Step #3: Associate the VM Class with the Supervisor Namespace

Optimize AI and Data Science Workloads (VMware Tanzu) (Latest Version)

Now that you have created a VM class, next we will associate it with the Supervisor Namespace. A VM class can be added to one or more namespaces on a Supervisor Cluster, and a Supervisor Cluster can have one or more VM Classes. The Supervisor Namespace will have multiple VM classes for most deployments to properly scale Kubernetes clusters.

  1. From vCenter, navigate to Inventory.

  2. Expand your Tanzu Cluster and associated Namespace.

  3. Select the Namespace and click on Add VM Class or Manage VM Classes.


  4. From the Add VM Class or Manage VM Classes pop up, select the check box next to the VM class you previously created and the prebuilt guaranteed-medium VM class. You can select one or many VM classes, dependent on how you choose to architect your deployment.


    The VM class, vm-class-t4-16gb, created in Create a GPU Accelerated VM Class, is listed above.

  5. Validate that the Content Library is associated with the Supervisor Namespace; click on Add Content Library in the VM Service card.


  6. From the Add Content Library pop-up, select the check box for the Subscribed Content Library, which will contain the VM Template to be used by NVIDIA AI Enterprise.


VMware provides the VM Template, which NVIDIA AI Enterprise uses within the subscriber content library.


DevOps Engineer(s) need access to the VM class to deploy a Tanzu Kubernetes cluster in the newly created Namespace. vSphere administrators must explicitly associate VM classes to any new namespaces where the Tanzu Kubernetes cluster is deployed.

Using the step above, a vSphere IT Administrator would typically start the initial provisioning of the Tanzu environment by creating required components associated with NVIDIA vGPU devices. Once this initial provisioning is complete, the DevOps Engineer will typically set up and interact with kubectl and install the required NVIDIA AI Enterprise elements such as GPU and Network Operators. You will do both vSphere IT Administrator and DevOps tasks for this curated lab. This mechanism allows IT admins to control access to hardware resources such as CPU, RAM, GPU and Network devices by DevOps Engineers(s).

© Copyright 2022-2023, NVIDIA. Last updated on Apr 13, 2023.