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How-to guides

Create CloudML

The user can enter the essential information of CloudML through the Samsung Cloud Platform Console and create the service by selecting detailed options.

To create CloudML, follow these steps.

  1. Click on the menu for all services > AI/ML > CloudML. It moves to the Service Home page of CloudML.

  2. Service Home page, click the CloudML creation button. It moves to the CloudML page.

  3. CloudML Creation page where you enter the information required for service creation and select detailed options.

    • Version Selection area, select the version of the service.

      Classification
      Necessity
      Detailed Description
      Version SelectionRequiredCloudML Version Selection
      Fig. CloudML Service Version Selection Items

    • In the SCP Kubernetes Engine deployment area, select the options required to create a service.

      Classification
      Necessity
      Detailed Description
      Cluster NameRequiredSelect Kubernetes Engine Cluster
      Fig. CloudML Service Cluster Selection Items

    • Service Information Input area, select the options required for service creation.

      Classification
      Necessity
      Detailed Description
      CloudML namerequiredEnter service name
      DescriptionSelectionEnter Service Description
      Domain NameRequiredEnter the domain name to be used in the service
      • Enter 2-63 characters using lowercase English letters, numbers, and special characters
      EndpointRequiredSelect the endpoint to use for the service
      • Private and Public options
      CopilotSelectionSelect whether to use Copilot in the service
      • Application selection requires agreement to terms in a popup window
      • If the selected cluster is not composed of LLM dedicated GPU and the allocated LLM resources are insufficient, Copilot application is not possible
      Resource InformationRequiredDisplays resource information of the selected cluster
      SCR Information InputRequiredInput SCR information to be used in the service
      • Private Endpoint, Authentication Key, Secret Key input
      Table. CloudML Service Information Input Items

    • Enter Additional Information Please enter or select the necessary information in the area.

      Classification
      Mandatory
      Detailed Description
      TagSelectionAdd Tag
      • Up to 50 can be added per resource
      • Click the Add Tag button and enter or select Key, Value
      Table. CloudML Additional Information Input Items

  4. In the Summary panel, review the detailed information and estimated charges, and click the Complete button.

    • Once creation is complete, check the created resource on the CloudML list page.

Check CloudML details

You can check and modify the entire resource list and detailed information of the CloudML service. The CloudML details page consists of details, tags, work history tabs.

To check the CloudML details, follow the next procedure.

  1. Click on all services > AI/ML > CloudML menu. It moves to the Service Home page of CloudML.

  2. Service Home page, click the resource (CloudML) to check the detailed information. It moves to the CloudML detail page.

    • CloudML Details page displays the status information and detailed information of CloudML, and consists of Details, Tags, Work History tabs.
    DivisionDetailed Description
    Service StatusCloudML’s Status
    • Creating: being created
    • Deployed: created/completed and operating normally
    • Updating: updating settings
    • Terminating: being deleted
    • Error: error occurred
    Connection GuideService Connection Guide
    • Host information guide to be registered on the user PC
    Service CancellationButton to cancel the service
    Fig. CloudML Status Information and Additional Features

Detailed Information

On the CloudML list page, you can check the detailed information of the selected resource and modify the information if necessary.

DivisionDetailed Description
ServiceService Name
Resource TypeResource Type
SRNUnique resource ID in Samsung Cloud Platform
Resource NameResource Title
Resource IDUnique resource ID in the service
CreatorUser who created the service
Creation TimeThe time when the service was created
EditorUser who modified the service information
Modified DateDate when service information was modified
Product NameCloudML Name
CopilotWhether to use Copilot
DescriptionDescription of the service
Cluster NameSelected Kubernetes Engine cluster name
Domain NameEntered Service Domain Name
VersionSelected Service Version
Installation Node InformationNode information installed in the cluster
SCR InformationEntered SCR Information
Fig. CloudML Detailed Information Items

Tag

On the CloudML list page, you can check the tag information of the selected resource, and add, change, or delete it.

ClassificationDetailed Description
Tag ListTag list
  • Check Key, Value information of tag
  • Up to 50 tags can be added per resource
  • Search and select existing Key and Value lists when entering tags
Fig. CloudML tags tab items

Work History

You can check the job history of the selected resource on the CloudML list page.

ClassificationDetailed Description
Work history listResource change history
  • Work time, resource type, resource name, work details, work result, worker name, path information can be checked
  • To perform a detailed search, click the Detailed Search button
Fig. Job History Tab Detailed Information Items

Canceling CloudML Service

Users can cancel the CloudML service through the Samsung Cloud Platform Console.

Reference
If the CloudML service status is Creating, Updating, or Terminating, the service cannot be canceled.

To cancel CloudML, follow these steps.

  1. Click on all services > AI/ML > CloudML menu. It moves to the Service Home page of CloudML.
  2. Service Home page, click the service cancellation button. A service cancellation notification window appears.
  3. Enter the CloudML name to be deleted in the notification window and click the Confirm button.

1 - Kubernetes Cluster Configuration

Configuring a Kubernetes Cluster

To apply for the CloudML service, a dedicated cluster for CloudML only must be configured. A dedicated cluster means creating a Kubernetes Engine with the required minimum specifications or higher and setting a few necessary requirements. Create a dedicated cluster before applying for the CloudML service.

  • The way to create a cluster is to refer to the Cluster Configuration guide.
  • CloudML exposes an HTTPS endpoint on port 443. Select the public endpoint when creating a cluster.

Cluster Node and Storage Recommended Specifications

Cluster nodes can be added or modified after the cluster is created. The following are the recommended specifications for the cluster nodes and storage that should be prepared to install CloudML based on 5 users.

DivisionItemRoleCapacity
Cluster NodeKubernetes Node Pool (Virtual Server)Application Execution
  • node.kubernetes.io/nodetype: ml-app
24 core / 96 GB
Cluster NodeKubernetes Node Pool (Virtual Server)Analysis Execution
  • node.kubernetes.io/nodetype: ml-analytics
8 core / 32 GBi x 2 EA
  • Total 16 core / 64 GBi
RepositoryFile StorageData Storage1 TB
Table. Recommended Specifications for Cluster Nodes and Storage
Notice

If you need to change the number of nodes, add GPU nodes, or scale up resources, please request technical support.

Adding Labels to Nodes

Add labels to nodes directly based on the roles presented in the recommended specifications for cluster nodes and storage.

To add a label to a cluster node, follow these steps.

  1. Click all services > Container > Kubernetes Engine menu. It moves to the Service Home page of Kubernetes Engine.
  2. On the Service Home page, click the Node menu. It moves to the Node List page.
  3. On the Node List page, select the cluster you want to check detailed information from the Gear button at the top left, then click the Confirm button.
  4. Select and click the node you want to check the detailed information of. It will move to the Node Details page.
  5. Click the Node Details page YAML tab. Move to the YAML tab page.
  6. Click the Edit button on the YAML tab page. The node editing window opens.
  7. In the node editing window, add a label that matches the role and click the Save button.
    • Check the following information and add labels that match the node specifications.
      DivisionPurpose-based Label
      CPU Node
      • For app: node.kubernetes.io/nodetype: ml-app
      • For analytics: node.kubernetes.io/nodetype: ml-analytics
      GPU node
      • For analysis: node.kubernetes.io/nodetype: ml-analytics-gpu
      • For copilot: node.kubernetes.io/nodetype: ml-gpu
      Table. Kubernetes node labels by purpose