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doc: simplify k8s deploy steps (#16402)

Signed-off-by: Gallardot <gallardot@apache.org>
Co-authored-by: xiangzihao <460888207@qq.com>
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Gallardot 3 months ago committed by GitHub
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  1. 24
      docs/docs/en/guide/installation/kubernetes.md
  2. 24
      docs/docs/zh/guide/installation/kubernetes.md

24
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 <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 <your-namespace-to-deploy-dolphinscheduler>
helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version <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 <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 <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 <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" \

24
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 <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``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 <!-- markdown-link-check-disable-line -->
> **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 <your-namespace-to-deploy-dolphinscheduler>
helm upgrade --install dolphinscheduler --create-namespace --namespace dolphinscheduler oci://registry-1.docker.io/apache/dolphinscheduler-helm --version <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``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 <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 <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 <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" \

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