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The following commit(s) were added to refs/heads/dev by this push:
     new aabda868da doc: simplify k8s deploy steps (#16402)
aabda868da is described below

commit aabda868daabe938e4894f1886d56def9401651c
Author: Gallardot <[email protected]>
AuthorDate: Thu Aug 1 16:42:26 2024 +0800

    doc: simplify k8s deploy steps (#16402)
    
    Signed-off-by: Gallardot <[email protected]>
    Co-authored-by: xiangzihao <[email protected]>
---
 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 <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" \
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 <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 <!-- 
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` 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 <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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