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.

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 labels to a node YAML, see the Editing Node YAML guide.

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.

     Division	Purpose-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