CLI (v2) workspace YAML schema

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APPLIES TO: Azure CLI ml extension v2 (current)

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

Note

The YAML syntax detailed in this document is based on the JSON schema for the latest version of the ML CLI v2 extension. This syntax is guaranteed only to work with the latest version of the ML CLI v2 extension. You can find the schemas for older extension versions at https://azuremlschemasprod.azureedge.net/.

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 Azure-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

$schema: https://azuremlschemas.azureedge.net/latest/workspace.schema.json
name: mlw-basic-prod
location: chinaeast2
display_name: Basic workspace-example
description: This example shows a YML configuration for a basic workspace. In case you use this configuration to deploy a new workspace, since no existing dependent resources are specified, these will be automatically created.
hbi_workspace: false
tags:
  purpose: demonstration

YAML: with existing resources

$schema: https://azuremlschemas.azureedge.net/latest/workspace.schema.json
name: mlw-basicex-prod
location: chinaeast2
display_name: Bring your own dependent resources-example
description: This configuration specifies a workspace configuration with existing dependent resources
storage_account: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.Storage/storageAccounts/<STORAGE_ACCOUNT>
container_registry: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.ContainerRegistry/registries/<CONTAINER_REGISTRY>
key_vault: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.KeyVault/vaults/<KEY_VAULT>
application_insights: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.insights/components/<APP_INSIGHTS>
tags:
  purpose: demonstration

YAML: customer-managed key

$schema: https://azuremlschemas.azureedge.net/latest/workspace.schema.json
name: mlw-cmkexample-prod
location: chinaeast2
display_name: Customer managed key encryption-example
description: This configurations shows how to create a workspace that uses customer-managed keys for encryption.
customer_managed_key: 
  key_vault: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.KeyVault/vaults/<KEY_VAULT>
  key_uri: https://<KEY_VAULT>.vault.azure.cn/keys/<KEY_NAME>/<KEY_VERSION>
tags:
  purpose: demonstration

$schema: https://azuremlschemas.azureedge.net/latest/workspace.schema.json
name: mlw-privatelink-prod
location: chinaeast2
display_name: Private Link endpoint workspace-example
description: When using private link, you must set the image_build_compute property to a cluster name to use for Docker image environment building. You can also specify whether the workspace should be accessible over the internet.
image_build_compute: cpu-compute
public_network_access: Disabled
tags:
  purpose: demonstration

YAML: high business impact

$schema: https://azuremlschemas.azureedge.net/latest/workspace.schema.json
name: mlw-hbiexample-prod
location: chinaeast2
display_name: High business impact-example
description: This configuration shows how to configure a workspace with the hbi flag enabled. This flag specifies whether to reduce telemetry collection and enable additional encryption when high-business-impact data is used.
hbi_workspace: true
tags:
  purpose: demonstration

YAML: managed network with allow internet outbound

name: myworkspace_aio
managed_network:
  isolation_mode: allow_internet_outbound
  outbound_rules:
  - name: added-perule
    type: private_endpoint
    destination:
      service_resource_id: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/MyGroup/providers/Microsoft.Storage/storageAccounts/MyAccount1
      spark_enabled: true
      subresource_target: blob
  - name: added-perule2
    type: private_endpoint
    destination:
      service_resource_id: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/MyGroup/providers/Microsoft.Storage/storageAccounts/MyAccount2
      spark_enabled: true
      subresource_target: file

YAML: managed network with allow only approved outbound

name: myworkspace_dep
managed_network:
  isolation_mode: allow_only_approved_outbound
  outbound_rules:
  - name: added-servicetagrule
    type: service_tag
    destination:
      port_ranges: 80, 8080
      protocol: TCP
      service_tag: DataFactory
  - name: added-perule
    type: private_endpoint
    destination:
      service_resource_id: /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/MyGroup/providers/Microsoft.Storage/storageAccounts/MyAccount2
      spark_enabled: true
      subresource_target: blob
  - name: added-fqdnrule
    type: fqdn
    destination: 'test2.com'

Next steps