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从零到一：基于 K3s 快速搭建本地化 kubeflow AI 机器学习平台
作者：从前慢现在也慢 | 2024-04-04 10:16:30
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从零到一：基于 K3s 快速搭建本地化 kubeflow AI 机器学习平台
背景
Kubeflow 是一种开源的 Kubernetes 原生框架，可用于开发、管理和运行机器学习工作负载，支持诸如 PyTorch、TensorFlow 等众多优秀的机器学习框架，本文介绍如何在 Mac 上搭建本地化的 kubeflow 机器学习平台。
注意：本文以 deyloyKF 发行版作为主要安装对象，本地环境仅适用于开发测试使用，不可用于生产环境！
更多 kubeflow 发行版参考官网介绍：https://www.kubeflow.org/docs/started/installing-kubeflow/
基本环境：
OS：macos 13.1 (amd64)
DockerDesktop：v4.15.0
尽管 K3s 自身需要的资源不多，但是 kubeflow 套件组件众多，需要设置 Docker 的资源分配，避免安装过程中发生 Pod Pending.
Docker 资源建议设置：CPU 8 核，Memory 10G，磁盘 40G
安装部署步骤
1. 安装依赖的 CLI
brew install bash argocd jq k3d kubectl kustomize
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2. 创建 Kubernetes 集群
为了尽可能降低资源消耗，这里使用 K3s 运行本地集群：
k3d cluster create "kubeflow" --image "rancher/k3s:v1.27.10-k3s2"
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通过如下命令检查集群是否就绪：
kubectl get -A pods
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正常的输出结果类似如下这样：
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system local-path-provisioner-957fdf8bc-cj9l5 1/1 Running 0 2m30s
kube-system coredns-77ccd57875-xzzz4 1/1 Running 0 2m30s
kube-system metrics-server-648b5df564-gwnhq 1/1 Running 0 2m30s
kube-system helm-install-traefik-crd-49l4k 0/1 Completed 0 2m31s
kube-system helm-install-traefik-xrjtd 0/1 Completed 2 2m31s
kube-system svclb-traefik-a79cf0ef-lj4td 2/2 Running 0 89s
kube-system traefik-768bdcdcdd-mr8z8 1/1 Running 0 89s
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3. 部署 ArgoCD
ArgoCD 是工作流编排工具，可以帮助我们实现 Kubeflow 的自动化部署
git clone -b main https://github.com/deployKF/deployKF.git
cd deployKF/argocd-plugin
chmod +x ./install_argocd.sh
bash ./install_argocd.sh
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通过如下命令检查 ArgoCD 是否就绪：
kubectl get pod -n argocd
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正常的输出结果类似如下这样：
NAME READY STATUS RESTARTS AGE
argocd-redis-69f8795dbd-7v4nn 1/1 Running 0 106s
argocd-applicationset-controller-7b9c4dfb77-7gsf2 1/1 Running 0 106s
argocd-notifications-controller-756764ddd5-jw92c 1/1 Running 0 106s
argocd-server-86f64667bc-7nt7d 1/1 Running 0 105s
argocd-application-controller-0 1/1 Running 0 105s
argocd-dex-server-9b5c6dccd-2p779 1/1 Running 0 106s
argocd-repo-server-5b55578f7c-sfzf4 2/2 Running 0 105s
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4. 安装 kubeflow 套件
准备如下文件：deploykf-app-of-apps.yaml
apiVersion: argoproj.io/v1alpha1 kind: Application metadata: name: deploykf-app-of-apps namespace: argocd labels: app.kubernetes.io/name: deploykf-app-of-apps app.kubernetes.io/part-of: deploykf spec: project: "default" source: ## source git repo configuration ## - we use the 'deploykf/deploykf' repo so we can read its 'sample-values.yaml' ## file, but you may use any repo (even one with no files) ## repoURL: "https://github.com/deployKF/deployKF.git" targetRevision: "v0.1.4" path: "." ## plugin configuration ## plugin: name: "deploykf" parameters: ## the deployKF generator version ## - available versions: https://github.com/deployKF/deployKF/releases ## - name: "source_version" string: "0.1.4" ## paths to values files within the `repoURL` repository ## - the values in these files are merged, with later files taking precedence ## - we strongly recommend using 'sample-values.yaml' as the base of your values ## so you can easily upgrade to newer versions of deployKF ## - name: "values_files" array: - "./sample-values.yaml" ## a string containing the contents of a values file ## - this parameter allows defining values without needing to create a file in the repo ## - these values are merged with higher precedence than those defined in `values_files` ## - name: "values" string: | ## ## This demonstrates how you might structure overrides for the 'sample-values.yaml' file. ## For a more comprehensive example, see the 'sample-values-overrides.yaml' in the main repo. ## ## Notes: ## - YAML maps are RECURSIVELY merged across values files ## - YAML lists are REPLACED in their entirety across values files ## - Do NOT include empty/null sections, as this will remove ALL values from that section. ## To include a section without overriding any values, set it to an empty map: `{}` ## ## -------------------------------------------------------------------------------- ## argocd ## -------------------------------------------------------------------------------- argocd: namespace: argocd project: default ## -------------------------------------------------------------------------------- ## kubernetes ## -------------------------------------------------------------------------------- kubernetes: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------------------------------------------------- ## deploykf-dependencies ## -------------------------------------------------------------------------------- deploykf_dependencies: ## -------------------------------------- ## cert-manager ## -------------------------------------- cert_manager: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## istio ## -------------------------------------- istio: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## kyverno ## -------------------------------------- kyverno: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------------------------------------------------- ## deploykf-core ## -------------------------------------------------------------------------------- deploykf_core: ## -------------------------------------- ## deploykf-auth ## -------------------------------------- deploykf_auth: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## deploykf-istio-gateway ## -------------------------------------- deploykf_istio_gateway: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## deploykf-profiles-generator ## -------------------------------------- deploykf_profiles_generator: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------------------------------------------------- ## deploykf-opt ## -------------------------------------------------------------------------------- deploykf_opt: ## -------------------------------------- ## deploykf-minio ## -------------------------------------- deploykf_minio: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## deploykf-mysql ## -------------------------------------- deploykf_mysql: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------------------------------------------------- ## kubeflow-tools ## -------------------------------------------------------------------------------- kubeflow_tools: ## -------------------------------------- ## katib ## -------------------------------------- katib: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## notebooks ## -------------------------------------- notebooks: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! ## -------------------------------------- ## pipelines ## -------------------------------------- pipelines: {} # <-- REMOVE THIS, IF YOU INCLUDE VALUES UNDER THIS SECTION! destination: server: "https://kubernetes.default.svc" namespace: "argocd"
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执行如下命令，部署工作流：
kubectl apply -f ./deploykf-app-of-apps.yaml
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通过 UI 界面查看 ArgoCD 状态：
kubectl port-forward --namespace "argocd" svc/argocd-server 8090:https
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浏览器打开 https://localhost:8090/，用户名：admin，密码可通过如下命令获取：
echo $(kubectl -n argocd get secret/argocd-initial-admin-secret \
-o jsonpath="{.data.password}" | base64 -d)
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由于程序间存在依赖关系，可以通过如下脚本按序执行 Sync 操作：
git clone -b main https://github.com/deployKF/deployKF.git
cd deployKF/scripts
chmod +x ./sync_argocd_apps.sh
bash ./sync_argocd_apps.sh
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该脚本是幂等的，失败后可反复执行直到部署成功，成功部署后的运行中 Pod 列表类似如下这样：
NAMESPACE NAME READY STATUS RESTARTS AGE argocd argocd-redis-69f8795dbd-x5wtv 1/1 Running 5 (17m ago) 105m argocd argocd-server-86f64667bc-zfm7m 1/1 Running 4 (17m ago) 73m argocd argocd-repo-server-5b55578f7c-x26zz 2/2 Running 10 (17m ago) 91m argocd argocd-notifications-controller-756764ddd5-2fqbr 1/1 Running 5 (17m ago) 89m argocd argocd-dex-server-9b5c6dccd-bl86m 1/1 Running 5 (17m ago) 91m argocd argocd-application-controller-0 1/1 Running 5 (17m ago) 91m argocd argocd-applicationset-controller-7b9c4dfb77-hph2r 1/1 Running 5 (17m ago) 105m cert-manager cert-manager-c688c56f-w4jts 1/1 Running 5 (17m ago) 109m cert-manager trust-manager-78766fd9bd-zd5zf 1/1 Running 5 (17m ago) 90m cert-manager cert-manager-webhook-d45447457-q6cf8 1/1 Running 6 (17m ago) 109m cert-manager cert-manager-cainjector-59d694bcc7-mrcvg 1/1 Running 6 (17m ago) 109m deploykf-auth oauth2-proxy-5fd9888b79-tpnrt 2/2 Running 11 (16m ago) 73m deploykf-auth dex-68c8bf56b9-78d5g 2/2 Running 8 (17m ago) 73m deploykf-dashboard profile-controller-5575767c76-vshp2 2/2 Running 8 (17m ago) 73m deploykf-dashboard kfam-api-75b64c9645-sjfcq 2/2 Running 10 (17m ago) 98m deploykf-dashboard central-dashboard-6b5d9574dc-fmlt4 2/2 Running 10 (17m ago) 98m deploykf-istio-gateway deploykf-gateway-6ddf8947cc-qz55g 1/1 Running 5 (17m ago) 98m deploykf-minio deploykf-minio-568b877668-w2wct 2/2 Running 5 (17m ago) 52m deploykf-mysql deploykf-mysql-0 1/1 Running 5 (17m ago) 109m istio-system istiod-7b9b6df595-jbztw 1/1 Running 5 (17m ago) 91m kube-system svclb-deploykf-gateway-7f7cba3a-kkskn 3/3 Running 15 (17m ago) 100m kube-system metrics-server-648b5df564-gwnhq 1/1 Running 9 (17m ago) 5h43m kube-system local-path-provisioner-957fdf8bc-cj9l5 1/1 Running 7 (17m ago) 5h43m kube-system coredns-77ccd57875-xzzz4 1/1 Running 7 (17m ago) 5h43m kube-system traefik-768bdcdcdd-mr8z8 1/1 Running 7 (17m ago) 5h42m kube-system svclb-traefik-a79cf0ef-6ksjm 2/2 Running 10 (17m ago) 100m kubeflow katib-controller-75858c4ddf-hwvkx 1/1 Running 8 (17m ago) 95m kubeflow ml-pipeline-ui-68b7f6586d-qtjp5 2/2 Running 15 (17m ago) 94m kubeflow ml-pipeline-persistenceagent-68bbd65f98-tsnqn 2/2 Running 10 (17m ago) 94m kubeflow katib-ui-d4df8bdb6-2x75p 2/2 Running 10 (17m ago) 95m kubeflow ml-pipeline-6445d9fb77-dxgv4 2/2 Running 24 (16m ago) 94m kubeflow admission-webhook-deployment-789dc56fbf-z7cj8 1/1 Running 5 (17m ago) 94m kubeflow metadata-writer-6f95b9588c-fmx4s 2/2 Running 8 (17m ago) 73m kubeflow notebook-controller-deployment-649cf9b976-vnvwd 2/2 Running 10 (17m ago) 95m kubeflow training-operator-7cf5c66858-jf5sr 1/1 Running 3 (17m ago) 43m kubeflow tensorboards-web-app-deployment-778466f5f6-dmrks 2/2 Running 2 (17m ago) 43m kubeflow tensorboard-controller-deployment-644f57dd7c-zlxnw 3/3 Running 24 (17m ago) 92m kubeflow ml-pipeline-scheduledworkflow-578475988-kwz27 2/2 Running 10 (17m ago) 94m kubeflow volumes-web-app-deployment-588d46bb75-95g6b 2/2 Running 2 (17m ago) 42m kubeflow ml-pipeline-viewer-crd-6857ccc85c-zl895 2/2 Running 10 (17m ago) 94m kubeflow metadata-grpc-deployment-566d54d578-wwj9n 2/2 Running 23 (16m ago) 94m kubeflow ml-pipeline-visualizationserver-7b45b7fd56-s4pxh 2/2 Running 15 (17m ago) 94m kubeflow cache-server-66d7586749-prmkq 2/2 Running 10 (17m ago) 94m kubeflow jupyter-web-app-deployment-9c8c779c-hcqvr 2/2 Running 15 (17m ago) 91m kubeflow katib-db-manager-6998f5bdd8-lrs77 1/1 Running 5 (17m ago) 95m kubeflow metadata-envoy-deployment-b48db5966-542nh 1/1 Running 5 (17m ago) 94m kubeflow-argo-workflows argo-workflow-controller-79fc5c6895-2g26t 2/2 Running 10 (17m ago) 98m kubeflow-argo-workflows argo-server-6d97fb7649-lsfdw 2/2 Running 5 (16m ago) 73m kyverno kyverno-cleanup-controller-6cb4d5848-hh8nm 1/1 Running 5 (17m ago) 109m kyverno kyverno-admission-controller-964c74c7d-frknb 1/1 Running 5 (17m ago) 109m kyverno kyverno-background-controller-796f77c79f-nwhrs 1/1 Running 5 (17m ago) 109m kyverno kyverno-reports-controller-6d6d98fc96-z7qjv 1/1 Running 5 (17m ago) 109m kyverno kyverno-admission-controller-964c74c7d-hgtc2 1/1 Running 4 (17m ago) 109m kyverno kyverno-admission-controller-964c74c7d-x744h 1/1 Running 5 (17m ago) 109m team-1 ml-pipeline-visualizationserver-677c86b748-nbrr5 2/2 Running 2 (17m ago) 73m team-1 ml-pipeline-ui-artifact-7749b4f5f6-ld7kl 2/2 Running 10 (17m ago) 94m team-1-prod ml-pipeline-visualizationserver-677c86b748-hqwsh 2/2 Running 2 (17m ago) 73m team-1-prod ml-pipeline-ui-artifact-7749b4f5f6-hl6gk 2/2 Running 10 (17m ago) 94m
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同步完成后的 ArgoCD 界面（完成 20 个应用同步）：
5. 访问控制台
执行端口转发：
kubectl port-forward \
--namespace "deploykf-istio-gateway" \
svc/deploykf-gateway 8080:http 8443:https
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由于 Istio Gateway 基于 Host Header 区分访问的目标服务，因此需要配置本地 /etc/hosts 文件，追加如下内容：
127.0.0.1 deploykf.example.com
127.0.0.1 argo-server.deploykf.example.com
127.0.0.1 minio-api.deploykf.example.com
127.0.0.1 minio-console.deploykf.example.com
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浏览器访问 https://deploykf.example.com:8443/
管理员：用户名 admin@example.com 密码 admin
用户 1: 用户名 user1@example.com 密码 user1
用户 2: 用户名 user2@example.com 密码 user2
6. 运行 Jupyter
更多功能持续探索中…
本文引用
https://www.deploykf.org/guides/local-quickstart/
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