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title titleSuffix description services ms.service ms.subservice ms.topic ms.custom author ms.author ms.date ms.reviewer
CLI (v2) workspace YAML schema
Azure Machine Learning
Reference documentation for the CLI (v2) workspace YAML schema.
machine-learning
machine-learning
core
reference
cliv2
deeikele
deeikele
10/21/2021
scottpolly

CLI (v2) workspace YAML schema

[!INCLUDE cli v2]

The source JSON schema can be found at https://azuremlschemas.azureedge.net/latest/workspace.schema.json.

[!INCLUDE schema note]

YAML syntax

Key Type Description Allowed values Default value
$schema string The YAML schema. If you use the Azure Machine Learning VS Code extension to author the YAML file, including $schema at the top of your file enables you to invoke schema and resource completions.
name string Required. Name of the workspace.
display_name string Display name of the workspace in the studio UI. Can be non-unique within the resource group.
description string Description of the workspace.
tags object Dictionary of tags for the workspace.
location string The location of the workspace. If omitted, defaults to the resource group location.
resource_group string Required. The resource group containing the workspace. If the resource group does not exist, a new one will be created.
hbi_workspace boolean Whether the customer data is of high business impact (HBI), containing sensitive business information. For more information, see Data encryption at rest. false
storage_account string The fully qualified resource ID of an existing Azure storage account to use as the default storage account for the workspace. A storage account with premium storage or hierarchical namespace cannot be used as the default storage account. If omitted, a new storage account will be created.
container_registry string The fully qualified resource ID of an existing Azure container registry to use as the default container registry for the workspace. Azure Machine Learning uses Azure Container Registry (ACR) for managing container images used for training and deployment. If omitted, a new container registry will be created. Creation is lazy loaded, so the container registry gets created the first time it is needed for an operation for either training or deployment.
key_vault string The fully qualified resource ID of an existing Azure key vault to use as the default key vault for the workspace. If omitted, a new key vault will be created.
application_insights string The fully qualified resource ID of an existing Azure application insights to use as the default application insights for the workspace. If omitted, a new application insights will be created.
customer_managed_key object Azure Machine Learning stores metadata in an Azure Cosmos DB instance. By default the data is encrypted at rest with Microsoft-managed keys. To use your own customer-managed key for encryption, specify the customer-managed key information in this section. For more information, see Data encryption for Azure Cosmos DB.
customer_managed_key.key_vault string The fully qualified resource ID of the key vault containing the customer-managed key. This key vault can be different than the default workspace key vault specified in key_vault.
customer_managed_key.key_uri string The key URI of the customer-managed key to encrypt data at rest. The URI format is https://<keyvault-dns-name>/keys/<key-name>/<key-version>.
image_build_compute string Name of the compute target to use for building environment Docker images when the container registry is behind a VNet. For more information, see Secure workspace resources behind VNets.
public_network_access string Whether public endpoint access is allowed if the workspace will be using Private Link. For more information, see Enable public access when behind VNets. enabled, disabled disabled
managed_network object Azure Machine Learning Workspace managed network isolation. For more information, see Workspace managed network isolation.

Remarks

The az ml workspace command can be used for managing Azure Machine Learning workspaces.

Examples

Examples are available in the examples GitHub repository. Several are shown below.

YAML: basic

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/basic.yml":::

YAML: with existing resources

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/with-existing-resources.yml":::

YAML: customer-managed key

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/cmk.yml":::

YAML: private link

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/privatelink.yml":::

YAML: high business impact

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/hbi.yml":::

YAML: managed network with allow internet outbound

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/mvnet-allow-internet-outbound.yml":::

YAML: managed network with allow only approved outbound

:::code language="yaml" source="~/azureml-examples-main/cli/resources/workspace/mvnet-allow-only-approved-outbound.yml":::

Next steps