Azure Machine Learning Compute Cluster

azurerm_machine_learning_compute_cluster (Terraform)

The Compute Cluster in Machine Learning can be configured in Terraform with the resource name azurerm_machine_learning_compute_cluster. The following sections describe 2 examples of how to use the resource and its parameters.

Example Usage from GitHub

SSC-DSAI/terraform-modules

resource "azurerm_machine_learning_compute_cluster" "test" {
  name                          = var.cluster_name
  location                      = var.location
  vm_priority                   = var.vm_priority
  vm_size                       = var.vm_size
  machine_learning_workspace_id = azurerm_machine_learning_workspace.this.id

toby-htx/nus-devops-course

resource "azurerm_machine_learning_compute_cluster" "example" {
  name                          = "example"
  location                      = "Southeast Asia"
  vm_priority                   = "LowPriority"
  vm_size                       = "Standard_NV6"
  machine_learning_workspace_id = azurerm_machine_learning_workspace.example.id

Parameters

The following arguments are supported:

• name - (Required) The name which should be used for this Machine Learning Compute Cluster. Changing this forces a new Machine Learning Compute Cluster to be created.

• machine_learning_workspace_id - (Required) The ID of the Machine Learning Workspace. Changing this forces a new Machine Learning Compute Cluster to be created.

• location - (Required) The Azure Region where the Machine Learning Compute Cluster should exist. Changing this forces a new Machine Learning Compute Cluster to be created.

• vm_priority - (Required) The priority of the VM. Changing this forces a new Machine Learning Compute Cluster to be created. Accepted values are Dedicated and LowPriority.

• vm_size - (Required) The size of the VM. Changing this forces a new Machine Learning Compute Cluster to be created.

• scale_settings - (Required) A scale_settings block as defined below. Changing this forces a new Machine Learning Compute Cluster to be created.

• ssh - (Optional) Credentials for an administrator user account that will be created on each compute node. A ssh block as defined below. Changing this forces a new Machine Learning Compute Cluster to be created.

• description - (Optional) The description of the Machine Learning compute. Changing this forces a new Machine Learning Compute Cluster to be created.

• identity - (Optional) An identity block as defined below. Changing this forces a new Machine Learning Compute Cluster to be created.

• local_auth_enabled - (Optional) Whether local authentication methods is enabled. Defaults to true. Changing this forces a new Machine Learning Compute Cluster to be created.

• ssh_public_access_enabled - (Optional) A boolean value indicating whether enable the public SSH port. Changing this forces a new Machine Learning Compute Cluster to be created.

• subnet_resource_id - (Optional) The ID of the Subnet that the Compute Cluster should reside in. Changing this forces a new Machine Learning Compute Cluster to be created.

• tags - (Optional) A mapping of tags which should be assigned to the Machine Learning Compute Cluster. Changing this forces a new Machine Learning Compute Cluster to be created.

A identity block supports the following:

• type - (Required) The Type of Identity which should be used for this Machine Learning Compute Cluster. Possible values are SystemAssigned, UserAssigned and SystemAssigned,UserAssigned. Changing this forces a new Machine Learning Compute Cluster to be created.

• identity_ids - (Optional) A list of User Managed Identity ID's which should be assigned to the Machine Learning Compute Cluster. Changing this forces a new Machine Learning Compute Cluster to be created.

A ssh block supports the following:

• admin_username - (Required) Name of the administrator user account which can be used to SSH to nodes. Changing this forces a new Machine Learning Compute Cluster to be created.

• admin_password - (Optional) Password of the administrator user account. Changing this forces a new Machine Learning Compute Cluster to be created.

• key_value - (Optional) SSH public key of the administrator user account. Changing this forces a new Machine Learning Compute Cluster to be created.

A scale_settings block supports the following:

• max_node_count - (Required) Maximum node count. Changing this forces a new Machine Learning Compute Cluster to be created.

• min_node_count - (Required) Minimal node count. Changing this forces a new Machine Learning Compute Cluster to be created.

• scale_down_nodes_after_idle_duration - (Required) Node Idle Time Before Scale Down: defines the time until the compute is shutdown when it has gone into Idle state. Is defined according to W3C XML schema standard for duration. Changing this forces a new Machine Learning Compute Cluster to be created.

In addition to the Arguments listed above - the following Attributes are exported:

• id - The ID of the Machine Learning Compute Cluster.

• identity - An identity block as defined below, which contains the Managed Service Identity information for this Machine Learning Compute Cluster.

A identity block exports the following:

• principal_id - The Principal ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Compute Cluster.

• tenant_id - The Tenant ID for the Service Principal associated with the Managed Service Identity of this Machine Learning Compute Cluster.

Explanation in Terraform Registry

Manages a Machine Learning Compute Cluster. NOTE: At this point in time the resource cannot be updated (not supported by the backend Azure Go SDK). Therefore it can only be created and deleted, not updated. At the moment, there is also no possibility to specify ssh User Account Credentials to ssh into the compute cluster.