Merge pull request #110 from sophongo/node

[en] update kpanda workload pages

docs/en/end-user/baize/jobs/mpi.md

@@ -20,7 +20,7 @@ Here we will use the `baize-notebook` base image and the **associated environmen
 
 ### Steps to Create an MPI Job
 
-1. **Log in to the Platform** : Log in to the AI Lab platform and click on **Job Center** in the left navigation bar to enter the **Training Jobs** page.
+1. **Log in to the Platform** : Log in to the AI Lab platform and click **Job Center** in the left navigation bar to enter the **Training Jobs** page.
 2. **Create Job** : Click the **Create** button in the upper right corner to enter the job creation page.
 3. **Select Job Type** : In the pop-up window, select the job type as `MPI`, then click **Next**.
 4. **Fill in Job Information** : Fill in the job name and description, for example, “benchmarks-mpi”, then click **Next**.

docs/en/end-user/baize/jobs/mxnet.md

@@ -25,7 +25,7 @@ We will use the `release-ci.daocloud.io/baize/kubeflow/mxnet-gpu:latest` image a
 
 #### Steps to Create
 
-1. **Log in to the Platform** : Log in to the AI Lab platform and click on **Job Center** in the left navigation bar to enter the **Training Jobs** page.
+1. **Log in to the Platform** : Log in to the AI Lab platform and click **Job Center** in the left navigation bar to enter the **Training Jobs** page.
 2. **Create Job** : Click the **Create** button in the upper right corner to enter the job creation page.
 3. **Select Job Type** : In the pop-up window, select the job type as `MXNet`, then click **Next**.
 4. **Fill in Job Information** : Enter the job name and description, for example, “MXNet Single-node Training Job”, then click **Confirm**.

docs/en/end-user/baize/jobs/paddle.md

@@ -21,7 +21,7 @@ We use the `registry.baidubce.com/paddlepaddle/paddle:2.4.0rc0-cpu` image as the
 
 #### Steps to Create
 
-1. **Log in to the Platform** : Log in to the AI Lab platform and click on **Job Center** in the left navigation bar to enter the **Training Jobs** page.
+1. **Log in to the Platform** : Log in to the AI Lab platform and click **Job Center** in the left navigation bar to enter the **Training Jobs** page.
 2. **Create Job** : Click the **Create** button in the upper right corner to enter the job creation page.
 3. **Select Job Type** : In the pop-up window, select the job type as `PaddlePaddle`, then click **Next**.
 4. **Fill in Job Information** : Enter the job name and description, for example, “PaddlePaddle Single-node Training Job”, then click **Confirm**.

docs/en/end-user/baize/quick-start.md

@@ -77,7 +77,7 @@ Prepare your development environment by clicking on **Notebooks** in the navigat
 
 ## Creating a Training Job
 
-1. Click on **Job Center** -> **Training Jobs** in the navigation bar to create a standalone `TensorFlow` job.
+1. Click **Job Center** -> **Training Jobs** in the navigation bar to create a standalone `TensorFlow` job.
 2. Fill in the basic parameters and click **Next**.
 3. In the job resource configuration, correctly set up the job resources and click **Next**.
 
@@ -96,8 +96,8 @@ Prepare your development environment by clicking on **Notebooks** in the navigat
         Logs will be saved in the output dataset at `/home/jovyan/model/train/logs/`.
 
 
-5. Return to the training job list and wait for the status to change to **Success**. Click on the **┇** icon on the right side of the list to view details, clone jobs, update priority, view logs, and delete jobs, among other options.
+5. Return to the training job list and wait for the status to change to **Success**. Click the **┇** icon on the right side of the list to view details, clone jobs, update priority, view logs, and delete jobs, among other options.
 
-6. Once the job is successfully created, click on **Job Analysis** in the left navigation bar to check the job status and fine-tune your training.
+6. Once the job is successfully created, click **Job Analysis** in the left navigation bar to check the job status and fine-tune your training.
 
     ![View Job](./images/baize-07.png)

docs/en/end-user/kpanda/nodes/add-node.md

@@ -1,4 +1,6 @@
 ---
+hide:
+  - toc
 MTPE: FanLin
 Date: 2024-02-27
 ---

docs/en/end-user/kpanda/nodes/delete-node.md

@@ -12,9 +12,7 @@ When the peak business period is over, in order to save resource costs, you can
 ## Precautions
 
 1. When cluster nodes scales down, they can only be uninstalled one by one, not in batches.
-
 2. If you need to uninstall cluster controller nodes, you need to ensure that the final number of controller nodes is an **odd number**.
-
 3. The **first controller** node cannot be offline when the cluster node scales down. If it is necessary to perform this operation, please contact the after-sales engineer.
 
 ## Steps

docs/en/end-user/kpanda/nodes/node-authentication.md

@@ -1,6 +1,9 @@
-# Node Authentication
+---
+hide:
+  - toc
+---
 
-## Authenticate Nodes Using SSH Keys
+# Node Authentication
 
 If you choose to authenticate the nodes of the cluster-to-be-created using SSH keys, you need to configure the public and private keys according to the following instructions.
 

docs/en/end-user/kpanda/workloads/create-cronjob.md

@@ -13,13 +13,13 @@ CronJobs are suitable for performing periodic operations, such as backup and rep
 
 Before creating a CronJob, the following prerequisites need to be met:
 
-- In the Container Management module [Integrate Kubernetes Cluster](../clusters/integrate-cluster.md) or [Create Kubernetes Cluster](../clusters/create-cluster.md), and can access the cluster UI interface.
+- You have integrated a Kubernetes Cluster in the Container Management module as described in [Integrate Kubernetes Cluster](../clusters/integrate-cluster.md) or [Create Kubernetes Cluster](../clusters/create-cluster.md), and you can access the cluster's UI interface.
 
 - Create a [namespace](../namespaces/createns.md) and a user.
 
 - The current operating user should have [NS Editor](../permissions/permission-brief.md#ns-editor) or higher permissions, for details, refer to [Namespace Authorization](../namespaces/createns.md).
 
-- When there are multiple containers in a single instance, please make sure that the ports used by the containers do not conflict, otherwise the deployment will fail.
+- When there are multiple containers in a single instance, please make sure that the ports used by the containers do not conflict, otherwise the CronJob will fail.
 
 ## Create by image
 

docs/en/end-user/kpanda/workloads/create-daemonset.md

@@ -21,13 +21,13 @@ For simplicity, a DaemonSet can be started on each node for each type of daemon.
 
 Before creating a DaemonSet, the following prerequisites need to be met:
 
-- In the Container Management module [Integrate Kubernetes Cluster](../clusters/integrate-cluster.md) or [Create Kubernetes Cluster](../clusters/create-cluster.md), and can access the cluster UI interface.
+- You have integrated a Kubernetes Cluster in the Container Management module as described in [Integrate Kubernetes Cluster](../clusters/integrate-cluster.md) or [Create Kubernetes Cluster](../clusters/create-cluster.md), and you can access the cluster's UI interface.
 
 - Create a [namespace](../namespaces/createns.md) and a user.
 
 - The current operating user should have [NS Editor](../permissions/permission-brief.md#ns-editor) or higher permissions, for details, refer to [Namespace Authorization](../namespaces/createns.md).
 
-- When there are multiple containers in a single instance, please make sure that the ports used by the containers do not conflict, otherwise the deployment will fail.
+- When there are multiple containers in a single instance, please make sure that the ports used by the containers do not conflict, otherwise the DaemonSet will fail.
 
 ## Create by image