From aabda868daabe938e4894f1886d56def9401651c Mon Sep 17 00:00:00 2001 From: Gallardot Date: Thu, 1 Aug 2024 16:42:26 +0800 Subject: [PATCH] doc: simplify k8s deploy steps (#16402) Signed-off-by: Gallardot Co-authored-by: xiangzihao <460888207@qq.com> --- docs/docs/en/guide/installation/kubernetes.md | 24 ++++--------------- docs/docs/zh/guide/installation/kubernetes.md | 24 ++++--------------- 2 files changed, 10 insertions(+), 38 deletions(-) diff --git a/docs/docs/en/guide/installation/kubernetes.md b/docs/docs/en/guide/installation/kubernetes.md index e8bceebf23..d2f25c3434 100644 --- a/docs/docs/en/guide/installation/kubernetes.md +++ b/docs/docs/en/guide/installation/kubernetes.md @@ -16,23 +16,9 @@ If you are a new hand and want to experience DolphinScheduler functions, we reco ```bash # Choose the corresponding version yourself -export VERSION=3.2.1 -helm pull oci://registry-1.docker.io/apache/dolphinscheduler-helm --version ${VERSION} -tar -xvf dolphinscheduler-helm-${VERSION}.tgz -cd dolphinscheduler-helm -helm repo add bitnami https://charts.bitnami.com/bitnami -helm dependency update . -helm install dolphinscheduler . +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version ``` -To publish the release name `dolphinscheduler` version to `test` namespace: - -```bash -$ helm install dolphinscheduler . -n test -``` - -> **Tip**: If a namespace named `test` is used, the optional parameter `-n test` needs to be added to the `helm` and `kubectl` commands. - These commands are used to deploy DolphinScheduler on the Kubernetes cluster by default. The [Appendix-Configuration](#appendix-configuration) section lists the parameters that can be configured during installation. > **Tip**: List all releases using `helm list` @@ -112,7 +98,7 @@ helm install keda kedacore/keda \ Secondly, you need to set `worker.keda.enabled` to `true` in `values.yaml` or install the chart by: ```bash -helm install dolphinscheduler . --set worker.keda.enabled=true -n +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version --set worker.keda.enabled=true ``` Once autoscaling enabled, the number of workers will scale between `minReplicaCount` and `maxReplicaCount` based on the states @@ -504,15 +490,15 @@ For example, if you need to deploy worker to both CPU and GPU servers in a clust ```bash # Install master, api-server, alert-server, and other default components, but do not install worker -helm install dolphinscheduler . --set worker.enabled=false +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version --set worker.enabled=false # Disable the installation of other components, only install worker, use the self-built CPU image, deploy to CPU servers with the `x86` label through nodeselector, and use zookeeper as the external registry center -helm install dolphinscheduler-cpu-worker . \ +helm upgrade --install dolphinscheduler-cpu-worker --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version \ --set minio.enabled=false --set postgresql.enabled=false --set zookeeper.enabled=false \ --set master.enabled=false --set api.enabled=false --set alert.enabled=false \ --set worker.enabled=true --set image.tag=latest-cpu --set worker.nodeSelector.cpu="x86" \ --set externalRegistry.registryPluginName=zookeeper --set externalRegistry.registryServers=dolphinscheduler-zookeeper:2181 # Disable the installation of other components, only install worker, use the self-built GPU image, deploy to GPU servers with the `a100` label through nodeselector, and use zookeeper as the external registry center -helm install dolphinscheduler-gpu-worker . \ +helm upgrade --install dolphinscheduler-gpu-worker --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version \ --set minio.enabled=false --set postgresql.enabled=false --set zookeeper.enabled=false \ --set master.enabled=false --set api.enabled=false --set alert.enabled=false \ --set worker.enabled=true --set image.tag=latest-gpu --set worker.nodeSelector.gpu="a100" \ diff --git a/docs/docs/zh/guide/installation/kubernetes.md b/docs/docs/zh/guide/installation/kubernetes.md index 7f496656a3..c7a1de5337 100644 --- a/docs/docs/zh/guide/installation/kubernetes.md +++ b/docs/docs/zh/guide/installation/kubernetes.md @@ -16,23 +16,9 @@ Kubernetes 部署目的是在 Kubernetes 集群中部署 DolphinScheduler 服务 ```bash # 自行选择对应的版本 -export VERSION=3.2.1 -helm pull oci://registry-1.docker.io/apache/dolphinscheduler-helm --version ${VERSION} -tar -xvf dolphinscheduler-helm-${VERSION}.tgz -cd dolphinscheduler-helm -helm repo add bitnami https://charts.bitnami.com/bitnami -helm dependency update . -helm install dolphinscheduler . +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version ``` -将名为 `dolphinscheduler` 的版本(release) 发布到 `test` 的命名空间中： - -```bash -$ helm install dolphinscheduler . -n test -``` - -> **提示**: 如果名为 `test` 的命名空间被使用, 选项参数 `-n test` 需要添加到 `helm` 和 `kubectl` 命令中 - 这些命令以默认配置在 Kubernetes 集群上部署 DolphinScheduler，[附录-配置](#appendix-configuration)部分列出了可以在安装过程中配置的参数 > **提示**: 列出所有已发布的版本，使用 `helm list` @@ -112,7 +98,7 @@ helm install keda kedacore/keda \ 其次，您需要将 `values.yaml` 中的 `worker.keda.enabled` 配置设置成 `true`，或者您可以通过以下命令安装 chart： ```bash -helm install dolphinscheduler . --set worker.keda.enabled=true -n +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version --set worker.keda.enabled=true ``` 一旦自动扩缩容功能启用，worker的数量将基于任务状态在 `minReplicaCount` 和 `maxReplicaCount` 之间弹性扩缩。 @@ -503,15 +489,15 @@ common: ```bash # 安装 master、api-server、alert-server以及其他默认组件，但是不安装 worker -helm install dolphinscheduler . --set worker.enabled=false +helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version --set worker.enabled=false # 禁用其他组件的安装，只安装 worker，使用自行建构建的 CPU镜像，通过 nodeselector部署到附带 x86标签的 CPU服务器，使用 zookeeper作为外部注册中心 -helm install dolphinscheduler-cpu-worker . \ +helm upgrade --install dolphinscheduler-cpu-worker --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version \ --set minio.enabled=false --set postgresql.enabled=false --set zookeeper.enabled=false \ --set master.enabled=false --set api.enabled=false --set alert.enabled=false \ --set worker.enabled=true --set image.tag=latest-cpu --set worker.nodeSelector.cpu="x86" \ --set externalRegistry.registryPluginName=zookeeper --set externalRegistry.registryServers=dolphinscheduler-zookeeper:2181 # 禁用其他组件的安装，只安装 worker，使用自行建构建的 GPU 镜像，通过 nodeselector部署到附带 a100标签的 gpu服务器，使用zookeeper作为外部注册中心 -helm install dolphinscheduler-gpu-worker . \ +helm upgrade --install dolphinscheduler-gpu-worker --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version \ --set minio.enabled=false --set postgresql.enabled=false --set zookeeper.enabled=false \ --set master.enabled=false --set api.enabled=false --set alert.enabled=false \ --set worker.enabled=true --set image.tag=latest-gpu --set worker.nodeSelector.gpu="a100" \