Create the prediction cluster

You must deploy your prediction custom resources in the prediction cluster that the Infrastructure Operator (IO) creates for you. The operator creates prediction workloads in this same cluster.

To create the prediction cluster, work with the IO to associate your prediction project and allocate the node pools needed for online predictions in Google Distributed Cloud (GDC) air-gapped.

To create a prediction cluster, perform the following steps:

  1. Identify the project in your organization that you want to associate with the new cluster for online predictions.

    To create a project, see Set up a project for Vertex AI. You need your project ID when making API calls.

  2. From the list of available machine types in Distributed Cloud, choose the machine type for the nodes that your workloads need in the cluster.

    The machine type you choose depends on your prediction model size and complexity and determines the compute and graphic processing unit (GPU) resources your IO provides to the cluster. Follow node selection recommendations when selecting the machine type for your nodes.

  3. Email the IO using the prediction cluster case template to open a case and address your request to create the cluster.

  4. If necessary, communicate with the IO until they finish creating the prediction cluster associated with your project and assigning the appropriate node pools within the cluster.

After completing cluster provisioning, the prediction cluster is ready for online predictions.

Node selection recommendations

When the IO creates node pools in a cluster, they assign one of the available machine types in Distributed Cloud to provide a predefined set of resources for the worker nodes. Depending on the model size and complexity, you require different computing performances and, consequently, a specific amount of CPU, memory, and GPU. You must provide these details in your communication with the IO when you want to create a prediction cluster.

When you determine with the IO the machine type for node pools that you require in the prediction cluster, you must adhere to the following practices:

  • Distributed Cloud adds computing overhead to the nodes for mandatory system components. Therefore, you must choose a larger machine type for your node pools than the one you intend to use in the resource pool for your models.
  • Choose the solution that provides the minimum memory and computing resources necessary for your requirements. For example, if your model requires eight vCPUs, choose the n2-highcpu-8-gdc machine type, the smallest solution with eight vCPUs and 8 GB of memory in Distributed Cloud.
  • As you progress, consider higher performance solutions only if smaller solutions are not adequate for your needs and the size and complexity of the model. It's crucial to adhere to the principle of least privilege, using only the resources you need to execute your specific workflow. This responsible approach ensures considerate use of resources in the Distributed Cloud environment.
  • Only choose solutions that have GPUs if you require them for your model.
  • If your model requires GPUs, consider the a2-highgpu-1g-gdc machine type, the smallest solution providing GPUs.

Prediction cluster case template

Use the following template to send an email to your IO. The email opens a case to create the prediction cluster that you need for online predictions.

Good day,

I need to create a prediction cluster and associate it with a project in my organization to use online predictions.

Please use the following information for the creation of the cluster:

- **Cluster name:** vtx-ai-prediction
- **Name of the organization:** [Specify your organization's name.]
- **Project name:** [Specify the name of your project to associate with the prediction cluster.]
- **Machine type for the node pool:** [Specify the machine type you chose from the list of available machine types for the cluster nodes based on node selection recommendations. Please note that the IO can respond with a different suggestion based on your needs.]
- **Compute resources:** [Optionally, if you know how many compute resources your workloads need, describe them in this field.]
- **Memory resources:** [Optionally, if you know how many memory resources your workloads need, describe them in this field.]
- **GPU resources:** [Optionally, if you know how many GPU resources your workloads need, describe them in this field.]

**Note for IO:** Review the instructions to create the prediction cluster in the following section of the documentation: Operator > Configure the deployment > Create the Prediction cluster

Thank you,
[Your name]