How-to guides

You can create a Training Job for the Simple AI Training service, choose the AI training method, and proceed with training.

Creating a Training Job

To use the Simple AI Training service, you must first create a Training Job. To create a Trainging Job, follow these steps.

1. All Services > AI/ML > Simple AI Training Click the menu. 1. Go to the Service Home page of Simple AI Training.

2. On the Service Home page, click the Create Training Job button. 2. Create Training Job Go to the page.

3. On the Training Job creation page, enter the information required for service creation and select detailed options.

   • Select the required information related to the Training Job in the Required Information Input area.

     Category	required status	Detailed description
     Learning type	Required	Select training mode On-Demand Training: Securely conduct training by preempting a server at the desired time Concurrent Checkpointing feature applied to support efficient checkpoint storage Spot Training: Conduct cost‑effective training for lower‑priority jobs using idle GPUs Concurrent Checkpointing and Mixed workload features applied to support training continuity (automatic pause and resume) For detailed information on the Concurrent Checkpointing feature, see the Concurrent Checkpointing 개요 reference
     Training Job name	Required	Enter the Training Job name Enter using lowercase English letters, numbers, and special characters (-.) within 3 ~ 63 characters The name must start and end with a lowercase English letter or number
     Distributed Framework	Required	Select version of the distributed Framework PyTorch, DeepSpeed selectable

     Table. Required input fields for Training Job
   • Select the options required to create a Training Job in the Service Information Input area.

     Category	required status	Detailed description
     Job Failover	Selection	Select whether to use the Job Failover feature Spot Training cannot be used with Job Failover For detailed information about the Job Failover feature, see Job Failover 사용하기
     Resource allocation	Required	Select the number of GPUs and memory size to use for training
     Number of nodes	Required	Set the scale of distributed training Distributed training is possible from 2 nodes onward
     Shared Memory	Required	Set the memory to be shared between processes for distributed training and distributed data processing.

     Table. Training Job service information input items
   • In the AI Training Image Information Input area, select the options required to create the service.

     Category	required status	Detailed description
     AI Training Image URL	Required	Enter the user’s container registry (SCR, Docker Hub, etc.) address
     User ID	Selection	User ID of the image repository
     Password	Required	Password for the image repository

     Table. Training Job AI Training Image Information Input Items
   • Training Command and Volume Information Input area, please input or select the required information.

     Category	required status	Detailed description
     Storage connection	Selection	Select whether to use an additional volume When used, enter the additional volume mount path and training script URL File Storage Volume Mount Path: Data path to use when connecting to File Storage (e.g., /root) Import Training Script (Object Storage): Enter the script URL when connecting to Object Storage
     Command	Required	Enter command information within 3 to 1,024.

     Table. Training Job AI Training Image Information Input Items
   • Additional Information Input area, please enter or select the required information.

     Category	required status	Detailed description
     tag	Selection	Add Tag Up to 50 can be added per resource After clicking the Add Tag button, enter or select Key, Value values

     Table. Training Job training command and volume information input items

4. Summary Check the detailed information generated in the panel, and click the Create button.

5. When the popup notifying creation opens, click the Confirm button.

   • When creation is complete, check the created resources on the Training Job List page.

Check detailed information of Training Job

You can view and edit the complete resource list and detailed information of the Training Job service. To view the details of a Training Job, follow these steps.

1. Click the All Services > AI/ML > Simple AI Training menu. 1. Go to the Service Home page of Simple AI Training.
2. On the Service Home page, click the Training Job menu. 2. Navigate to the Training Job List page.
3. On the Training Job List page, click the resource to view detailed information. 3. Navigate to the Training Job Details page.
   • Training Job Details page consists of the Details, Monitoring, Logs, Tags tabs.

     Category	Detailed description
     Service status	CloudML status Creating: Creating Deployed: Created / operating normally Updating: Updating settings Terminating: Deleting Error: Error occurred
     Delete Training Job	Button to cancel the service

     Table. Training Job detail page items

Detailed Information

Training Job List page allows you to view detailed information of the selected resource.

Monitoring

Training Job List page allows you to view the monitoring information of the selected resource.

log

On the Training Job List page, you can view the log information of the selected resource.

Tag

Training Job list page lets you view the tag information of the selected resource, and you can add, modify, or delete it.

Checking Training Job logs

You can view the logs of a Training Job in the ServiceWatch service. To view the logs of the Training Job, follow these steps.

1. Click the All Services > AI/ML > Simple AI Training menu. 1. Go to the Service Home page of Simple AI Training.
2. On the Service Home page, click the Training Job menu. 2. Go to the Training Job List page.
3. Training Job list page: select the resource to view logs. 3. Navigate to the Training Job Details page.
4. On the Training Job Details page, click the Log tab. 4. The log information for this job is displayed.
5. Click the name below the Training Job name in the log information. 5. Navigate to the ServiceWatch Log Group Details page.
6. Log Group Details page, click the Log Stream tab. 6. The list of log streams is displayed.
7. Click the log stream name to verify (example: master). 7. The logs of the stream are displayed in chronological order.
   • When a failover occurs, the logs of the training that was interrupted due to the failure and the logs of the training that was restarted after reallocation are recorded together in a single stream.
   • If the initialization log displayed at the start of training (e.g., Starting dataset initialization) appears more than once, you can confirm that the training was rescheduled and restarted.

Delete Training Job

You can delete unused Training Jobs. To delete a Training Job, follow these steps.

1. All Services > AI/ML > Simple AI Training Click the menu. 1. Go to the Service Home page of Simple AI Training.
2. On the Service Home page, click the Training Job menu. 2. Go to the Training Job List page.
3. On the Training Job List page, select the resources to delete, then click the Delete button at the top of the list.
   • Click the resource to delete, go to the Training Job Details page, and you can also delete it individually.
4. When a pop-up notifying deletion opens, click the Confirm button.

Using the Training Workspace

You can use the Simple AI Training service by using the Training Workspace.

Create Training Workspace

To create a Training Workspace, follow the steps below.

1. Click the All Services > AI/ML > Simple AI Training menu. 1. Go to the Service Home page of Simple AI Training.

2. Click the Training Workspace menu on the Service Home page. 2. Go to the Training Workspace List page.

3. On the Training Workspace List page, click the Create Service button. 3. Go to the Create Training Workspace page.

4. Enter the information required to create the service and select detailed options.

   • In the Service Information Input area, select the options required to create a Training Workspace.

     Category	required status	Detailed description
     Training Workspace name	Required	Enter the Training Workspace name Enter using lowercase English letters, numbers, and special characters (-.) within 63 characters
     Resource allocation	Required	Select the number of GPUs and memory size to use for training
     Number of nodes	Required	Set the scale of distributed training Distributed training is possible from 2 nodes onward
     Contract period	Required	Select the service usage agreement period

     Table. Training Workspace service information input items

5. Summary Check the detailed information and estimated billing amount generated in the panel, and click the Create button.

6. When the popup notifying creation opens, click the Confirm button.

   • When creation is complete, check the resources you created on the Training Workspace List page.

Edit Training Workspace

You can modify the number of nodes in the Training Workspace. To modify the Training Workspace, follow these steps.

1. Click the All Services > AI/ML > Simple AI Training menu. 1. Go to the Service Home page of Simple AI Training.
2. On the Service Home page, click the Training Workspace menu. 2. Navigate to the Training Workspace List page.
3. On the Training Workspace List page, click the More > Edit button of the resource you want to modify. 3. Go to the Training Workspace Edit page.
4. On the Training Workspace Edit page, check and modify the node count.
5. When the edit is complete, click the Confirm button.

Delete Training Workspace

You can delete an unused Training Workspace. To delete the Training Workspace, follow these steps.

1. All Services > AI/ML > Simple AI Training Click the menu. 1. Go to the Service Home page of Simple AI Training.
2. On the Service Home page, click the Training Workspace menu. 2. Navigate to the Training Workspace List page.
3. On the Training Workspace List page, select the resource to delete, then click the Cancel Service button at the top of the list.
   • You can also delete the resource individually by clicking the More > Service Cancellation button.
4. When a pop-up indicating deletion opens, click the Confirm button.