如何部署Ubuntu20.04 + k8s 1.21.0开发环境

发布时间:2021-12-18 11:51:35 作者:小新
来源:亿速云 阅读:420

这篇文章主要为大家展示了“如何部署Ubuntu20.04 + k8s 1.21.0开发环境”,内容简而易懂,条理清晰,希望能够帮助大家解决疑惑,下面让小编带领大家一起研究并学习一下“如何部署Ubuntu20.04 + k8s 1.21.0开发环境”这篇文章吧。

Kubeflow 部署(使用 kfctl_k8s_istio)

安装 Kubeflow的一些指南(使用 kfctl_k8s_istio 配置部署到已有的Kubernetes集群中)。该配置清单创建Kubeflow的核心部件部署,但不包括外部依赖,可以根据您的环境需要进行优化。KubeFlow 1.2.0部署到Ubuntu20.04和k8s 1.21.0,其它平台可能有些变化。

该Kubeflow deployment要求 StorageClass 支持 dynamic volume provisioner。确认缺省的StorageClass的 provisioner 域的设置。如果换没有 provisioner, 确保配置了 volume provisioning,按照下面的描述在 Kubernetes cluster 进行设置(参考 below)。

使用 kfctl_k8s_istio.v1.2.0.yaml 配置安装,需要考虑下面的选项:

准备环境

下载 kfctl 的 Kubeflow CLI 工具,然后手动设置环境变量:

wget https://github.com/kubeflow/kfctl/releases/download/v1.2.0/kfctl_v1.2.0-0-gbc038f9_linux.tar.gz

tar -vxf kfctl_v1.2.0-0-gbc038f9_linux.tar.gz

sudo cp kfctl /usr/bin/
# The following command is optional. It adds the kfctl binary to your path.# If you don't add kfctl to your path, you must use the full path# each time you run kfctl.# Use only alphanumeric characters or - in the directory name.export PATH=$PATH:"<path-to-kfctl>"##实际如下:##export PATH=$PATH:"/home/supermap/openthings/kubeflow"# Set KF_NAME to the name of your Kubeflow deployment. You also use this# value as directory name when creating your configuration directory.# For example, your deployment name can be 'my-kubeflow' or 'kf-test'.export KF_NAME=<your choice of name for the Kubeflow deployment>##实际如下:##export KF_NAME="kubeflow"# Set the path to the base directory where you want to store one or more # Kubeflow deployments. For example, /opt/.# Then set the Kubeflow application directory for this deployment.export BASE_DIR=<path to a base directory>export KF_DIR=${BASE_DIR}/${KF_NAME}##实际如下:##export BASE_DIR="/home/supermap/openthings/"##export KF_DIR=${BASE_DIR}/${KF_NAME}# Set the configuration file to use when deploying Kubeflow.# The following configuration installs Istio by default. Comment out # the Istio components in the config file to skip Istio installation. # See https://github.com/kubeflow/kubeflow/pull/3663export CONFIG_URI="https://raw.githubusercontent.com/kubeflow/manifests/v1.2-branch/kfdef/kfctl_k8s_istio.v1.2.0.yaml"##实际如下:##export CONFIG_URI=${BASE_DIR}/${KF_NAME}/kfctl_k8s_istio.v1.2.0.yaml

注意:

⚠️注意:

  repos:
  - name: manifests
    uri: /home/supermap/openthings/kubeflow/v1.2.0.tar.gz
  version: v1.2-branch

设置和部署 Kubeflow

使用缺省设置来设置和部署 Kubeflow using the default settings,运行 kfctl apply 如下:

mkdir -p ${KF_DIR}
cd ${KF_DIR}
kfctl apply -V -f ${CONFIG_URI}

检查 resources deployed in namespace kubeflow:

kubectl -n kubeflow get all

可选,设置以后部署的配置参数:

在部署 Kubeflow时,如果需要定制安装参数,可以编辑该配置文件,然后运行 Kubeflow的部署命令即可:

  1. 运行 kfctl build 命令设置安装参数:

    mkdir -p ${KF_DIR}
    cd ${KF_DIR}
    kfctl build -V -f ${CONFIG_URI}


  2. 编辑配置文件,描述如上 customizing your Kubeflow deployment。

  3. 设置环境变量指向本地的配置文件:

    export CONFIG_FILE=${KF_DIR}/kfctl_k8s_istio.v1.2.0.yaml


  4. 运行 kfctl apply 目录实施 Kubeflow 部署:

    kfctl apply -V -f ${CONFIG_FILE}


出现错误:

2021/04/28 10:24:44 absolute path error in '/home/supermap/openthings/kubeflow/.cache/manifests/namespaces/base' : evalsymlink failure on '/home/supermap/openthings/kubeflow/.cache/manifests/namespaces/base' : lstat /home/supermap/openthings/kubeflow/.cache/manifests/namespaces: no such file or directory
ERRO[0000] Error evaluating kustomization manifest for namespaces: accumulating resources: accumulating resources from '../../.cache/manifests/namespaces/base': open /home/supermap/openthings/kubeflow/.cache/manifests/namespaces/base: no such file or directory  filename="kustomize/kustomize.go:155"
Error: failed to apply:  (kubeflow.error): Code 500 with message: kfApp Apply failed for kustomize:  (kubeflow.error): Code 500 with message: error evaluating kustomization manifest for namespaces: accumulating resources: accumulating resources from '../../.cache/manifests/namespaces/base': open /home/supermap/openthings/kubeflow/.cache/manifests/namespaces/base: no such file or directory
cd manifests-1.2.0
mv -r * ../
apiVersion: kfdef.apps.kubeflow.org/v1
kind: KfDef
metadata:
  creationTimestamp: null
  namespace: kubeflow
spec:
  applications:
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/namespaces/base
    name: namespaces
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/application/v3
    name: application
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/istio-1-3-1-stack
    name: istio-stack
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/cluster-local-gateway-1-3-1
    name: cluster-local-gateway
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/istio/istio/base
    name: istio
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/cert-manager-crds
    name: cert-manager-crds
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/cert-manager-kube-system-resources
    name: cert-manager-kube-system-resources
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/add-anonymous-user-filter
    name: add-anonymous-user-filter
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/metacontroller/base
    name: metacontroller
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/admission-webhook/bootstrap/overlays/application
    name: bootstrap
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/spark-operator
    name: spark-operator
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes
    name: kubeflow-apps
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/knative/installs/generic
    name: knative
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/kfserving/installs/generic
    name: kfserving
  - kustomizeConfig:
      repoRef:
        name: manifests
        path: manifests-1.2.0/stacks/kubernetes/application/spartakus
    name: spartakus
  repos:
  - name: manifests
    uri: /home/supermap/openthings/kubeflow/v1.2.0.tar.gz
  version: v1.2-branch
status: {}

KubeFlow的镜像较多,完全启动需要比较长的时间,需要耐心等待。

过段时间看,有些pod已经启动起来了,主界面已经可以访问了。

查看状态,有些镜像和服务有问题,包括镜像下载、存储卷设置等,留待后续解决。

(base) supermap@xriver02:~$ kubectl get pod -n kubeflow
NAME                                                     READY   STATUS             RESTARTS   AGE
admission-webhook-bootstrap-stateful-set-0               0/1     ImagePullBackOff   0          36h
admission-webhook-deployment-5cd7dc96f5-l9rxl            1/1     Running            0          36h
application-controller-stateful-set-0                    0/1     ImagePullBackOff   0          36h
argo-ui-657cf69ff5-kn966                                 1/1     Running            0          36h
cache-deployer-deployment-5f4979f45-q6psq                1/2     ImagePullBackOff   0          36h
cache-server-7859fd67f5-kx8zm                            0/2     Init:0/1           0          36h
centraldashboard-86744cbb7b-44rbc                        1/1     Running            0          36h
jupyter-web-app-deployment-8486d5ffff-9czzl              1/1     Running            0          36h
katib-controller-7fcc95676b-tsbzx                        1/1     Running            1          36h
katib-db-manager-67867f5498-jzrgh                        0/1     Running            442        36h
katib-mysql-6b5d848bf5-gs95h                             0/1     Pending            0          36h
katib-ui-65dc4cf6f5-pqj5p                                1/1     Running            0          36h
kfserving-controller-manager-0                           1/2     ImagePullBackOff   0          36h
kubeflow-pipelines-profile-controller-797fb44db9-vznlv   1/1     Running            0          36h
metacontroller-0                                         1/1     Running            0          36h
metadata-db-c65f4bc75-m2ggv                              0/1     Pending            0          36h
metadata-envoy-deployment-67bd5954c-jl7pn                1/1     Running            0          36h
metadata-grpc-deployment-577c67c96f-29dwx                0/1     CrashLoopBackOff   433        36h
metadata-writer-756dbdd478-tlrpw                         2/2     Running            325        36h
minio-54d995c97b-jrmqq                                   0/1     Pending            0          36h
ml-pipeline-8d6749d9c-drv2h                              1/2     CrashLoopBackOff   662        36h
ml-pipeline-persistenceagent-d984c9585-mhstn             2/2     Running            0          36h
ml-pipeline-scheduledworkflow-5ccf4c9fcc-wqg4d           2/2     Running            0          36h
ml-pipeline-ui-8ccbf585c-77krb                           2/2     Running            0          36h
ml-pipeline-viewer-crd-56c68f6c85-bssgc                  1/2     ImagePullBackOff   0          36h
ml-pipeline-visualizationserver-7446b96877-ffs7b         2/2     Running            0          36h
mpi-operator-d5bfb8489-75m6b                             1/1     Running            0          36h
mxnet-operator-7576d697d6-jwks8                          1/1     Running            0          36h
mysql-74f8f99bc8-ndzqg                                   0/2     Pending            0          36h
notebook-controller-deployment-dd4c74b47-k9fng           0/1     ImagePullBackOff   0          36h
profiles-deployment-65f54cb5c4-9xtws                     0/2     ImagePullBackOff   0          36h
pytorch-operator-847c8d55d8-x6l4t                        0/1     ImagePullBackOff   0          36h
seldon-controller-manager-6bf8b45656-d7rvf               1/1     Running            0          36h
spark-operatorsparkoperator-fdfbfd99-cst9l               0/1     ImagePullBackOff   0          36h
spartakus-volunteer-558f8bfd47-tcvpn                     1/1     Running            0          36h
tf-job-operator-58477797f8-wr79t                         1/1     Running            0          36h
workflow-controller-64fd7cffc5-m6gkc                     1/1     Running            0          36h

访问 Kubeflow 用户界面 (UI)

Kubeflow 部署完成后,Kubeflow Dashboard 的访问通过服务 istio-ingressgateway 来获取。loadbalancer在环境中不可用,NodePort 或 Port forwarding 可以用于访问 Kubeflow Dashboard,参考 Ingress Gateway guide 或者:

删除 Kubeflow

运行下面的命令删除部署并回收资源:

cd ${KF_DIR}# If you want to delete all the resources, run:kfctl delete -f ${CONFIG_FILE}

理解部署过程

 kfctl 部署过程包含下面几个命令:

应用的布局

您的 Kubeflow 应用目录 ${KF_DIR} 包含下面的文件和目录:

建议将${KF_DIR} 目录中的内容纳入版本管理系统。

Provisioning of Persistent Volumes in Kubernetes

如果已经有 dynamic volume provisioner,可以跳过本步骤

问题解决

Persistent Volume Claims 处于 Pending 状态

检查PersistentVolumeClaims 是否 Bound 到 PersistentVolumes,如下:

kubectl -n kubeflow get pvc

如果PersistentVolumeClaims (PVCs) 在 Pending 状态,部署后没有bound 到 PersistentVolumes (PVs),就需要手动为每一个PVC创建PV,或者安装 dynamic volume provisioning 来按需创建PVs ,以及删除存在的PVCs然后重新部署 Kubeflow。

以上是“如何部署Ubuntu20.04 + k8s 1.21.0开发环境”这篇文章的所有内容,感谢各位的阅读!相信大家都有了一定的了解,希望分享的内容对大家有所帮助,如果还想学习更多知识,欢迎关注亿速云行业资讯频道!

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