Mighten opened a new issue, #16478:
URL: https://github.com/apache/dolphinscheduler/issues/16478

   ### Search before asking
   
   - [X] I had searched in the 
[DSIP](https://github.com/apache/dolphinscheduler/issues/14102) and found no 
similar DSIP.
   
   
   ### Motivation
   
   
   Supporting **user-customized K8s YAML tasks** has the following benefits:
   
   - **Flexibility:** Unlike the existing K8s low-code job with limited 
functionality, YAML tasks provide users with the flexibility to define 
sophisticated task instances in DolphinScheduler, similar to how custom JSON 
does in DataX.
   
   - **Workflow Customization:** Users can integrate operational and 
maintenance processes into DolphinScheduler using YAML for complex workflows.
   
   - **Configuration Requirements:** The current K8s low-code job does not meet 
users' in-depth needs, particularly for tasks involving *multiple pods* or 
specific *configurations* like *environment variables* and *tolerations*; in 
contrast, K8s YAML tasks do.
   
   In short, by enabling user-customized YAML tasks, *DolphinScheduler* can 
better support a wide range of Kubernetes-based workflows and operational 
requirements.
   
   
   ### Design Detail
   
   ### 2.1 Design Overview
   
   The following is a Swimlane Diagram showing how this k8s YAML task is 
*embedded* into Apache DolphinScheduler:
   
   
![2-1-1-design-overview](https://github.com/user-attachments/assets/94b140ff-f650-49f0-8132-4c94ba543f12)
   *Figure 2-1(1). Design Overview*
   
   1. **User** starts a Web page to edit and save K8s YAML Workflow.
   2. **UI** provides an editor for user to input YAML in Custom Template mode.
   3. **API Server** encapsulates command and hands it over to *Master*.
   4. **Master** splits the workflow DAG and dispatches tasks to **Worker**.
   5. **Worker** picks the appropriate *task executor* and *operation*. E.g., 
for k8s Pod YAML, Worker picks *YAML Task Executor*, and then picks *Pod 
Operation*.
   6. **Worker** reports status to *Master*.
   7. **User** reviews k8s YAML task *log* in the Task Instance Window.
   
   
   ### 2.2 Frontend Design
   
   The frontend adds support for user-customized k8s YAML tasks while remaining 
compatible with the original k8s low-code jobs.
   
   
![2-2-1-frontend-design](https://github.com/user-attachments/assets/3a0d82b0-e3c7-4cbd-8983-9376e4ec0cdd)
   *Figure 2-2(1). Design Overview*
   
   1. **The Web UI layouts**
   
       When the user switches on the Custom Template, the Low-code k8s Job 
fields should *hide* and YAML editor should *appear* (or vice versa), similar 
to the JSON Custom Template in the *DataX* plugin.
   
       This feature, as shown in Figure 2-2(1), is implemented using the *Vue 
component span*, which is controlled by *reactive variables* (such as 
`yamlEditorSpan`) in the file 
`dolphinscheduler-ui/src/views/projects/task/components/node/fields/use-k8s.ts`.
   
   2. **The Request body**
   
       When the user switches to Custom Template mode, the request body should 
include only YAML-related fields (`customConfig` and `yamlContent`), and all 
previously hidden fields should not be sent.
   
       This feature is implemented using the `taskParams` in the file 
`dolphinscheduler-ui/src/views/projects/task/components/node/format-data.ts`
   
   3. **i18n/locales**
   
       Apache DolphinScheduler is an international software and should support 
multiple languages.
   
       The text on the Web UI are retrieved from variables defined in the file 
`dolphinscheduler-ui/src/locales/{en_US, zh_CN}/project.ts`. And for 
user-customized k8s YAML tasks, there are three key variables to consider:
       - `k8s_custom_template`: the label for the switch to enable 
user-customized k8s YAML tasks.
       - `k8s_yaml_template`: the label for the text editor used to input user 
YAML.
       - `k8s_yaml_empty_tips`: the warning message displayed when a user tries 
to submit empty YAML
   
       This feature is implemented by invoking 
`t('project.node.${variable_name}')` (such as 
`t('project.node.k8s_yaml_template')`) in the file 
`dolphinscheduler-ui/src/views/projects/task/components/node/fields/use-k8s.ts`.
   
   ### 2.3 Backend Design
   
   The backend design describes the process of how the worker executes 
user-customized k8s YAML tasks. As shown in Figure 2-3(1), we can see how 
user-customized k8s YAML Pod tasks are related to the original k8s low-code 
jobs.
   
   
![2-3-1-backend-design-overview](https://github.com/user-attachments/assets/d3797bd3-e5bd-4161-b460-622e09f46daf)
   *Figure 2-3(1). Backend Design Overview*
   
   After the worker checks the parameters, `K8sYamlTaskExecutor` is loaded for 
the current user-customized k8s YAML Pod task. Once the YAML is parsed into 
`HasMetadata`, its `kind` field is used to assign `abstractK8sOperation` as 
`K8sPodOperation` for executing the YAML Pod task.
   
   1. **K8s Task Executors**
   
   
       
![2-3-2-backend-design-task-executors](https://github.com/user-attachments/assets/d7bb9413-5f2b-4aa2-9503-195c7b785e0e)
       *Figure 2-3(2). K8s Task Executors*
   
       Three k8s task executor are involved, as shown in Figure 2-3(2):
       - `AbstractK8sTaskExecutor` is an abstract class that represents a k8s 
task executor.
       - `K8sTaskExecutor` is a concrete class that *extends* 
`AbstractK8sTaskExecutor` to represent a low-code executor 
       - `K8sYamlTaskExecutor` is a concrete class that *extends* 
`AbstractK8sTaskExecutor` to represent a user-customized k8s YAML task executor.
   
   2. **K8s Operation handler**
   
       
![2-3-3-backend-design-operation-handlers](https://github.com/user-attachments/assets/92b63548-d1f6-4edb-b626-90eea4648185)
       *Figure 2-3(3). K8s Operation Handlers*
   
       Two operation handlers are involved, as shown in Figure 2-3(3):
       - `AbstractK8sOperation` is an interface representing all k8s resource 
operations. 
       - `K8sPodOperation` is a concrete class that implements 
`AbstractK8sOperation` to handle *Pod* operations
   
   
   
   
   ### 2.4 Usecase Design
   
   A typical use case for a k8s YAML task includes *uploading* YAML, *online* 
workflows, and *starting* workflows, similar to k8s low-code jobs, unless users 
switch to the *Custom Template* option to fill in YAML.
   
   
![2-4-1-usecase-design](https://github.com/user-attachments/assets/bf853d38-eca6-49f8-9e1b-ade239bef1ab)
   *Figure 2-4(1). Usecase Design*
   
   1. The user **edits** a k8s YAML node in a workflow
   2. If the *Custom Template* is activated and YAML content is not blank, the 
user may **online** this whole workflow
   3. If the workflow is *online*, the user may **start** the workflow and 
review the logs generated during the execution of the workflow.
   
   
   ### Compatibility, Deprecation, and Migration Plan
   
   
   ### 3.1 Compatibility Plan
   
   The user-customized k8s YAML feature requires only `customConfig` to be 
activated, By default, the value is 0, which applies to the existing k8s 
low-code jobs.
   
   
   **Action List:** Extension of operations for the k8s YAML task:
   - [x] Pod  #15301
   - [ ] ConfigMaps
   - [ ] ...
   
   The remainder of this section will demonstrate the *flexibility* and 
*compatibility* of this design by using the example of introducing `Configmaps`:
   
   ```java
       this.k8sYamlType = K8sYamlType.valueOf(this.metadata.getKind());
       generateOperation();
   ```
   
   After parsing with `YamlUtils::load`, the `kind` field acquired by 
`this.metadata.getKind()` will be `ConfigMaps`. Then, `this.k8sYamlType` is 
determined and used to generate the corresponding operations:
   
   ```java
       private void generateOperation() {
           switch (k8sYamlType) {
               case Pod:
                   abstractK8sOperation = new 
K8sPodOperation(k8sUtils.getClient());
                   break;
               case ConfigMaps:
                   abstractK8sOperation = new 
K8sConfigmapsOperation(k8sUtils.getClient());
                   break;
               default:
                   throw new TaskException(
                           String.format("K8sYamlTaskExecutor do not support 
type %s", k8sYamlType.name()));
           }
       }
   ```
   
   Consequently, `generateOperation()` will set `this.abstractK8sOperation` to 
a new instance of `K8sConfigmapsOperation`. Next, we can implement 
K8sConfigmapsOperation to handle the ConfigMaps operations.
   
   
   ### 3.2 Deprecation Plan
   
   N/A for now, *waiting for community opinions*.
   
   ### 3.3 Migration Plan
   
   N/A for now, *waiting for community opinions*.
   
   
   ### Test Plan
   
   
   ### 4.1 Overview
   
   The User-customized k8s YAML task feature allows users to submit YAML task 
to k8s, including *Pod*, *ConfigMaps*, and other resources.
   
   This test plan aims to ensure that the feature functions as expected and 
meets user requirements.
   
   
   ### 4.2 Scope
   
   1. **YAML Pod**
   
   | Test Case #|        Name      |            Action          |               
Expectation             |
   | :--------: | :----------------| :------------------------- | 
:------------------------------------ |
   |    1       | UI Display       | Edit YAML, save and reopen | The YAML 
content stays up-to-date.    |
   |    2       | UI Validation    | try to submit empty YAML   | The UI modal 
dialog intercepts empty YAML. |
   |    3       | Online Workflow  | Save workflow, and online  | The User 
successfully brings the workflow online. |
   |    4       | Dryrun Workflow  | Run workflow as dryrun mode| The Master 
successfully dry runs this task. |
   |    5       | Test Workflow    | Run workflow as test mode  | The Worker 
successfully tests this task. |
   |    6       | Run Workflow     | Run workflow               | The Worker 
successfully runs this task. |
   
   
   ### Code of Conduct
   
   - [X] I agree to follow this project's [Code of 
Conduct](https://www.apache.org/foundation/policies/conduct)
   


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