machinelearning¶

This provider is a derived work of the Terraform Provider distributed under MPL 2.0. If you encounter a bug or missing feature, first check the pulumi/pulumi-azure repo; however, if that doesn’t turn up anything, please consult the source terraform-providers/terraform-provider-azurerm repo.

class pulumi_azure.machinelearning.AwaitableGetWorkspaceResult(id=None, location=None, name=None, resource_group_name=None, tags=None)¶

class pulumi_azure.machinelearning.GetWorkspaceResult(id=None, location=None, name=None, resource_group_name=None, tags=None)¶

A collection of values returned by getWorkspace.

id = None¶

The provider-assigned unique ID for this managed resource.

location = None¶

The location where the Machine Learning Workspace exists.

tags = None¶

A mapping of tags assigned to the Machine Learning Workspace.

class pulumi_azure.machinelearning.Workspace(resource_name, opts=None, application_insights_id=None, container_registry_id=None, description=None, friendly_name=None, identity=None, key_vault_id=None, location=None, name=None, resource_group_name=None, sku_name=None, storage_account_id=None, tags=None, __props__=None, __name__=None, __opts__=None)¶

Manages a Azure Machine Learning Workspace

import pulumi
import pulumi_azure as azure

current = azure.core.get_client_config()
example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West Europe")
example_insights = azure.appinsights.Insights("exampleInsights",
    location=example_resource_group.location,
    resource_group_name=example_resource_group.name,
    application_type="web")
example_key_vault = azure.keyvault.KeyVault("exampleKeyVault",
    location=example_resource_group.location,
    resource_group_name=example_resource_group.name,
    tenant_id=current.tenant_id,
    sku_name="premium")
example_account = azure.storage.Account("exampleAccount",
    location=example_resource_group.location,
    resource_group_name=example_resource_group.name,
    account_tier="Standard",
    account_replication_type="GRS")
example_workspace = azure.machinelearning.Workspace("exampleWorkspace",
    location=example_resource_group.location,
    resource_group_name=example_resource_group.name,
    application_insights_id=example_insights.id,
    key_vault_id=example_key_vault.id,
    storage_account_id=example_account.id,
    identity={
        "type": "SystemAssigned",
    })

Parameters

• resource_name (str) – The name of the resource.

• opts (pulumi.ResourceOptions) – Options for the resource.

• application_insights_id (pulumi.Input[str]) – The ID of the Application Insights associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• container_registry_id (pulumi.Input[str]) – The ID of the container registry associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• description (pulumi.Input[str]) – The description of this Machine Learning Workspace.

• friendly_name (pulumi.Input[str]) – Friendly name for this Machine Learning Workspace.

• identity (pulumi.Input[dict]) – An identity block defined below.

• key_vault_id (pulumi.Input[str]) – The ID of key vault associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• location (pulumi.Input[str]) – Specifies the supported Azure location where the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

• name (pulumi.Input[str]) – Specifies the name of the Machine Learning Workspace. Changing this forces a new resource to be created.

• resource_group_name (pulumi.Input[str]) – Specifies the name of the Resource Group in which the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

• sku_name (pulumi.Input[str]) – SKU/edition of the Machine Learning Workspace, possible values are Basic for a basic workspace or Enterprise for a feature rich workspace. Defaults to Basic.

• storage_account_id (pulumi.Input[str]) – The ID of the Storage Account associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• tags (pulumi.Input[dict]) – A mapping of tags to assign to the resource. Changing this forces a new resource to be created.

The identity object supports the following:

• principal_id (pulumi.Input[str]) - The (Client) ID of the Service Principal.

• tenant_id (pulumi.Input[str]) - The ID of the Tenant the Service Principal is assigned in.

• type (pulumi.Input[str]) - The Type of Identity which should be used for this Disk Encryption Set. At this time the only possible value is SystemAssigned.

application_insights_id: pulumi.Output[str] = None¶

The ID of the Application Insights associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

container_registry_id: pulumi.Output[str] = None¶

The ID of the container registry associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

description: pulumi.Output[str] = None¶

The description of this Machine Learning Workspace.

friendly_name: pulumi.Output[str] = None¶

Friendly name for this Machine Learning Workspace.

identity: pulumi.Output[dict] = None¶

An identity block defined below.

• principal_id (str) - The (Client) ID of the Service Principal.

• tenant_id (str) - The ID of the Tenant the Service Principal is assigned in.

• type (str) - The Type of Identity which should be used for this Disk Encryption Set. At this time the only possible value is SystemAssigned.

key_vault_id: pulumi.Output[str] = None¶

The ID of key vault associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

location: pulumi.Output[str] = None¶

Specifies the supported Azure location where the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

name: pulumi.Output[str] = None¶

Specifies the name of the Machine Learning Workspace. Changing this forces a new resource to be created.

resource_group_name: pulumi.Output[str] = None¶

Specifies the name of the Resource Group in which the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

sku_name: pulumi.Output[str] = None¶

SKU/edition of the Machine Learning Workspace, possible values are Basic for a basic workspace or Enterprise for a feature rich workspace. Defaults to Basic.

storage_account_id: pulumi.Output[str] = None¶

The ID of the Storage Account associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

tags: pulumi.Output[dict] = None¶

A mapping of tags to assign to the resource. Changing this forces a new resource to be created.

static get(resource_name, id, opts=None, application_insights_id=None, container_registry_id=None, description=None, friendly_name=None, identity=None, key_vault_id=None, location=None, name=None, resource_group_name=None, sku_name=None, storage_account_id=None, tags=None)¶

Get an existing Workspace resource’s state with the given name, id, and optional extra properties used to qualify the lookup.

Parameters

• resource_name (str) – The unique name of the resulting resource.

• id (str) – The unique provider ID of the resource to lookup.

• opts (pulumi.ResourceOptions) – Options for the resource.

• application_insights_id (pulumi.Input[str]) – The ID of the Application Insights associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• container_registry_id (pulumi.Input[str]) – The ID of the container registry associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• description (pulumi.Input[str]) – The description of this Machine Learning Workspace.

• friendly_name (pulumi.Input[str]) – Friendly name for this Machine Learning Workspace.

• identity (pulumi.Input[dict]) – An identity block defined below.

• key_vault_id (pulumi.Input[str]) – The ID of key vault associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• location (pulumi.Input[str]) – Specifies the supported Azure location where the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

• name (pulumi.Input[str]) – Specifies the name of the Machine Learning Workspace. Changing this forces a new resource to be created.

• resource_group_name (pulumi.Input[str]) – Specifies the name of the Resource Group in which the Machine Learning Workspace should exist. Changing this forces a new resource to be created.

• sku_name (pulumi.Input[str]) – SKU/edition of the Machine Learning Workspace, possible values are Basic for a basic workspace or Enterprise for a feature rich workspace. Defaults to Basic.

• storage_account_id (pulumi.Input[str]) – The ID of the Storage Account associated with this Machine Learning Workspace. Changing this forces a new resource to be created.

• tags (pulumi.Input[dict]) – A mapping of tags to assign to the resource. Changing this forces a new resource to be created.

The identity object supports the following:

• principal_id (pulumi.Input[str]) - The (Client) ID of the Service Principal.

• tenant_id (pulumi.Input[str]) - The ID of the Tenant the Service Principal is assigned in.

• type (pulumi.Input[str]) - The Type of Identity which should be used for this Disk Encryption Set. At this time the only possible value is SystemAssigned.

translate_output_property(prop)¶

Provides subclasses of Resource an opportunity to translate names of output properties into a format of their choosing before writing those properties to the resource object.

Parameters

prop (str) – A property name.

Returns

A potentially transformed property name.

Return type

str

translate_input_property(prop)¶

Provides subclasses of Resource an opportunity to translate names of input properties into a format of their choosing before sending those properties to the Pulumi engine.

Parameters

prop (str) – A property name.

Returns

A potentially transformed property name.

Return type

str

pulumi_azure.machinelearning.get_workspace(name=None, resource_group_name=None, opts=None)¶

Use this data source to access information about an existing Machine Learning Workspace.

import pulumi
import pulumi_azure as azure

existing = azure.machinelearning.get_workspace(name="example-workspace",
    resource_group_name="example-resources")
pulumi.export("id", azurerm_machine_learning_workspace["existing"]["id"])

Parameters

• name (str) – The name of the Machine Learning Workspace exists.

• resource_group_name (str) – The name of the Resource Group where the Machine Learning Workspace exists.