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Python 人工智能 5秒钟偷走你的声音 介绍Python 深度学习AI - 声音克隆、声音模仿，是一个三阶段的深度学习框架，允许从几秒钟的音频中创建语音的数字表示，并用它来调节文本到语音模型，该模型经过培训，可以概括到新的声音。环境准备与安装原始英文版地址：https://github.com/CorentinJ/Real-Time-Voice-Cloning中文二次开发版（本文使用该版本）：https://github.com/babysor/MockingBirdpycharm环境下载：https://www.jetbrains.com/pycharm/download/#section=windowsconda虚拟环境：https://www.anaconda.com/products/individualFFmpeg ：https://github.com/BtbN/FFmpeg-Builds/releases模型文件：https://pan.baidu.com/s/1PI-hM3sn5wbeChRryX-RCQ 提取码 2021在电脑系统上安装 FFmpeg 工具下载zip压缩包连接为：https://github.com/BtbN/FFmpeg-Builds/releases/download/autobuild-2021-11-09-12-23/ffmpeg-N-104488-ga13646639f-win64-gpl.zip下载完成后将其解压到一个目录后在系统的环境变量中添加该目录打开新的cmd中查看是否安装成功ffmpeg -version使用打开项目目录后，创建时使用conda的Python 3.9虚拟环境创建完成后，在cmd中查看现有的虚拟环境，并进入刚刚创建的虚拟环境conda env listactivate pythonProject1进入环境后在进行安装pip所需依赖，并使用国内源进行安装实现下载加速pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple在虚拟环境下安装pytorchpip install torch -i https://pypi.tuna.tsinghua.edu.cn/simple回到pycharm中，将模型导入到项目目录下，把目录复制黏贴到项目中修改一行代码，在 synthesizer/utils/symbols.py 文件中修改为： _characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz12340!'(),-.:;? '之后在terminal中启动工具箱使用音频合成工具箱Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。48篇原创内容公众号 https://blog.csdn.net/qq_33921750https://my.oschina.net/u/3981543https://www.zhihu.com/people/chen-bu-yun-2https://segmentfault.com/u/hppyvyv6/articleshttps://juejin.cn/user/3315782802482007https://space.bilibili.com/352476552/articlehttps://cloud.tencent.com/developer/column/93230知乎、CSDN、开源中国、思否、掘金、哔哩哔哩、腾讯云本文使用 文章同步助手 同步 -
kubernetes（k8s）中部署dashboard可视化面板 Web 界面 (Dashboard)Dashboard 是基于网页的 Kubernetes 用户界面。你可以使用 Dashboard 将容器应用部署到 Kubernetes 集群中，也可以对容器应用排错，还能管理集群资源。你可以使用 Dashboard 获取运行在集群中的应用的概览信息，也可以创建或者修改 Kubernetes 资源 （如 Deployment，Job，DaemonSet 等等）。例如，你可以对 Deployment 实现弹性伸缩、发起滚动升级、重启 Pod 或者使用向导创建新的应用。Dashboard 同时展示了 Kubernetes 集群中的资源状态信息和所有报错信息。kubernetes官方提供的可视化界面https://github.com/kubernetes/dashboard一键执行kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.4.0/aio/deploy/recommended.yaml 先下载后执行root@master1:~/dashboard# wget https://raw.githubusercontent.com/kubernetes/dashboard/v2.4.0/aio/deploy/recommended.yaml root@master1:~/dashboard# kubectl apply -f recommended.yaml若下载不下来，可以使用vim添加进去后再次执行root@master1:~/dashboard# vim recommended.yaml root@master1:~/dashboard# root@master1:~/dashboard# root@master1:~/dashboard# cat recommended.yaml # Copyright 2017 The Kubernetes Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. apiVersion: v1 kind: Namespace metadata: name: kubernetes-dashboard --- apiVersion: v1 kind: ServiceAccount metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard --- kind: Service apiVersion: v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard spec: ports: - port: 443 targetPort: 8443 selector: k8s-app: kubernetes-dashboard --- apiVersion: v1 kind: Secret metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard-certs namespace: kubernetes-dashboard type: Opaque --- apiVersion: v1 kind: Secret metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard-csrf namespace: kubernetes-dashboard type: Opaque data: csrf: "" --- apiVersion: v1 kind: Secret metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard-key-holder namespace: kubernetes-dashboard type: Opaque --- kind: ConfigMap apiVersion: v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard-settings namespace: kubernetes-dashboard --- kind: Role apiVersion: rbac.authorization.k8s.io/v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard rules: # Allow Dashboard to get, update and delete Dashboard exclusive secrets. - apiGroups: [""] resources: ["secrets"] resourceNames: ["kubernetes-dashboard-key-holder", "kubernetes-dashboard-certs", "kubernetes-dashboard-csrf"] verbs: ["get", "update", "delete"] # Allow Dashboard to get and update 'kubernetes-dashboard-settings' config map. - apiGroups: [""] resources: ["configmaps"] resourceNames: ["kubernetes-dashboard-settings"] verbs: ["get", "update"] # Allow Dashboard to get metrics. - apiGroups: [""] resources: ["services"] resourceNames: ["heapster", "dashboard-metrics-scraper"] verbs: ["proxy"] - apiGroups: [""] resources: ["services/proxy"] resourceNames: ["heapster", "http:heapster:", "https:heapster:", "dashboard-metrics-scraper", "http:dashboard-metrics-scraper"] verbs: ["get"] --- kind: ClusterRole apiVersion: rbac.authorization.k8s.io/v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard rules: # Allow Metrics Scraper to get metrics from the Metrics server - apiGroups: ["metrics.k8s.io"] resources: ["pods", "nodes"] verbs: ["get", "list", "watch"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: RoleBinding metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard roleRef: apiGroup: rbac.authorization.k8s.io kind: Role name: kubernetes-dashboard subjects: - kind: ServiceAccount name: kubernetes-dashboard namespace: kubernetes-dashboard --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: kubernetes-dashboard roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: kubernetes-dashboard subjects: - kind: ServiceAccount name: kubernetes-dashboard namespace: kubernetes-dashboard --- kind: Deployment apiVersion: apps/v1 metadata: labels: k8s-app: kubernetes-dashboard name: kubernetes-dashboard namespace: kubernetes-dashboard spec: replicas: 1 revisionHistoryLimit: 10 selector: matchLabels: k8s-app: kubernetes-dashboard template: metadata: labels: k8s-app: kubernetes-dashboard spec: containers: - name: kubernetes-dashboard image: kubernetesui/dashboard:v2.4.0 imagePullPolicy: Always ports: - containerPort: 8443 protocol: TCP args: - --auto-generate-certificates - --namespace=kubernetes-dashboard # Uncomment the following line to manually specify Kubernetes API server Host # If not specified, Dashboard will attempt to auto discover the API server and connect # to it. Uncomment only if the default does not work. # - --apiserver-host=http://my-address:port volumeMounts: - name: kubernetes-dashboard-certs mountPath: /certs # Create on-disk volume to store exec logs - mountPath: /tmp name: tmp-volume livenessProbe: httpGet: scheme: HTTPS path: / port: 8443 initialDelaySeconds: 30 timeoutSeconds: 30 securityContext: allowPrivilegeEscalation: false readOnlyRootFilesystem: true runAsUser: 1001 runAsGroup: 2001 volumes: - name: kubernetes-dashboard-certs secret: secretName: kubernetes-dashboard-certs - name: tmp-volume emptyDir: {} serviceAccountName: kubernetes-dashboard nodeSelector: "kubernetes.io/os": linux # Comment the following tolerations if Dashboard must not be deployed on master tolerations: - key: node-role.kubernetes.io/master effect: NoSchedule --- kind: Service apiVersion: v1 metadata: labels: k8s-app: dashboard-metrics-scraper name: dashboard-metrics-scraper namespace: kubernetes-dashboard spec: ports: - port: 8000 targetPort: 8000 selector: k8s-app: dashboard-metrics-scraper --- kind: Deployment apiVersion: apps/v1 metadata: labels: k8s-app: dashboard-metrics-scraper name: dashboard-metrics-scraper namespace: kubernetes-dashboard spec: replicas: 1 revisionHistoryLimit: 10 selector: matchLabels: k8s-app: dashboard-metrics-scraper template: metadata: labels: k8s-app: dashboard-metrics-scraper spec: securityContext: seccompProfile: type: RuntimeDefault containers: - name: dashboard-metrics-scraper image: kubernetesui/metrics-scraper:v1.0.7 ports: - containerPort: 8000 protocol: TCP livenessProbe: httpGet: scheme: HTTP path: / port: 8000 initialDelaySeconds: 30 timeoutSeconds: 30 volumeMounts: - mountPath: /tmp name: tmp-volume securityContext: allowPrivilegeEscalation: false readOnlyRootFilesystem: true runAsUser: 1001 runAsGroup: 2001 serviceAccountName: kubernetes-dashboard nodeSelector: "kubernetes.io/os": linux # Comment the following tolerations if Dashboard must not be deployed on master tolerations: - key: node-role.kubernetes.io/master effect: NoSchedule volumes: - name: tmp-volume emptyDir: {} root@master1:~/dashboard# root@master1:~/dashboard# kubectl apply -f recommended.yaml 查看是否在运行 root@master1:~/dashboard# kubectl get pod -n kubernetes-dashboard NAME READY STATUS RESTARTS AGE dashboard-metrics-scraper-c45b7869d-2xhx8 1/1 Running 0 2m40s kubernetes-dashboard-576cb95f94-scrxw 1/1 Running 0 2m40s root@master1:~/dashboard# 修改为nodeIP root@master1:~/dashboard# kubectl edit svc kubernetes-dashboard -n kubernetes-dashboard service/kubernetes-dashboard edited 创建访问账号root@master1:~/dashboard# vim dash.yaml root@master1:~/dashboard# cat dash.yaml apiVersion: v1 kind: ServiceAccount metadata: name: admin-user namespace: kubernetes-dashboard --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: admin-user roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: cluster-admin subjects: - kind: ServiceAccount name: admin-user namespace: kubernetes-dashboard root@master1:~/dashboard#root@master1:~/dashboard# kubectl apply -f dash.yaml serviceaccount/admin-user created clusterrolebinding.rbac.authorization.k8s.io/admin-user created root@master1:~/dashboard#查看token令牌root@master1:~/dashboard# root@master1:~/dashboard# kubectl -n kubernetes-dashboard get secret $(kubectl -n kubernetes-dashboard get sa/admin-user -o jsonpath="{.secrets[0].name}") -o go-template="{{.data.token | base64decode}}" eyJhbGciOiJSUzI1NiIsImtpZCI6IlBqb09VbWNDX1hVdldnM3pjcmllQ1NMMXA3bUZQRTBfNEdNTEZnUnhScncifQ.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.v1MCLz9q_IvP49sh69XLoBZc0YQ6X1Pbw-lfZYYeeDcw6HqmEkW1Lfs1Soz-b8ir4lbWvNF90h6pGU_1aEE9NkTaV5b6A5FGhKivVk-09gjcx8JC8RDtlJ5Ol-MiHQOqPY67qPO6UzRm3H1luGKXtnNnTA74PTOssGgH3eNsFMKOPqaANt03h6-sjVXQBD2uca3l1pD5ywa-P54WwL_uJraCpIopX98iiFoN5hV_2W6dnPJ09whmaaTl8fJGXQ_0ln5NbdcURQeuL-ZRAC_b5i4RoBKlOHjDg1AREH_27qtwl9GbDNe-HgzSsFGKHzLV93Pqjwo9pI03P6xkyYym9groot@master1:~/dashboard#查看svc服务ip以及端口root@master1:~/dashboard# kubectl get svc -n kubernetes-dashboard NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE dashboard-metrics-scraper ClusterIP 10.233.58.150 <none> 8000/TCP 7m22s kubernetes-dashboard NodePort 10.233.38.57 <none> 443:30282/TCP 7m22s root@master1:~/dashboard#访问页面 https://blog.csdn.net/qq_33921750https://my.oschina.net/u/3981543https://www.zhihu.com/people/chen-bu-yun-2https://segmentfault.com/u/hppyvyv6/articleshttps://juejin.cn/user/3315782802482007https://space.bilibili.com/352476552/articlehttps://cloud.tencent.com/developer/column/93230知乎、CSDN、开源中国、思否、掘金、哔哩哔哩、腾讯云本文使用 文章同步助手 同步
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kubernetes（k8s）安装命令行自动补全功能 Ubuntu下安装命令root@master1:~# apt install -y bash-completion Reading package lists... Done Building dependency tree Reading state information... Done bash-completion is already the newest version (1:2.10-1ubuntu1). 0 upgraded, 0 newly installed, 0 to remove and 29 not upgraded.centos下安装命令[root@dss ~]# yum install bash-completion -y Loaded plugins: fastestmirror, langpacks Loading mirror speeds from cached hostfile * epel: mirrors.tuna.tsinghua.edu.cn Package 1:bash-completion-2.1-8.el7.noarch already installed and latest version Nothing to do [root@dss ~]#root@master1:~# locate bash_completion /etc/bash_completion /etc/bash_completion.d /etc/bash_completion.d/apport_completion /etc/bash_completion.d/git-prompt /etc/profile.d/bash_completion.sh /snap/core18/2128/etc/bash_completion /snap/core18/2128/usr/share/bash-completion/bash_completion /snap/core18/2128/usr/share/doc/bash/README.md.bash_completion.gz /snap/core18/2128/usr/share/perl5/Debian/Debhelper/Sequence/bash_completion.pm /snap/lxd/21029/etc/bash_completion.d /snap/lxd/21029/etc/bash_completion.d/snap.lxd.lxc /usr/share/bash-completion/bash_completion /usr/share/doc/bash/README.md.bash_completion.gz /usr/share/perl5/Debian/Debhelper/Sequence/bash_completion.pm /var/lib/docker/overlay2/0f27e9d2ca7fbe8a3b764a525f1c58990345512fa6dfe4162aba3e05ccff5b56/diff/etc/bash_completion.d /var/lib/docker/overlay2/5eb1b0cb946881e1081bfa7a608b6fa85dbf2cb7e67f84b038f3b8a85bd13196/diff/usr/local/lib/node_modules/npm/node_modules/dashdash/etc/dashdash.bash_completion.in /var/lib/docker/overlay2/76c41c1d1eb6eaa7b9259bd822a4bffebf180717a24319d2ffec3b4dcae0e66a/merged/etc/bash_completion.d /var/lib/docker/overlay2/78b8ab76c0e0ad7ee873daab9ab3987a366ec32fda68a4bb56a218c7f8806a58/merged/etc/profile.d/bash_completion.sh /var/lib/docker/overlay2/78b8ab76c0e0ad7ee873daab9ab3987a366ec32fda68a4bb56a218c7f8806a58/merged/usr/share/bash-completion/bash_completion /var/lib/docker/overlay2/802133f75f62596a2c173f1b57231efbe210eddd7a43770a62ca94c86ce2ca56/merged/usr/local/lib/node_modules/npm/node_modules/dashdash/etc/dashdash.bash_completion.in /var/lib/docker/overlay2/ee672bdd0bf0fdf590f9234a8a784ca12c262c47a0ac8ab91acc0942dfafc339/diff/etc/profile.d/bash_completion.sh /var/lib/docker/overlay2/ee672bdd0bf0fdf590f9234a8a784ca12c262c47a0ac8ab91acc0942dfafc339/diff/usr/share/bash-completion/bash_completion临时环境变量root@master1:~# source /usr/share/bash-completion/bash_completion root@master1:~# source <(kubectl completion bash) root@master1:~# root@master1:~# root@master1:~# kubectl annotate auth config delete exec kustomize plugin run uncordon api-resources autoscale cordon describe explain label port-forward scale version api-versions certificate cp diff expose logs proxy set wait apply cluster-info create drain get options replace taint attach completion debug edit help patch rollout top root@master1:~# kubectl永久写入环境变量配置文件root@master1:~# root@master1:~# root@master1:~# echo "source <(kubectl completion bash)" >> ~/.bashrc root@master1:~# root@master1:~# cat ~/.bashrc ----略---- # some more ls aliases alias ll='ls -alF' alias la='ls -A' alias l='ls -CF' # Alias definitions. # You may want to put all your additions into a separate file like # ~/.bash_aliases, instead of adding them here directly. # See /usr/share/doc/bash-doc/examples in the bash-doc package. if [ -f ~/.bash_aliases ]; then . ~/.bash_aliases fi # enable programmable completion features (you don't need to enable # this, if it's already enabled in /etc/bash.bashrc and /etc/profile # sources /etc/bash.bashrc). #if [ -f /etc/bash_completion ] && ! shopt -oq posix; then # . /etc/bash_completion #fi source <(kubectl completion bash) root@master1:~# https://blog.csdn.net/qq_33921750https://my.oschina.net/u/3981543https://www.zhihu.com/people/chen-bu-yun-2https://segmentfault.com/u/hppyvyv6/articleshttps://juejin.cn/user/3315782802482007https://space.bilibili.com/352476552/articlehttps://cloud.tencent.com/developer/column/93230知乎、CSDN、开源中国、思否、掘金、哔哩哔哩、腾讯云本文使用 文章同步助手 同步
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人工智能 deepface 换脸技术 学习 介绍 Deepface是一个轻量级的python人脸识别和人脸属性分析（年龄、性别、情感和种族）框架。它是一种混合人脸识别框架缠绕状态的最先进的模型：VGG-Face，Google FaceNet，OpenFace，Facebook DeepFace，DeepID，ArcFace和Dlib。那些模型已经达到并通过了人类水平的准确性。该库主要基于 TensorFlow 和 Keras。环境准备与安装项目地址：https://github.com/serengil/deepfacepycharm环境下载：https://www.jetbrains.com/pycharm/download/#section=windowsconda虚拟环境：https://www.anaconda.com/products/individual数据集：https://github.com/serengil/deepface_models/releases/download/v1.0/vgg_face_weights.h5https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5创建项目使用打开项目目录后，创建时使用conda的Python 3.9虚拟环境安装pip依赖创建完成后，在cmd中查看现有的虚拟环境，并进入刚刚创建的虚拟环境conda env listactivate pythonProject进入环境后在进行安装pip所需依赖，并使用国内源进行安装实现下载加速pip install deepface -i https://pypi.tuna.tsinghua.edu.cn/simple使用面部验证此功能验证同一人或不同人员的面部对。它期望精确的图像路径作为输入。也欢迎通过笨重或基于 64 编码的图像。cd C:\Users\Administrator\PycharmProjects\pythonProject\tests\dataset from deepface import DeepFace result = DeepFace.verify(img1_path = "img1.jpg", img2_path = "img2.jpg")会自动下载数据集，若无法下载数据集可以提前下载好数据集，放入到 C:\Users\Administrator.deepface\weights\ 目录下面部属性分析Deepface还配备了一个强大的面部属性分析模块，包括年龄，性别，面部表情（包括愤怒，恐惧，中性，悲伤，厌恶，快乐和惊喜）和种族（包括亚洲，白人，中东，印度，拉丁和黑色）预测。from deepface import DeepFace obj = DeepFace.analyze(img_path = "img4.jpg", actions = ['age', 'gender', 'race', 'emotion'])会自动下载数据集，若无法下载数据集可以提前下载好数据集，放入到 C:\Users\Administrator.deepface\weights\ 目录下Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。49篇原创内容公众号 https://blog.csdn.net/qq_33921750https://my.oschina.net/u/3981543https://www.zhihu.com/people/chen-bu-yun-2https://segmentfault.com/u/hppyvyv6/articleshttps://juejin.cn/user/3315782802482007https://space.bilibili.com/352476552/articlehttps://cloud.tencent.com/developer/column/93230知乎、CSDN、开源中国、思否、掘金、哔哩哔哩、腾讯云本文使用 文章同步助手 同步
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KubeSphere 高可用集群搭建并启用所有插件 介绍大多数情况下，单主节点集群大致足以供开发和测试环境使用。但是，对于生产环境，您需要考虑集群的高可用性。如果关键组件（例如 kube-apiserver、kube-scheduler 和 kube-controller-manager）都在同一个主节点上运行，一旦主节点宕机，Kubernetes 和 KubeSphere 都将不可用。因此，您需要为多个主节点配置负载均衡器，以创建高可用集群。您可以使用任意云负载均衡器或者任意硬件负载均衡器（例如 F5）。此外，也可以使用 Keepalived 和 HAproxy，或者 Nginx 来创建高可用集群。架构在您开始操作前，请确保准备了 6 台 Linux 机器，其中 3 台充当主节点，另外 3 台充当工作节点。下图展示了这些机器的详情，包括它们的私有 IP 地址和角色。配置负载均衡器您必须在您的环境中创建一个负载均衡器来监听（在某些云平台也称作监听器）关键端口。建议监听下表中的端口。服务 协议 端口apiserver TCP 6443ks-console TCP 30880http TCP 80https TCP 443配置免密root@hello:~# ssh-keygen root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.10 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.11 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.12 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.13 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.14 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.15 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.16 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.51 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.52 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.53 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.54 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.55 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.56 root@hello:~# ssh-copy-id -i ~/.ssh/id_rsa.pub root@192.168.1.57下载 KubeKeyKubekey 是新一代安装程序，可以简单、快速和灵活地安装 Kubernetes 和 KubeSphere。root@cby:~# export KKZONE=cn root@cby:~# curl -sfL https://get-kk.kubesphere.io | VERSION=v1.2.0 sh - Downloading kubekey v1.2.0 from https://kubernetes.pek3b.qingstor.com/kubekey/releases/download/v1.2.0/kubekey-v1.2.0-linux-amd64.tar.gz ... Kubekey v1.2.0 Download Complete!为 kk 添加可执行权限root@cby:~# chmod +x kk root@cby:~# ./kk create config --with-kubesphere v3.2.0 --with-kubernetes v1.22.1部署 KubeSphere 和 Kubernetesroot@cby:~# vim config-sample.yaml root@cby:~# root@cby:~# root@cby:~# cat config-sample.yaml apiVersion: kubekey.kubesphere.io/v1alpha1 kind: Cluster metadata: name: sample spec: hosts: - {name: master1, address: 192.168.1.10, internalAddress: 192.168.1.10, user: root, password: Cby123..} - {name: master2, address: 192.168.1.11, internalAddress: 192.168.1.11, user: root, password: Cby123..} - {name: master3, address: 192.168.1.12, internalAddress: 192.168.1.12, user: root, password: Cby123..} - {name: node1, address: 192.168.1.13, internalAddress: 192.168.1.13, user: root, password: Cby123..} - {name: node2, address: 192.168.1.14, internalAddress: 192.168.1.14, user: root, password: Cby123..} - {name: node3, address: 192.168.1.15, internalAddress: 192.168.1.15, user: root, password: Cby123..} - {name: node4, address: 192.168.1.16, internalAddress: 192.168.1.16, user: root, password: Cby123..} - {name: node5, address: 192.168.1.51, internalAddress: 192.168.1.51, user: root, password: Cby123..} - {name: node6, address: 192.168.1.52, internalAddress: 192.168.1.52, user: root, password: Cby123..} - {name: node7, address: 192.168.1.53, internalAddress: 192.168.1.53, user: root, password: Cby123..} - {name: node8, address: 192.168.1.54, internalAddress: 192.168.1.54, user: root, password: Cby123..} - {name: node9, address: 192.168.1.55, internalAddress: 192.168.1.55, user: root, password: Cby123..} - {name: node10, address: 192.168.1.56, internalAddress: 192.168.1.56, user: root, password: Cby123..} - {name: node11, address: 192.168.1.57, internalAddress: 192.168.1.57, user: root, password: Cby123..} roleGroups: etcd: - master1 - master2 - master3 master: - master1 - master2 - master3 worker: - node1 - node2 - node3 - node4 - node5 - node6 - node7 - node8 - node9 - node10 - node11 controlPlaneEndpoint: ##Internal loadbalancer for apiservers #internalLoadbalancer: haproxy domain: lb.kubesphere.local address: "192.168.1.20" port: 6443 kubernetes: version: v1.22.1 clusterName: cluster.local network: plugin: calico kubePodsCIDR: 10.233.64.0/18 kubeServiceCIDR: 10.233.0.0/18 registry: registryMirrors: [] insecureRegistries: [] addons: [] --- apiVersion: installer.kubesphere.io/v1alpha1 kind: ClusterConfiguration metadata: name: ks-installer namespace: kubesphere-system labels: version: v3.2.0 spec: persistence: storageClass: "" authentication: jwtSecret: "" local_registry: "" # dev_tag: "" etcd: monitoring: false endpointIps: localhost port: 2379 tlsEnable: true common: core: console: enableMultiLogin: true port: 30880 type: NodePort # apiserver: # resources: {} # controllerManager: # resources: {} redis: enabled: false volumeSize: 2Gi openldap: enabled: false volumeSize: 2Gi minio: volumeSize: 20Gi monitoring: # type: external endpoint: http://prometheus-operated.kubesphere-monitoring-system.svc:9090 GPUMonitoring: enabled: false gpu: kinds: - resourceName: "nvidia.com/gpu" resourceType: "GPU" default: true es: # master: # volumeSize: 4Gi # replicas: 1 # resources: {} # data: # volumeSize: 20Gi # replicas: 1 # resources: {} logMaxAge: 7 elkPrefix: logstash basicAuth: enabled: false username: "" password: "" externalElasticsearchUrl: "" externalElasticsearchPort: "" alerting: enabled: false # thanosruler: # replicas: 1 # resources: {} auditing: enabled: false # operator: # resources: {} # webhook: # resources: {} devops: enabled: false jenkinsMemoryLim: 2Gi jenkinsMemoryReq: 1500Mi jenkinsVolumeSize: 8Gi jenkinsJavaOpts_Xms: 512m jenkinsJavaOpts_Xmx: 512m jenkinsJavaOpts_MaxRAM: 2g events: enabled: false # operator: # resources: {} # exporter: # resources: {} # ruler: # enabled: false # replicas: 2 # resources: {} logging: enabled: false containerruntime: docker logsidecar: enabled: false replicas: 2 # resources: {} metrics_server: enabled: false monitoring: storageClass: "" # kube_rbac_proxy: # resources: {} # kube_state_metrics: # resources: {} # prometheus: # replicas: 1 # volumeSize: 20Gi # resources: {} # operator: # resources: {} # adapter: # resources: {} # node_exporter: # resources: {} # alertmanager: # replicas: 1 # resources: {} # notification_manager: # resources: {} # operator: # resources: {} # proxy: # resources: {} gpu: nvidia_dcgm_exporter: enabled: false # resources: {} multicluster: clusterRole: none network: networkpolicy: enabled: false ippool: type: none topology: type: none openpitrix: store: enabled: false servicemesh: enabled: false kubeedge: enabled: false cloudCore: nodeSelector: {"node-role.kubernetes.io/worker": ""} tolerations: [] cloudhubPort: "10000" cloudhubQuicPort: "10001" cloudhubHttpsPort: "10002" cloudstreamPort: "10003" tunnelPort: "10004" cloudHub: advertiseAddress: - "" nodeLimit: "100" service: cloudhubNodePort: "30000" cloudhubQuicNodePort: "30001" cloudhubHttpsNodePort: "30002" cloudstreamNodePort: "30003" tunnelNodePort: "30004" edgeWatcher: nodeSelector: {"node-role.kubernetes.io/worker": ""} tolerations: [] edgeWatcherAgent: nodeSelector: {"node-role.kubernetes.io/worker": ""} tolerations: [] root@cby:~#若是haproxy配置如下：frontend kube-apiserver bind *:6443 mode tcp option tcplog default_backend kube-apiserver backend kube-apiserver mode tcp option tcplog option tcp-check balance roundrobin default-server inter 10s downinter 5s rise 2 fall 2 slowstart 60s maxconn 250 maxqueue 256 weight 100 server kube-apiserver-1 192.168.1.10:6443 check server kube-apiserver-2 192.168.1.11:6443 check server kube-apiserver-3 192.168.1.12:6443 check 安装所需环境root@hello:~# bash -x 1.sh root@hello:~# cat 1.sh ssh root@192.168.1.10 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.11 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.12 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.13 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.14 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.15 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.16 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.51 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.52 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.53 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.54 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.55 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.56 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y" ssh root@192.168.1.57 "apt update && apt install sudo curl openssl ebtables socat ipset conntrack nfs-common -y"开始安装配置完成后，您可以执行以下命令来开始安装：root@hello:~# ./kk create cluster -f config-sample.yaml +---------+------+------+---------+----------+-------+-------+-----------+--------+------------+-------------+------------------+--------------+ | name | sudo | curl | openssl | ebtables | socat | ipset | conntrack | docker | nfs client | ceph client | glusterfs client | time | +---------+------+------+---------+----------+-------+-------+-----------+--------+------------+-------------+------------------+--------------+ | node3 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node1 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node4 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node8 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node11 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | master1 | y | y | y | y | y | y | y | | y | | | UTC 13:26:00 | | node5 | y | y | y | y | y | y | y | | y | | | UTC 13:26:00 | | master2 | y | y | y | y | y | y | y | | y | | | UTC 13:26:00 | | node2 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node7 | y | y | y | y | y | y | y | | y | | | UTC 13:26:00 | | master3 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node6 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node9 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | | node10 | y | y | y | y | y | y | y | | y | | | UTC 13:26:01 | +---------+------+------+---------+----------+-------+-------+-----------+--------+------------+-------------+------------------+--------------+ This is a simple check of your environment. Before installation, you should ensure that your machines meet all requirements specified at https://github.com/kubesphere/kubekey#requirements-and-recommendations Continue this installation? [yes/no]: yes INFO[13:26:06 UTC] Downloading Installation Files INFO[13:26:06 UTC] Downloading kubeadm ... ---略---验证安装运行以下命令查看安装日志。root@cby:~# kubectl logs -n kubesphere-system $(kubectl get pod -n kubesphere-system -l app=ks-install -o jsonpath='{.items[0].metadata.name}') -f ************************************************** Collecting installation results ... ##################################################### ### Welcome to KubeSphere! ### ##################################################### Console: http://192.168.1.10:30880 Account: admin Password: P@88w0rd NOTES： 1. After you log into the console, please check the monitoring status of service components in "Cluster Management". If any service is not ready, please wait patiently until all components are up and running. 2. Please change the default password after login. ##################################################### https://kubesphere.io 2021-11-10 10:24:00 ##################################################### root@hello:~# kubectl get node NAME STATUS ROLES AGE VERSION master1 Ready control-plane,master 30m v1.22.1 master2 Ready control-plane,master 29m v1.22.1 master3 Ready control-plane,master 29m v1.22.1 node1 Ready worker 29m v1.22.1 node10 Ready worker 29m v1.22.1 node11 Ready worker 29m v1.22.1 node2 Ready worker 29m v1.22.1 node3 Ready worker 29m v1.22.1 node4 Ready worker 29m v1.22.1 node5 Ready worker 29m v1.22.1 node6 Ready worker 29m v1.22.1 node7 Ready worker 30m v1.22.1 node8 Ready worker 30m v1.22.1 node9 Ready worker 29m v1.22.1在安装后启用插件使用 admin 用户登录控制台。点击左上角的平台管理，然后选择集群管理。点击 CRD，然后在搜索栏中输入 clusterconfiguration。点击搜索结果查看其详情页。在自定义资源中，点击 ks-installer 右侧的 ，然后选择编辑 YAML。apiVersion: installer.kubesphere.io/v1alpha1 kind: ClusterConfiguration metadata: annotations: kubectl.kubernetes.io/last-applied-configuration: > {"apiVersion":"installer.kubesphere.io/v1alpha1","kind":"ClusterConfiguration","metadata":{"annotations":{},"labels":{"version":"v3.2.0"},"name":"ks-installer","namespace":"kubesphere-system"},"spec":{"alerting":{"enabled":false},"auditing":{"enabled":false},"authentication":{"jwtSecret":""},"common":{"core":{"console":{"enableMultiLogin":true,"port":30880,"type":"NodePort"}},"es":{"basicAuth":{"enabled":false,"password":"","username":""},"elkPrefix":"logstash","externalElasticsearchPort":"","externalElasticsearchUrl":"","logMaxAge":7},"gpu":{"kinds":[{"default":true,"resourceName":"nvidia.com/gpu","resourceType":"GPU"}]},"minio":{"volumeSize":"20Gi"},"monitoring":{"GPUMonitoring":{"enabled":false},"endpoint":"http://prometheus-operated.kubesphere-monitoring-system.svc:9090"},"openldap":{"enabled":false,"volumeSize":"2Gi"},"redis":{"enabled":false,"volumeSize":"2Gi"}},"devops":{"enabled":false,"jenkinsJavaOpts_MaxRAM":"2g","jenkinsJavaOpts_Xms":"512m","jenkinsJavaOpts_Xmx":"512m","jenkinsMemoryLim":"2Gi","jenkinsMemoryReq":"1500Mi","jenkinsVolumeSize":"8Gi"},"etcd":{"endpointIps":"192.168.1.10,192.168.1.11,192.168.1.12","monitoring":false,"port":2379,"tlsEnable":true},"events":{"enabled":false},"kubeedge":{"cloudCore":{"cloudHub":{"advertiseAddress":[""],"nodeLimit":"100"},"cloudhubHttpsPort":"10002","cloudhubPort":"10000","cloudhubQuicPort":"10001","cloudstreamPort":"10003","nodeSelector":{"node-role.kubernetes.io/worker":""},"service":{"cloudhubHttpsNodePort":"30002","cloudhubNodePort":"30000","cloudhubQuicNodePort":"30001","cloudstreamNodePort":"30003","tunnelNodePort":"30004"},"tolerations":[],"tunnelPort":"10004"},"edgeWatcher":{"edgeWatcherAgent":{"nodeSelector":{"node-role.kubernetes.io/worker":""},"tolerations":[]},"nodeSelector":{"node-role.kubernetes.io/worker":""},"tolerations":[]},"enabled":false},"logging":{"containerruntime":"docker","enabled":false,"logsidecar":{"enabled":false,"replicas":2}},"metrics_server":{"enabled":false},"monitoring":{"gpu":{"nvidia_dcgm_exporter":{"enabled":false}},"storageClass":""},"multicluster":{"clusterRole":"none"},"network":{"ippool":{"type":"none"},"networkpolicy":{"enabled":false},"topology":{"type":"none"}},"openpitrix":{"store":{"enabled":false}},"persistence":{"storageClass":""},"servicemesh":{"enabled":false}}} labels: version: v3.2.0 name: ks-installer namespace: kubesphere-system spec: alerting: enabled: true auditing: enabled: true authentication: jwtSecret: '' common: core: console: enableMultiLogin: true port: 30880 type: NodePort es: basicAuth: enabled: true password: '' username: '' elkPrefix: logstash externalElasticsearchPort: '' externalElasticsearchUrl: '' logMaxAge: 7 gpu: kinds: - default: true resourceName: nvidia.com/gpu resourceType: GPU minio: volumeSize: 20Gi monitoring: GPUMonitoring: enabled: true endpoint: 'http://prometheus-operated.kubesphere-monitoring-system.svc:9090' openldap: enabled: true volumeSize: 2Gi redis: enabled: true volumeSize: 2Gi devops: enabled: true jenkinsJavaOpts_MaxRAM: 2g jenkinsJavaOpts_Xms: 512m jenkinsJavaOpts_Xmx: 512m jenkinsMemoryLim: 2Gi jenkinsMemoryReq: 1500Mi jenkinsVolumeSize: 8Gi etcd: endpointIps: '192.168.1.10,192.168.1.11,192.168.1.12' monitoring: false port: 2379 tlsEnable: true events: enabled: true kubeedge: cloudCore: cloudHub: advertiseAddress: - '' nodeLimit: '100' cloudhubHttpsPort: '10002' cloudhubPort: '10000' cloudhubQuicPort: '10001' cloudstreamPort: '10003' nodeSelector: node-role.kubernetes.io/worker: '' service: cloudhubHttpsNodePort: '30002' cloudhubNodePort: '30000' cloudhubQuicNodePort: '30001' cloudstreamNodePort: '30003' tunnelNodePort: '30004' tolerations: [] tunnelPort: '10004' edgeWatcher: edgeWatcherAgent: nodeSelector: node-role.kubernetes.io/worker: '' tolerations: [] nodeSelector: node-role.kubernetes.io/worker: '' tolerations: [] enabled: true logging: containerruntime: docker enabled: true logsidecar: enabled: true replicas: 2 metrics_server: enabled: true monitoring: gpu: nvidia_dcgm_exporter: enabled: true storageClass: '' multicluster: clusterRole: none network: ippool: type: weave-scope networkpolicy: enabled: true topology: type: none openpitrix: store: enabled: true persistence: storageClass: '' servicemesh: enabled: true批量将所有服务器设置阿里云加速root@hello:~# vim 8 root@hello:~# cat 8 sudo mkdir -p /etc/docker sudo tee /etc/docker/daemon.json <<-'EOF' { "registry-mirrors": ["https://ted9wxpi.mirror.aliyuncs.com"] } EOF sudo systemctl daemon-reload sudo systemctl restart docker root@hello:~# vim 7 root@hello:~# cat 7 scp 8 root@192.168.1.11: scp 8 root@192.168.1.12: scp 8 root@192.168.1.13: scp 8 root@192.168.1.14: scp 8 root@192.168.1.15: scp 8 root@192.168.1.16: scp 8 root@192.168.1.51: scp 8 root@192.168.1.52: scp 8 root@192.168.1.53: scp 8 root@192.168.1.54: scp 8 root@192.168.1.55: scp 8 root@192.168.1.56: scp 8 root@192.168.1.57: root@hello:~# bash -x 7 root@hello:~# vim 6 root@hello:~# cat 6 ssh root@192.168.1.10 "bash -x 8" ssh root@192.168.1.11 "bash -x 8" ssh root@192.168.1.12 "bash -x 8" ssh root@192.168.1.13 "bash -x 8" ssh root@192.168.1.14 "bash -x 8" ssh root@192.168.1.15 "bash -x 8" ssh root@192.168.1.16 "bash -x 8" ssh root@192.168.1.51 "bash -x 8" ssh root@192.168.1.52 "bash -x 8" ssh root@192.168.1.53 "bash -x 8" ssh root@192.168.1.54 "bash -x 8" ssh root@192.168.1.55 "bash -x 8" ssh root@192.168.1.56 "bash -x 8" ssh root@192.168.1.57 "bash -x 8" root@hello:~# bash -x 6查看node节点root@hello:~# kubectl get node NAME STATUS ROLES AGE VERSION master1 Ready control-plane,master 11h v1.22.1 master2 Ready control-plane,master 11h v1.22.1 master3 Ready control-plane,master 11h v1.22.1 node1 Ready worker 11h v1.22.1 node10 Ready worker 11h v1.22.1 node11 Ready worker 11h v1.22.1 node2 Ready worker 11h v1.22.1 node3 Ready worker 11h v1.22.1 node4 Ready worker 11h v1.22.1 node5 Ready worker 11h v1.22.1 node6 Ready worker 11h v1.22.1 node7 Ready worker 11h v1.22.1 node8 Ready worker 11h v1.22.1 node9 Ready worker 11h v1.22.1 root@hello:~# root@hello:~#Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。51篇原创内容公众号 https://blog.csdn.net/qq_33921750https://my.oschina.net/u/3981543https://www.zhihu.com/people/chen-bu-yun-2https://segmentfault.com/u/hppyvyv6/articleshttps://juejin.cn/user/3315782802482007https://space.bilibili.com/352476552/articlehttps://cloud.tencent.com/developer/column/93230知乎、CSDN、开源中国、思否、掘金、哔哩哔哩、腾讯云本文使用 文章同步助手 同步