做静态页面的网站,深圳门户网站开发,大淘客网站建设app,东莞网络公司名字前言#xff1a;纯个人记录使用。
搭建 Zero to JupyterHub with Kubernetes 上篇 - Kubernetes 离线二进制部署。搭建 Zero to JupyterHub with Kubernetes 中篇 - Kubernetes 常规使用记录。搭建 Zero to JupyterHub with Kubernetes 下篇 - Jupyterhub on k8s。
官方文档…前言纯个人记录使用。
搭建 Zero to JupyterHub with Kubernetes 上篇 - Kubernetes 离线二进制部署。搭建 Zero to JupyterHub with Kubernetes 中篇 - Kubernetes 常规使用记录。搭建 Zero to JupyterHub with Kubernetes 下篇 - Jupyterhub on k8s。
官方文档Zero to JupyterHub with Kubernetes
**版本对应**This documentation is for Helm chart version 2.0.0 that deploys JupyterHub version 3.0.0 and other components versioned in hub/images/requirements.txt. The Helm chart requires Kubernetes version 1.20.0 and Helm 3.5
组件版本kubernetesv1.20.4jupyterhub-chart2.0.0helmv3.12.3 文章目录 第一部分: Setup Kubernetes1、Setup Kubernetes2、Setting up helm 第二部分: Setup JupyterHub1、Installing JupyterHub1.1 下载所需jupyterhub chart版本1.2 下载相关离线镜像1.3 加载镜像1.4 jupyterhub 配置1.4.1 预先配置pv与pvc1.5 启动jupyterhub1.6 jupyterhub 服务验证 第一部分: Setup Kubernetes
1、Setup Kubernetes
kubernetes-v1.20.4 离线二进制部署
[rootk8s-master /data/s0/kubernetes]$ kubectl version --short
Client Version: v1.20.4
Server Version: v1.20.42、Setting up helm
通过百度网盘分享的文件helm-v3.12.3-linux-amd64.tar.gz 链接https://pan.baidu.com/s/1f8xONKHWshHxieu7jEN4yA 提取码1234
# 解压安装
[rootk8s-master /data/s0/kubernetes/helm]$ tar -xzvf helm-v3.12.3-linux-amd64.tar.gz
[rootk8s-master /data/s0/kubernetes/helm]$ ln -s /data/s0/kubernetes/helm/linux-amd64/helm /usr/local/bin
# 验证
[rootk8s-master /data/s0/kubernetes/helm]$ helm version
version.BuildInfo{Version:v3.12.3, GitCommit:3a31588ad33fe3b89af5a2a54ee1d25bfe6eaa5e, GitTreeState:clean, GoVersion:go1.20.7}第二部分: Setup JupyterHub
1、Installing JupyterHub
1.1 下载所需jupyterhub chart版本
JupyterHub’s Helm chart 仓库 -- jupyterhub-2.0.0.tgz
通过百度网盘分享的文件jupyterhub-2.0.0.tgz 链接https://pan.baidu.com/s/1ZrEHC9al29ye7n0W3UAi3g 提取码1234
1.2 下载相关离线镜像
# 解压安装
[rootk8s-master /data/s0/kubernetes/helm]$ tar -xzvf jupyterhub-2.0.0.tgz # jupyterhub chart
# 查看所需镜像
[rootk8s-master /data/s0/kubernetes/helm]$ cat jupyterhub/Chart.yaml
annotations:artifacthub.io/images: |- image: jupyterhub/configurable-http-proxy:4.5.3name: configurable-http-proxy- image: jupyterhub/k8s-hub:2.0.0name: k8s-hub- image: jupyterhub/k8s-image-awaiter:2.0.0name: k8s-image-awaiter- image: jupyterhub/k8s-network-tools:2.0.0name: k8s-network-tools- image: jupyterhub/k8s-secret-sync:2.0.0name: k8s-secret-sync- image: jupyterhub/k8s-singleuser-sample:2.0.0name: k8s-singleuser-sample- image: k8s.gcr.io/kube-scheduler:v1.23.10 # helm upgrate 启动部署时此版本有问题改为v1.20.15注意values.yaml中镜像名称修改镜像保持一致name: kube-scheduler- image: k8s.gcr.io/pause:3.8 # 部署k8s时已下载安装注意values.yaml中镜像名称修改保持一致name: pause- image: k8s.gcr.io/pause:3.8name: pausd- image: traefik:v2.8.4name: traefik# 联网保存本地镜像
# 1. 下载保存 jupyterhub/configurable-http-proxy:4.5.3docker pull quay.io/jupyterhub/configurable-http-proxy:4.5.3docker tag quay.io/jupyterhub/configurable-http-proxy:4.5.3 jupyterhub/configurable-http-proxy:4.5.3docker save -o configurable-http-proxy:4.5.3.tar jupyterhub/configurable-http-proxy:4.5.3 # 2. 下载保存 jupyterhub/k8s-hub:2.0.0docker pull quay.io/jupyterhub/k8s-hub:2.0.0docker tag quay.io/jupyterhub/k8s-hub:2.0.0 jupyterhub/k8s-hub:2.0.0docker save -o k8s-hub:2.0.0.tar jupyterhub/k8s-hub:2.0.0# 3. 下载保存 jupyterhub/k8s-image-awaiter:2.0.0docker pull quay.io/jupyterhub/k8s-image-awaiter:2.0.0docker tag quay.io/jupyterhub/k8s-image-awaiter:2.0.0 jupyterhub/k8s-image-awaiter:2.0.0 docker save -o k8s-image-awaiter:2.0.0.tar jupyterhub/k8s-image-awaiter:2.0.0
# 4. 下载保存 jupyterhub/k8s-network-tools:2.0.0docker pull quay.io/jupyterhub/k8s-network-tools:2.0.0docker tag quay.io/jupyterhub/k8s-network-tools:2.0.0 jupyterhub/k8s-network-tools:2.0.0docker save -o k8s-network-tools:2.0.0.tar jupyterhub/k8s-network-tools:2.0.0# 5. 下载保存 jupyterhub/k8s-secret-sync:2.0.0docker pull quay.io/jupyterhub/k8s-secret-sync:2.0.0docker tag quay.io/jupyterhub/k8s-secret-sync:2.0.0 jupyterhub/k8s-secret-sync:2.0.0docker save -o k8s-secret-sync:2.0.0.tar jupyterhub/k8s-secret-sync:2.0.0# 6. 下载保存 jupyterhub/k8s-singleuser-sample:2.0.0docker pull m.daocloud.io/docker.io/jupyterhub/k8s-singleuser-sample:2.0.0docker tag m.daocloud.io/docker.io/jupyterhub/k8s-singleuser-sample:2.0.0 jupyterhub/k8s-singleuser-sample:2.0.0docker save -o k8s-singleuser-sample:2.0.0.tar jupyterhub/k8s-singleuser-sample:2.0.0# 7. 下载保存 k8s.gcr.io/kube-scheduler:v1.20.15docker pull k8s-gcr.m.daocloud.io/kube-scheduler:v1.20.15docker tag k8s-gcr.m.daocloud.io/kube-scheduler:v1.20.15 k8s.gcr.io/kube-scheduler:v1.20.15docker save -o kube-scheduler:v1.20.15.tar k8s.gcr.io/kube-scheduler:v1.20.15# 8. 下载保存 traefik:v2.8.4docker pull m.daocloud.io/docker.io/library/traefik:v2.8.4docker tag m.daocloud.io/docker.io/library/traefik:v2.8.4 traefik:v2.8.4docker save -o traefik:v2.8.4.tar traefik:v2.8.4## 9. 将离线镜像打包上传tar -czvf jupyterhub-chart-images.tgz ./*scp jupyterhub-chart-images.tgz k8s-master:/data/s0/kubernetes/helm1.3 加载镜像
# ------------------ k8s-matserk8s-node1、k8s-node2 ----------------------------
# 1. 加载镜像node1、node2节点同理
[rootk8s-master /data/s0/kubernetes/helm]$ tar -xzvf jupyterhub-chart-images.tgz -C ./chart-images
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i configurable-http-proxy:4.5.3.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i k8s-hub:2.0.0.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i k8s-image-awaiter:2.0.0.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i k8s-network-tools:2.0.0.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i k8s-secret-sync:2.0.0.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i k8s-singleuser-sample:2.0.0.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i kube-scheduler:v1.20.15.tar
[rootk8s-master /data/s0/kubernetes/helm/chart-images]$ docker load -i traefik:v2.8.4.tar# 2.加载自定义用户科学环境默认的单用户服务器jupyter镜像 k8s-singleuser-sample
# docker pull m.daocloud.io/docker.io/jupyter/datascience-notebook 默认拉取最新版本,最好指定版本否则每次拉最新的
[rootk8s-master /data/s0/kubernetes/helm]$ docker load -i datascience-notebook.tar
# 注意k8s在不指定镜像拉取策略imagePullPolicy的情况下如果镜像标签taglatestimagePullPolicy默认值为“Always” 总是从镜像库拉取
# 如果镜像标签tag不是latestimagePullPolicy默认值为“IfNotPresent” 本地有使用本地镜像本地没有则拉取镜像库
[rootk8s-master /data/s0/kubernetes/helm]$ docker tag jupyter/datascience-notebook:latest jupyter/datascience-notebook:2023.10.231.4 jupyterhub 配置
# jupyterhub 自定义配置
[rootdatanode40 /data/s0/kubernetes/helm]$ touch config.yaml
[rootdatanode40 /data/s0/kubernetes/helm]$ vim config.yamlconfig.yaml 内容如下
# 应用名称deployment、service、pod等资源对象名称
fullnameOverride: jupyterhub# 拉取镜像时相关仓库身份认证使用本机离线镜像
imagePullSecret:create: falseautomaticReferenceInjection: false# hub服务pod配置(auth权限认证)
hub:revisionHistoryLimit: 1 # Kubernetes 中保留的历史版本数量config: # jupyterhub_cnfig.py 配置文件内容JupyterHub:admin_access: trueadmin_users: - zyp # 设置管理员用户authenticator_class: dummy # 用户验证测试采用虚拟验证service:type: ClusterIP ports:nodePort:db:type: sqlite-pvc # JupyterHub 使用数据库,存储用户信息、服务器状态、活动记录等数据pvc: # 需要预先创建对应pvaccessModes:- ReadWriteOncestorage: 2GisubPath: sqlite # PV存储卷子路径默认根路径storageClassName: sqlite-pv # 存储类别image:name: jupyterhub/k8s-hubtag: 2.0.0pullPolicy: IfNotPresent#设置 chp(configurable-http-proxy)pod的代理、公网代理、https代理相关
proxy:service:type: NodePort # 公网代理服务 nodePorts:http: 30081chp: # configurable-http-proxy (chp)配置revisionHistoryLimit: 1image:name: jupyterhub/configurable-http-proxytag: 4.5.3 pullPolicy: IfNotPresenthttps:enabled: false # 禁用https # 单用户jupyter服务器
singleuser:networkTools:image:name: jupyterhub/k8s-network-toolstag: 2.0.0pullPolicy: IfNotPresentstorage: # 配置单用户环境存储type: static # 静态挂载方式static:pvcName: notebook-pvc # 存储pvc名称需手动创建pvc和pvsubPath: {username}capacity: 10GihomeMountPath: /home/jovyan # 容器中挂载主文件夹存储的位置 # Defines the default image image:name: jupyterhub/k8s-singleuser-sample # 可修改为自己的科学计算环境tag: 2.0.0pullPolicy: IfNotPresent profileList: # 用户科学环境选择- display_name: sample environmentdescription: To avoid too much bells and whistles: Python.default: true- display_name: Datascience environmentdescription: If you want the additional bells and whistles: Python, R, and Julia.kubespawner_override:image: jupyter/datascience-notebook:2023.10.23pullPolicy: IfNotPresentstartTimeout: 300cpu:limit:guarantee: 0.5memory:limit:guarantee: 1Gcmd: jupyterhub-singleuser # 容器内启动单用户服务器的命令defaultUrl: /lab # 用户jupyter界面extraEnv:JUPYTERHUB_SINGLEUSER_APP: jupyter_server.serverapp.ServerApp # k8s 容器调度相关
scheduling:userScheduler:revisionHistoryLimit: 1image:name: k8s.gcr.io/kube-schedulertag: v1.20.15 pullPolicy: IfNotPresentuserPlaceholder:image:name: k8s.gcr.io/pausetag: 3.8pullPolicy: IfNotPresent# 镜像拉取器
prePuller: hook:enabled: false # 离线环境本地镜像无需拉取pullOnlyOnChanges: falsecontinuous:enabled: falsepullProfileListImages: false# 空闲进程杀死服务
cull:enabled: trueusers: false # --cull-usersadminUsers: true # --cull-admin-usersremoveNamedServers: false # --remove-named-serverstimeout: 3600 # --timeoutevery: 600 # --cull-everyconcurrency: 10 # --concurrencymaxAge: 0 # --max-age1.4.1 预先配置pv与pvc
pv 持久化参见 Kubernetes 常规使用记录。
# 配置sqlite存储的PV 和 单用户服务器存储的pv和PVC
[rootk8s-node1 /data/s0/kubernetes/nfs]$ mkdir pvs
[rootk8s-node1 /data/s0/kubernetes/nfs/pvs]$ vim pvs.yaml# sqlite存储的PV
apiVersion: v1
kind: PersistentVolume
metadata:name: sqlite-pv1
spec:nfs: path: /data/s0/kubernetes/nfs/pv1readOnly: false server: k8s-node1capacity: storage: 2GiaccessModes: - ReadWriteOncestorageClassName: sqlite-pv persistentVolumeReclaimPolicy: Retain
---
# 单用户服务器pv
apiVersion: v1
kind: PersistentVolume
metadata:name: notebook-pv2
spec:nfs: path: /data/s0/kubernetes/nfs/pv2readOnly: false server: k8s-node1capacity: storage: 200GiaccessModes: - ReadWriteMany storageClassName: single-notebook persistentVolumeReclaimPolicy: Retain
---
# 单用户服务器pvc
apiVersion: v1
kind: PersistentVolumeClaim
metadata:name: notebook-pvc # 与配置文件对应 namespace: jhub
spec:accessModes:- ReadWriteManystorageClassName: single-notebook resources: requests:storage: 20Gi1.5 启动jupyterhub
# 创建命名空间
[rootk8s-master /data/s0/kubernetes/helm]$ kubectl create ns jhub
# 启动预设pvc和pv
[rootk8s-node1 /data/s0/kubernetes/nfs/pvs]$ kubectl apply -f pvs.yaml
# 启动jupyterhub
[rootk8s-master /data/s0/kubernetes/helm]$ helm upgrade --cleanup-on-fail \--install jupyterhub-release ./jupyterhub \--namespace jhub \--values config.yaml# 验证pod运行状态若存在pod 状态 Pending or ContainerCreating --》 kubectl --namespacejhub describe pod name of pod
[rootk8s-master /data/s0/kubernetes/helm]$ kubectl --namespacejhub get pod
jupyterhub-hub-c87985f75-lkl4f 1/1 Running 0 5m18s
jupyterhub-proxy-5d95bb6786-87cqs 1/1 Running 0 5m18s
jupyterhub-user-scheduler-786c6759c7-2r24k 1/1 Running 0 5m18s
jupyterhub-user-scheduler-786c6759c7-6x5k6 1/1 Running 0 5m18s# 验证是否为k8s服务jupyterhub-proxy-public提供了外部IP
[rootk8s-master /data/s0/kubernetes/helm]$ kubectl --namespacejhub get svc
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
jupyterhub-hub ClusterIP 10.0.0.50 none 8081/TCP 90s
jupyterhub-proxy-api ClusterIP 10.0.0.196 none 8001/TCP 90s
jupyterhub-proxy-public NodePort 10.0.0.51 none 80:30081/TCP 90s
问题Error: rendered manifests contain a resource that already exists. Unable to continue with install: ClusterRole “jupyterhub-user-scheduler” in namespace “” exists and cannot be imported into the current release: invalid ownership metadata; annotation validation error: key “meta.helm.sh/release-name” must equal “jupyterhub-release”: current value is “jupyterhub-v1”
解决
kubectl delete clusterrole jupyterhub-user-scheduler
kubectl delete clusterrolebinding jupyterhub-user-scheduler
1.6 jupyterhub 服务验证
远程主机登录 http://k8s-matser:80081 用户登录界面 科学计算环境选择界面 用户分析操作界面 底层单用户容器 持久化存储查看 k8s管理界面查看
