matchExpressions":[{"key":"node-role.kubernetes.io/edge","operator":"DoesNotExist"}]}]}}}}}}}'
+   
+ns="kube-system"
+
+
+DaemonSets=("nodelocaldns" "kube-proxy" "calico-node")
+
+length=\${#DaemonSets[@]}
+   
+for((i=0;i<length;i++));  
+do
+         ds=\${DaemonSets[$i]}
+        echo "Patching resources:DaemonSet/\${ds}" in ns:"$ns",
+        kubectl -n $ns patch DaemonSet/\${ds} --type merge --patch "$NoShedulePatchJson"
+        sleep 1
+done
+

创建防火墙规则和端口转发规则

若要确保边缘节点可以成功地与集群通信，您必须转发端口，以便外部流量进入您的网络。您可以根据下表将外网端口映射到相应的内网 IP 地址（主节点）和端口。此外，您还需要创建防火墙规则以允许流量进入这些端口（10000 至 10004）。

提示

在 ks-installer 的 ClusterConfiguration中，如果您设置的是局域网地址，那么需要配置转发规则。如果您未配置转发规则，直接连接 30000 – 30004 端口即可。

字段外网端口字段内网端口
cloudhubPort10000cloudhubNodePort30000
cloudhubQuicPort10001cloudhubQuicNodePort30001
cloudhubHttpsPort10002cloudhubHttpsNodePort30002
cloudstreamPort10003cloudstreamNodePort30003
tunnelPort10004tunnelNodePort30004

配置边缘节点

您需要在边缘节点上安装容器运行时并配置 EdgeMesh。

安装容器运行时

`,10),D={href:"https://docs.kubeedge.io/zh/docs/",target:"_blank",rel:"noopener noreferrer"},K={href:"https://docs.kubeedge.io/zh/docs/advanced/cri/",target:"_blank",rel:"noopener noreferrer"},B=e("div",{class:"hint-container tip"},[e("p",{class:"hint-container-title"},"提示"),e("p",null,"如果您的边缘节点使用 Docker 作为容器运行时，为确保 KubeSphere 可以获取 Pod 指标，请务必在边缘节点上安装 Docker v19.3.0 或更高版本。")],-1),N=e("h3",{id:"配置-edgemesh",tabindex:"-1"},[e("a",{class:"header-anchor",href:"#配置-edgemesh"},[e("span",null,"配置 EdgeMesh")])],-1),P={href:"https://kubeedge.io/zh/docs/advanced/edgemesh/",target:"_blank",rel:"noopener noreferrer"},M=t(`

  1. 编辑 /etc/nsswitch.conf。

    vi /etc/nsswitch.conf
+

  2. 在该文件中添加以下内容。

    hosts:          dns files mdns4_minimal [NOTFOUND=return]
+

  3. 保存文件并运行以下命令启用 IP 转发：

    sudo echo "net.ipv4.ip_forward = 1" >> /etc/sysctl.conf
+

  4. 验证修改：

    sudo sysctl -p | grep ip_forward
+

    预期结果：

    net.ipv4.ip_forward = 1
+

添加边缘节点

`,2),Q=e("li",null,[e("p",null,[n("使用 "),e("code",null,"admin"),n(" 用户登录控制台，点击左上角的"),e("strong",null,"平台管理"),n("。")])],-1),w=e("p",null,[n("选择"),e("strong",null,"集群管理"),n("，然后导航至"),e("strong",null,"节点"),n("下的"),e("strong",null,"边缘节点"),n("。")],-1),z={class:"hint-container tip"},C=e("p",{class:"hint-container-title"},"提示",-1),R={href:"https://kubesphere.io/zh/docs/v3.3/multicluster-management/",target:"_blank",rel:"noopener noreferrer"},S=t('

  • 点击添加。在出现的对话框中，设置边缘节点的节点名称并输入其内网 IP 地址。点击验证以继续。

    add-edge-node
    add-edge-node

    提示

    • 内网 IP 地址仅用于节点间通信，您不一定要使用边缘节点的真实内网 IP 地址。只要 IP 地址验证成功，您就可以使用该 IP 地址。
    • 建议您勾选方框添加默认污点。

  • 复制边缘节点配置命令下自动创建的命令，并在您的边缘节点上运行该命令。

    edge-command
    edge-command

    提示

    在运行该命令前，请确保您的边缘节点上已安装 wget。

    • ',2),U=e("p",null,"关闭对话框，刷新页面，您将看到边缘节点显示在列表中。",-1),F={class:"hint-container tip"},I=e("p",{class:"hint-container-title"},"提示",-1),V=e("strong",null,"边缘节点",-1),G={href:"https://kubesphere.io/zh/docs/v3.3/pluggable-components/metrics-server/",target:"_blank",rel:"noopener noreferrer"},L=t('

    收集边缘节点监控信息

    如果需要收集边缘节点的监控信息，请先在ClusterConfiguration 中开启 metrics_server，以及在 KubeEdge 中开启 edgeStream。

    1. 在 KubeSphere 控制台上，点击平台管理 > 集群管理。

    2. 在左侧导航栏。点击定制资源定义。

    3. 在右侧的搜索框中，输入 clusterconfiguration，并点击结果查看其详细页面。

    4. 点击 ks-installer 右侧的 icon，选择编辑 YAML。

    5. 找到 metrics_server，将 enabled 的 false 更改为 true。

        metrics_server:
+  enabled: true # 将“false”更改为“true”。
+

    6. 点击右下角的确定，保存配置。

    7. 进入 /etc/kubeedge/config 文件，搜索 edgeStream，将 false 更改为 true 并保存文件。

      cd /etc/kubeedge/config
+vi edgecore.yaml
+
      edgeStream:
+enable: true #将“false”更改为“true”。
+handshakeTimeout: 30
+readDeadline: 15
+server: xx.xxx.xxx.xxx:10004 #如果没有添加端口转发，将端口修改为30004。
+tlsTunnelCAFile: /etc/kubeedge/ca/rootCA.crt
+tlsTunnelCertFile: /etc/kubeedge/certs/server.crt
+tlsTunnelPrivateKeyFile: /etc/kubeedge/certs/server.key
+writeDeadline: 15
+

    8. 重启 edgecore.service。

      systemctl restart edgecore.service
+

    9. 如果仍然无法显示监控数据，执行以下命令：

      journalctl -u edgecore.service -b -r
+

      提示

      如果提示 failed to check the running environment: kube-proxy should not running on edge node when running edgecore，需要参考步骤 8 再次重启 edgecore.service。

    移除边缘节点

    移除边缘节点之前，请删除在该节点上运行的全部工作负载。

    1. 在边缘节点上运行以下命令：

      ./keadm reset
+
      apt remove mosquitto
+
      rm -rf /var/lib/kubeedge /var/lib/edged /etc/kubeedge/ca /etc/kubeedge/certs
+

      提示

      如果无法删除 tmpfs 挂载的文件夹，请重启节点或先取消挂载该文件夹。

    2. 运行以下命令从集群中移除边缘节点：

      kubectl delete node <edgenode-name>
+

    3. 如需从集群中卸载 KubeEdge，运行以下命令：

      helm uninstall kubeedge -n kubeedge
+
      kubectl delete ns kubeedge
+

      提示

      卸载完成后，您将无法为集群添加边缘节点。

    `,6);function H(T,j){const s=l("ExternalLinkIcon");return o(),d("div",null,[e("p",null,[n("KubeSphere 利用 "),e("a",g,[n("KubeEdge"),a(s)]),n(" 将原生容器化应用程序编排功能扩展到边缘的主机。KubeEdge 拥有单独的云端和边端核心模块，提供完整的边缘计算解决方案，但安装过程可能较为繁琐。")]),b,e("div",v,[m,e("p",null,[n("有关 KubeEdge 不同组件的更多信息，请参见 "),e("a",k,[n("KubeEdge 文档"),a(s)]),n("。")])]),A,f,e("ul",null,[e("li",null,[n("您需要启用 "),e("a",_,[n("KubeEdge"),a(s)]),n("。")]),x,E,y]),q,e("p",null,[e("a",D,[n("KubeEdge"),a(s)]),n(" 支持多种容器运行时，包括 Docker、containerd、CRI-O 和 Virtlet。有关更多信息，请参见 "),e("a",K,[n("KubeEdge 文档"),a(s)]),n("。")]),B,N,e("p",null,[n("执行以下步骤以在边缘节点上配置 "),e("a",P,[n("EdgeMesh"),a(s)]),n("。")]),M,e("ol",null,[Q,e("li",null,[w,e("div",z,[C,e("p",null,[n("如果已经启用"),e("a",R,[n("多集群管理"),a(s)]),n("，则需要首先选择一个集群。")])])]),S,e("li",null,[U,e("div",F,[I,e("p",null,[n("添加边缘节点后，如果在"),V,n("页面查看不到 CPU 和内存资源使用情况，请确保您的集群中已安装 "),e("a",G,[n("Metrics Server"),a(s)]),n(" 0.4.1 或以上版本。")])])])]),L])}const O=i(h,[["render",H],["__file","add-edge-nodes.html.vue"]]),X=JSON.parse('{"path":"/guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-edge-nodes.html","title":"添加边缘节点","lang":"zh-CN","frontmatter":{"title":"添加边缘节点","description":"KubeSphere 利用 KubeEdge 将原生容器化应用程序编排功能扩展到边缘的主机。KubeEdge 拥有单独的云端和边端核心模块，提供完整的边缘计算解决方案，但安装过程可能较为繁琐。 kubeedge_archkubeedge_arch 提示 有关 KubeEdge 不同组件的更多信息，请参见 KubeEdge 文档。 本教程演示如何将边缘节...","head":[["meta",{"property":"og:url","content":"https://github.com/abelit/abelit-datapeacock.git/guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-edge-nodes.html"}],["meta",{"property":"og:site_name","content":"数之雀"}],["meta",{"property":"og:title","content":"添加边缘节点"}],["meta",{"property":"og:description","content":"KubeSphere 利用 KubeEdge 将原生容器化应用程序编排功能扩展到边缘的主机。KubeEdge 拥有单独的云端和边端核心模块，提供完整的边缘计算解决方案，但安装过程可能较为繁琐。 kubeedge_archkubeedge_arch 提示 有关 KubeEdge 不同组件的更多信息，请参见 KubeEdge 文档。 本教程演示如何将边缘节..."}],["meta",{"property":"og:type","content":"article"}],["meta",{"property":"og:locale","content":"zh-CN"}],["meta",{"property":"og:updated_time","content":"2024-05-14T06:18:25.000Z"}],["meta",{"property":"article:author","content":"Abelit"}],["meta",{"property":"article:modified_time","content":"2024-05-14T06:18:25.000Z"}],["script",{"type":"application/ld+json"},"{\\"@context\\":\\"https://schema.org\\",\\"@type\\":\\"Article\\",\\"headline\\":\\"添加边缘节点\\",\\"image\\":[\\"\\"],\\"dateModified\\":\\"2024-05-14T06:18:25.000Z\\",\\"author\\":[{\\"@type\\":\\"Person\\",\\"name\\":\\"Abelit\\",\\"url\\":\\"https://github.com/abelit\\"}]}"]]},"headers":[{"level":2,"title":"准备工作","slug":"准备工作","link":"#准备工作","children":[]},{"level":2,"title":"防止非边缘工作负载调度到边缘节点","slug":"防止非边缘工作负载调度到边缘节点","link":"#防止非边缘工作负载调度到边缘节点","children":[]},{"level":2,"title":"创建防火墙规则和端口转发规则","slug":"创建防火墙规则和端口转发规则","link":"#创建防火墙规则和端口转发规则","children":[]},{"level":2,"title":"配置边缘节点","slug":"配置边缘节点","link":"#配置边缘节点","children":[{"level":3,"title":"安装容器运行时","slug":"安装容器运行时","link":"#安装容器运行时","children":[]},{"level":3,"title":"配置 EdgeMesh","slug":"配置-edgemesh","link":"#配置-edgemesh","children":[]}]},{"level":2,"title":"添加边缘节点","slug":"添加边缘节点","link":"#添加边缘节点","children":[]},{"level":2,"title":"收集边缘节点监控信息","slug":"收集边缘节点监控信息","link":"#收集边缘节点监控信息","children":[]},{"level":2,"title":"移除边缘节点","slug":"移除边缘节点","link":"#移除边缘节点","children":[]}],"git":{"createdTime":1715667505000,"updatedTime":1715667505000,"contributors":[{"name":"陈英","email":"abelit@dataforum-3.local","commits":1}]},"readingTime":{"minutes":5,"words":1499},"filePathRelative":"guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-edge-nodes.md","localizedDate":"2024年5月14日","autoDesc":true,"excerpt":"

    KubeSphere 利用 KubeEdge 将原生容器化应用程序编排功能扩展到边缘的主机。KubeEdge 拥有单独的云端和边端核心模块，提供完整的边缘计算解决方案，但安装过程可能较为繁琐。

    \\n
    kubeedge_arch
    \\n
    \\n

    提示

    \\n

    有关 KubeEdge 不同组件的更多信息，请参见 KubeEdge 文档。

    \\n
    "}');export{O as comp,X as data}; diff --git a/assets/add-new-nodes.html-C_nvYiNv.js b/assets/add-new-nodes.html-C_nvYiNv.js new file mode 100644 index 00000000..66e64f3f --- /dev/null +++ b/assets/add-new-nodes.html-C_nvYiNv.js @@ -0,0 +1,75 @@ +import{_ as l}from"./plugin-vue_export-helper-DlAUqK2U.js";import{r as p,o,c as i,a as n,d as s,b as e,f as t}from"./app-C9W9jIIt.js";const c={},u={href:"https://github.com/kubesphere/kubekey",target:"_blank",rel:"noopener noreferrer"},r=n("p",null,"本教程演示了如何将新节点添加到单节点集群。若要水平扩展多节点集群，操作步骤基本相同。",-1),d=n("h2",{id:"准备工作",tabindex:"-1"},[n("a",{class:"header-anchor",href:"#准备工作"},[n("span",null,"准备工作")])],-1),k={href:"https://kubesphere.io/zh/docs/v3.3/quick-start/all-in-one-on-linux/",target:"_blank",rel:"noopener noreferrer"},v={href:"https://kubesphere.io/zh/docs/v3.3/installing-on-linux/introduction/multioverview/#%E6%AD%A5%E9%AA%A4-2%E4%B8%8B%E8%BD%BD-kubekey",target:"_blank",rel:"noopener noreferrer"},m=t(`

    添加工作节点

    1. 使用 KubeKey 检索集群信息。以下命令会创建配置文件 (sample.yaml)。

      ./kk create config --from-cluster
+

    提示

    如果您的机器上已有配置文件，就可以跳过此步骤。例如，若要将节点添加到由 KubeKey 设置的多节点集群，如果您没有删除该集群，则可能仍拥有该配置文件。

    1. 在配置文件中，将新节点的信息放在 hosts 和 roleGroups 之下。该示例添加了两个新节点（即 node1 和 node2）。这里的 master1 是现有节点。

      ···
+spec:
+  hosts:
+  - {name: master1, address: 192.168.0.3, internalAddress: 192.168.0.3, user: root, password: Qcloud@123}
+  - {name: node1, address: 192.168.0.4, internalAddress: 192.168.0.4, user: root, password: Qcloud@123}
+  - {name: node2, address: 192.168.0.5, internalAddress: 192.168.0.5, user: root, password: Qcloud@123}
+  roleGroups:
+    etcd:
+    - master1
+    control-plane:
+    - master1
+    worker:
+    - node1
+    - node2
+···
+
    `,4),b={class:"hint-container tip"},h=n("p",{class:"hint-container-title"},"提示",-1),y={href:"https://kubesphere.io/zh/docs/v3.3/installing-on-linux/introduction/multioverview/#2-%E7%BC%96%E8%BE%91%E9%85%8D%E7%BD%AE%E6%96%87%E4%BB%B6",target:"_blank",rel:"noopener noreferrer"},g=n("li",null,[n("p",null,"添加新节点时，请勿修改现有节点的主机名。")],-1),_=n("li",null,[n("p",null,"用自己的主机名替换示例中的主机名。")],-1),f=t(`

    1. 执行以下命令：

      ./kk add nodes -f sample.yaml
+

    2. 安装完成后，您将能够在 KubeSphere 的控制台上查看新节点及其信息。在集群管理页面，选择左侧菜单节点下的集群节点，或者执行命令 kubectl get node 以检查更改。

      $ kubectl get node
+NAME          STATUS   ROLES           AGE   VERSION
+master1       Ready    master,worker   20d   v1.17.9
+node1         Ready    worker          31h   v1.17.9
+node2         Ready    worker          31h   v1.17.9
+

    添加主节点以实现高可用

    `,2),K={href:"https://www.haproxy.com/",target:"_blank",rel:"noopener noreferrer"},x=t(`

    1. 使用 KubeKey 创建配置文件。

      ./kk create config --from-cluster
+

    2. 打开文件，可以看到一些字段预先填充了值。将新节点和负载均衡器的信息添加到文件中。以下示例供您参考：

      apiVersion: kubekey.kubesphere.io/v1alpha1
+kind: Cluster
+metadata:
+  name: sample
+spec:
+  hosts:
+  # You should complete the ssh information of the hosts
+  - {name: master1, address: 172.16.0.2, internalAddress: 172.16.0.2, user: root, password: Testing123}
+  - {name: master2, address: 172.16.0.5, internalAddress: 172.16.0.5, user: root, password: Testing123}
+  - {name: master3, address: 172.16.0.6, internalAddress: 172.16.0.6, user: root, password: Testing123}
+  - {name: worker1, address: 172.16.0.3, internalAddress: 172.16.0.3, user: root, password: Testing123}
+  - {name: worker2, address: 172.16.0.4, internalAddress: 172.16.0.4, user: root, password: Testing123}
+  - {name: worker3, address: 172.16.0.7, internalAddress: 172.16.0.7, user: root, password: Testing123}
+  roleGroups:
+    etcd:
+    - master1
+    - master2
+    - master3
+    control-plane:
+    - master1
+    - master2
+    - master3
+    worker:
+    - worker1
+    - worker2
+    - worker3
+  controlPlaneEndpoint:
+    # If loadbalancer is used, 'address' should be set to loadbalancer's ip.
+    domain: lb.kubesphere.local
+    address: 172.16.0.253
+    port: 6443
+  kubernetes:
+    version: v1.22.12
+    imageRepo: kubesphere
+    clusterName: cluster.local
+    proxyMode: ipvs
+    masqueradeAll: false
+    maxPods: 110
+    nodeCidrMaskSize: 24
+  network:
+    plugin: calico
+    kubePodsCIDR: 10.233.64.0/18
+    kubeServiceCIDR: 10.233.0.0/18
+  registry:
+    privateRegistry: ""
+

    3. 请注意 controlPlaneEndpoint 字段。

        controlPlaneEndpoint:
+    # If you use a load balancer, the address should be set to the load balancer's ip.
+    domain: lb.kubesphere.local
+    address: 172.16.0.253
+    port: 6443
+
      • 负载均衡器的域名默认为 lb.kubesphere.local，用于内部访问。您可以按需进行更改。
      • 大多数情况下，您需要为 address 字段提供负载均衡器的私有 IP 地址。然而，不同的云厂商可能为负载均衡器进行不同的配置。例如，如果您在阿里云上配置服务器负载均衡 (SLB)，该平台会为 SLB 分配一个公共 IP 地址，这意味着您需要为 address 字段指定公共 IP 地址。
      • port 字段指代 api-server 的端口。

    4. 保存文件并执行以下命令以应用配置。

      ./kk add nodes -f sample.yaml
+
    `,1);function w(S,A){const a=p("ExternalLinkIcon");return o(),i("div",null,[n("p",null,[s("KubeSphere 使用一段时间之后，由于工作负载不断增加，您可能需要水平扩展集群。自 KubeSphere v3.0.0 起，您可以使用全新的安装程序 "),n("a",u,[s("KubeKey"),e(a)]),s(" 将新节点添加到集群。从根本上说，该操作是基于 Kubelet 的注册机制。换言之，新节点将自动加入现有的 Kubernetes 集群。KubeSphere 支持混合环境，这意味着新添加的主机操作系统可以是 CentOS 或者 Ubuntu。")]),r,d,n("ul",null,[n("li",null,[n("p",null,[s("您需要一个单节点集群。有关更多信息，请参见"),n("a",k,[s("在 Linux 上以 All-in-One 模式安装 KubeSphere"),e(a)]),s("。")])]),n("li",null,[n("p",null,[s("您需要已经"),n("a",v,[s("下载了 KubeKey"),e(a)]),s("。")])])]),m,n("div",b,[h,n("ul",null,[n("li",null,[n("p",null,[s("有关更多配置文件的信息，请参见"),n("a",y,[s("编辑配置文件"),e(a)]),s("。")])]),g,_])]),f,n("p",null,[s("添加主节点的步骤与添加工作节点的步骤大体一致，不过您需要为集群配置负载均衡器。您可以使用任何云负载均衡器或者硬件负载均衡器（例如 F5）。另外，Keepalived 和 "),n("a",K,[s("HAproxy"),e(a)]),s("、或者 Nginx 也是创建高可用集群的替代方案。")]),x])}const T=l(c,[["render",w],["__file","add-new-nodes.html.vue"]]),N=JSON.parse('{"path":"/guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-new-nodes.html","title":"添加新节点","lang":"zh-CN","frontmatter":{"title":"添加新节点","description":"KubeSphere 使用一段时间之后，由于工作负载不断增加，您可能需要水平扩展集群。自 KubeSphere v3.0.0 起，您可以使用全新的安装程序 KubeKey 将新节点添加到集群。从根本上说，该操作是基于 Kubelet 的注册机制。换言之，新节点将自动加入现有的 Kubernetes 集群。KubeSphere 支持混合环境，这意味着新添...","head":[["meta",{"property":"og:url","content":"https://github.com/abelit/abelit-datapeacock.git/guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-new-nodes.html"}],["meta",{"property":"og:site_name","content":"数之雀"}],["meta",{"property":"og:title","content":"添加新节点"}],["meta",{"property":"og:description","content":"KubeSphere 使用一段时间之后，由于工作负载不断增加，您可能需要水平扩展集群。自 KubeSphere v3.0.0 起，您可以使用全新的安装程序 KubeKey 将新节点添加到集群。从根本上说，该操作是基于 Kubelet 的注册机制。换言之，新节点将自动加入现有的 Kubernetes 集群。KubeSphere 支持混合环境，这意味着新添..."}],["meta",{"property":"og:type","content":"article"}],["meta",{"property":"og:locale","content":"zh-CN"}],["meta",{"property":"og:updated_time","content":"2024-05-14T06:18:25.000Z"}],["meta",{"property":"article:author","content":"Abelit"}],["meta",{"property":"article:modified_time","content":"2024-05-14T06:18:25.000Z"}],["script",{"type":"application/ld+json"},"{\\"@context\\":\\"https://schema.org\\",\\"@type\\":\\"Article\\",\\"headline\\":\\"添加新节点\\",\\"image\\":[\\"\\"],\\"dateModified\\":\\"2024-05-14T06:18:25.000Z\\",\\"author\\":[{\\"@type\\":\\"Person\\",\\"name\\":\\"Abelit\\",\\"url\\":\\"https://github.com/abelit\\"}]}"]]},"headers":[{"level":2,"title":"准备工作","slug":"准备工作","link":"#准备工作","children":[]},{"level":2,"title":"添加工作节点","slug":"添加工作节点","link":"#添加工作节点","children":[]},{"level":2,"title":"添加主节点以实现高可用","slug":"添加主节点以实现高可用","link":"#添加主节点以实现高可用","children":[]}],"git":{"createdTime":1715667505000,"updatedTime":1715667505000,"contributors":[{"name":"陈英","email":"abelit@dataforum-3.local","commits":1}]},"readingTime":{"minutes":3.54,"words":1063},"filePathRelative":"guide/cloudnative/kubesphere/install-on-linux/cluster-operation/add-new-nodes.md","localizedDate":"2024年5月14日","autoDesc":true,"excerpt":"

    KubeSphere 使用一段时间之后，由于工作负载不断增加，您可能需要水平扩展集群。自 KubeSphere v3.0.0 起，您可以使用全新的安装程序 KubeKey 将新节点添加到集群。从根本上说，该操作是基于 Kubelet 的注册机制。换言之，新节点将自动加入现有的 Kubernetes 集群。KubeSphere 支持混合环境，这意味着新添加的主机操作系统可以是 CentOS 或者 Ubuntu。

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    项目地址

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    项目地址

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    为了方便下游开发者针对自己的应用场景定制模型，我们同时实现了基于 P-Tuning v2 的高效参数微调方法 (使用指南) ，INT4 量化级别下最低只需 7GB 显存即可启动微调。

    项目地址

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    项目地址

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    项目地址

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    项目地址

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    项目地址

    Github

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    项目地址

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    项目地址

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    项目地址

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    简介

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    简介

    FastGPT 是一个基于 LLM 大语言模型的知识库问答系统，提供开箱即用的数据处理、模型调用等能力。同时可以通过 Flow 可视化进行工作流编排，从而实现复杂的问答场景！

    项目地址

    Github

    https://github.com/labring/FastGPT.git

    h2ogpt

    简介

    Query and summarize your documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project.

    项目地址

    Github

    https://github.com/h2oai/h2ogpt.git

    ChatDev

    简介

    ChatDev stands as a virtual software company that operates through various intelligent agents holding different roles, including Chief Executive Officer, Chief Technology Officer, Programmer, Tester, and more. These agents form a multi-agent organizational structure and are united by a mission to "revolutionize the digital world through programming." The agents within ChatDev collaborate by participating in specialized functional seminars, including tasks such as designing, coding, testing, and documenting.

    项目地址

    Github

    https://github.com/OpenBMB/ChatDev.git

    ValueNet

    简介

    ValueNet: A Neural Text-to-SQL Architecture Incorporating Values

    项目地址

    Github

    https://github.com/brunnurs/valuenet.git

    OpenChat

    简介

    OpenChat is an everyday user chatbot console that simplifies the utilization of large language models. With the advancements in AI, the installation and usage of these models have become overwhelming. OpenChat aims to address this challenge by providing a two-step setup process to create a comprehensive chatbot console. It serves as a central hub for managing multiple customized chatbots.

    项目地址

    Github

    https://github.com/openchatai/OpenChat.git

    Bringing-Old-Photos-Back-to-Life

    简介

    ringing Old Photo Back to Life (CVPR 2020 oral)

    项目地址

    Github

    https://github.com/microsoft/Bringing-Old-Photos-Back-to-Life.git

    PaddleHub

    简介

    Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)

    项目地址

    Github

    https://github.com/PaddlePaddle/PaddleHub.git

    Fooocus

    简介

    Fooocus is an image generating software (based on Gradio).

    项目地址

    Github

    git@github.com:aileague/Fooocus.git

    OpenCat

    简介

    An open source quadruped robot pet framework for developing Boston Dynamics-style four-legged robots that are perfect for STEM, coding & robotics education, IoT robotics applications, AI-enhanced robotics application services, research, and DIY robotics kit development.

    项目地址

    Github

    https://github.com/PetoiCamp/OpenCat.git

    Qwen-7B

    简介

    Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques.

    项目地址

    Github

    https://github.com/QwenLM/Qwen-7B.git

    MaxKB

    简介

    MaxKB 是一款基于 LLM 大语言模型的知识库问答系统。MaxKB = Max Knowledge Base，旨在成为企业的最强大脑。

    项目地址

    Github

    https://github.com/1Panel-dev/MaxKB.git

    MaxText

    简介

    MaxText is a high performance, arbitrarily scalable, open-source, simple, easily forkable, well-tested, batteries included LLM written in pure Python/Jax and targeting Google Cloud TPUs. MaxText typically achieves 55% to 60% model-flop utilization and scales from single host to very large clusters while staying simple and "optimization-free" thanks to the power of Jax and the XLA compiler.

    项目地址

    Github

    https://github.com/google/maxtext.git

    private-gpt

    简介

    Interact with your documents using the power of GPT, 100% privately, no data leaks

    项目地址

    Github

    https://github.com/zylon-ai/private-gpt.git

    reor

    简介

    Self-organizing AI note-taking app that runs models locally.

    项目地址

    Github

    https://github.com/reorproject/reor.git

    langchain

    简介

    🦜🔗 Build context-aware reasoning applications.

    To help you ship LangChain apps to production faster, check out LangSmith. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications. Fill out this form to speak with our sales team.

    项目地址

    Github

    https://github.com/langchain-ai/langchain.git

    ollama

    简介

    Get up and running with Llama 2, Mistral, Gemma, and other large language models.

    项目地址

    Github

    https://github.com/ollama/ollama.git

    llama

    简介

    We are unlocking the power of large language models. Our latest version of Llama is now accessible to individuals, creators, researchers, and businesses of all sizes so that they can experiment, innovate, and scale their ideas responsibly.

    This release includes model weights and starting code for pre-trained and fine-tuned Llama language models — ranging from 7B to 70B parameters.

    This repository is intended as a minimal example to load Llama 2 models and run inference. For more detailed examples leveraging Hugging Face, see llama-recipes.

    项目地址

    Github

    https://github.com/meta-llama/llama.git

    gemma

    简介

    Open weights LLM from Google DeepMind.

    项目地址

    Github

    https://github.com/google-deepmind/gemma.git

    anything-llm

    简介

    A multi-user ChatGPT for any LLMs and vector database. Unlimited documents, messages, and storage in one privacy-focused app. Now available as a desktop application with a built-in LLM!

    项目地址

    Github

    https://github.com/Mintplex-Labs/anything-llm.git

    lobe-chat

    简介

    🤯 Lobe Chat - an open-source, modern-design LLMs/AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Perplexity / Bedrock / Azure / Mistral / Ollama ), Multi-Modals (Vision/TTS) and plugin system. One-click FREE deployment of your private ChatGPT chat application.

    项目地址

    Github

    https://github.com/lobehub/lobe-chat.git

    ragflow

    简介

    RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

    项目地址

    Github

    https://github.com/infiniflow/ragflow.git

    modescope

    简介

    ModelScope: bring the notion of Model-as-a-Service to life.

    项目地址

    Github

    https://github.com/modelscope/modelscope.git

    Open-Sora

    简介

    Open-Sora: Democratizing Efficient Video Production for All.

    项目地址

    Github

    https://github.com/hpcaitech/Open-Sora.git

    ColossalAI

    简介

    Making large AI models cheaper, faster and more accessible.

    项目地址

    Github

    https://github.com/hpcaitech/ColossalAI.git

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