Azure Machine Learning Workspace
This page shows how to write Terraform and Azure Resource Manager for Machine Learning Workspace and write them securely.
azurerm_machine_learning_workspace (Terraform)
The Workspace in Machine Learning can be configured in Terraform with the resource name azurerm_machine_learning_workspace
. The following sections describe 8 examples of how to use the resource and its parameters.
Example Usage from GitHub
resource "azurerm_machine_learning_workspace" "ml" {
name = join("-", ["ml", var.namespace, var.environment])
location = azurerm_resource_group.ml.location
resource_group_name = azurerm_resource_group.ml.name
application_insights_id = azurerm_application_insights.ml.id
key_vault_id = azurerm_key_vault.ml.id
resource "azurerm_machine_learning_workspace" "AML" {
name = "cloudquickpocs-aml-workspace"
location = azurerm_resource_group.AML.location
resource_group_name = azurerm_resource_group.AML.name
application_insights_id = azurerm_application_insights.AML.id
key_vault_id = azurerm_key_vault.AML.id
resource "azurerm_machine_learning_workspace" "mlw" {
name = var.machine_learning_workspace_name
location = var.resource_group_location
resource_group_name = var.resource_group_name
application_insights_id = azurerm_application_insights.appi.id
key_vault_id = var.key_vault_id
resource "azurerm_machine_learning_workspace" "mlworkspace" {
name = var.name
location = data.azurerm_resource_group.ml_resource_group.location
resource_group_name = var.resource_group_name
application_insights_id = var.application_insights_id
key_vault_id = var.key_vault_id
resource "azurerm_machine_learning_workspace" "mlw" {
name = var.machine_learning_workspace_name
location = azurerm_resource_group.rg.location
resource_group_name = azurerm_resource_group.rg.name
application_insights_id = azurerm_application_insights.appi.id
key_vault_id = azurerm_key_vault.kv.id
resource "azurerm_machine_learning_workspace" "this" {
name = var.workspace_name
location = var.location
resource_group_name = var.resource_group_name
application_insights_id = azurerm_application_insights.this.id
key_vault_id = var.key_vault_id
resource "azurerm_machine_learning_workspace" "ws" {
name = azurecaf_name.ws.result
location = var.location
resource_group_name = var.resource_group_name
application_insights_id = var.application_insights_id
key_vault_id = var.keyvault_id
resource "azurerm_machine_learning_workspace" "ws" {
name = azurecaf_name.ws.result
location = var.location
resource_group_name = var.resource_group_name
application_insights_id = var.application_insights_id
key_vault_id = var.keyvault_id
Parameters
-
application_insights_id
required - string -
container_registry_id
optional - string -
description
optional - string -
friendly_name
optional - string -
high_business_impact
optional - bool -
id
optional computed - string -
key_vault_id
required - string -
location
required - string -
name
required - string -
resource_group_name
required - string -
sku_name
optional - string -
storage_account_id
required - string -
tags
optional - map from string to string -
identity
list block-
principal_id
optional computed - string -
tenant_id
optional computed - string -
type
required - string
-
-
timeouts
single block
Explanation in Terraform Registry
Manages a Azure Machine Learning Workspace
Microsoft.MachineLearningServices/workspaces (Azure Resource Manager)
The workspaces in Microsoft.MachineLearningServices can be configured in Azure Resource Manager with the resource name Microsoft.MachineLearningServices/workspaces
. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
Parameters
apiVersion
required - stringidentity
optionaltype
optional - stringThe identity type.
userAssignedIdentities
optional - undefineddictionary containing all the user assigned identities, with resourceId of the UAI as key.
location
optional - stringSpecifies the location of the resource.
name
required - stringName of Azure Machine Learning workspace.
properties
requiredallowPublicAccessWhenBehindVnet
optional - booleanThe flag to indicate whether to allow public access when behind VNet.
applicationInsights
optional - stringARM id of the application insights associated with this workspace. This cannot be changed once the workspace has been created
containerRegistry
optional - stringARM id of the container registry associated with this workspace. This cannot be changed once the workspace has been created
description
optional - stringThe description of this workspace.
discoveryUrl
optional - stringUrl for the discovery service to identify regional endpoints for machine learning experimentation services
encryption
optionalidentity
optionaluserAssignedIdentity
optional - stringThe ArmId of the user assigned identity that will be used to access the customer managed key vault
keyVaultProperties
requiredidentityClientId
optional - stringFor future use - The client id of the identity which will be used to access key vault.
keyIdentifier
required - stringKey vault uri to access the encryption key.
keyVaultArmId
required - stringThe ArmId of the keyVault where the customer owned encryption key is present.
status
required - stringIndicates whether or not the encryption is enabled for the workspace.
friendlyName
optional - stringThe friendly name for this workspace. This name in mutable
hbiWorkspace
optional - booleanThe flag to signal HBI data in the workspace and reduce diagnostic data collected by the service
imageBuildCompute
optional - stringThe compute name for image build
keyVault
optional - stringARM id of the key vault associated with this workspace. This cannot be changed once the workspace has been created
primaryUserAssignedIdentity
optional - stringThe user assigned identity resource id that represents the workspace identity.
publicNetworkAccess
optional - stringWhether requests from Public Network are allowed.
serviceManagedResourcesSettings
optionalcosmosDb
optionalcollectionsThroughput
optional - integerThe throughput of the collections in cosmosdb database
sharedPrivateLinkResources
optional arrayname
optional - stringUnique name of the private link.
properties
optionalgroupId
optional - stringThe private link resource group id.
privateLinkResourceId
optional - stringThe resource id that private link links to.
requestMessage
optional - stringRequest message.
status
optional - stringIndicates whether the connection has been Approved/Rejected/Removed by the owner of the service.
storageAccount
optional - stringARM id of the storage account associated with this workspace. This cannot be changed once the workspace has been created
sku
optionalname
optional - stringName of the sku
tier
optional - stringTier of the sku like Basic or Enterprise
systemData
optionalcreatedAt
optional - stringThe timestamp of resource creation (UTC).
createdBy
optional - stringThe identity that created the resource.
createdByType
optional - stringThe type of identity that created the resource.
lastModifiedAt
optional - stringThe timestamp of resource last modification (UTC)
lastModifiedBy
optional - stringThe identity that last modified the resource.
lastModifiedByType
optional - stringThe type of identity that last modified the resource.
tags
optional - stringContains resource tags defined as key/value pairs.
type
required - string
Frequently asked questions
What is Azure Machine Learning Workspace?
Azure Machine Learning Workspace is a resource for Machine Learning of Microsoft Azure. Settings can be wrote in Terraform.
Where can I find the example code for the Azure Machine Learning Workspace?
For Terraform, the dmaxim/terrademo, seeewhy/PythonHacks and FabLabGent/InfrastructureFabLabGent source code examples are useful. See the Terraform Example section for further details.