CLI (v2) Azure Blob datastore YAML schema

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APPLIES TO: Azure CLI ml extension v2 (current)

See the source JSON schema at https://azuremlschemas.azureedge.net/latest/azureBlob.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 Visual Studio Code extension to author the YAML file, include $schema at the top of your file to invoke schema and resource completions.
type string Required. The datastore type. azure_blob
name string Required. The datastore name.
description string The datastore description.
tags object The datastore tag dictionary.
account_name string Required. The Azure storage account name.
container_name string Required. The container name.
endpoint string The endpoint suffix of the storage service, used for creation of the storage account endpoint URL. It combines the storage account name and endpoint. Example storage account URL: https://<storage-account-name>.blob.core.chinacloudapi.cn. core.chinacloudapi.cn
protocol string Protocol for connection to the container. https, wasbs https
credentials object Credential-based authentication credentials for connection to the Azure storage account. An account key or a shared access signature (SAS) token will work. The workspace key vault stores the credential secrets.
credentials.account_key string The account key used for storage account access. One of credentials.account_key or credentials.sas_token is required if credentials is specified.
credentials.sas_token string The SAS token for accessing the storage account. One of credentials.account_key or credentials.sas_token is required if credentials is specified.

Remarks

You can use the az ml datastore command to manage Azure Machine Learning datastores.

Examples

Visit this GitHub resource for examples. Several are shown here:

YAML: identity-based access

$schema: https://azuremlschemas.azureedge.net/latest/azureBlob.schema.json
name: blob_credless_example
type: azure_blob
description: Credential-less datastore pointing to a blob container.
account_name: mytestblobstore
container_name: data-container

YAML: account key

$schema: https://azuremlschemas.azureedge.net/latest/azureBlob.schema.json
name: blob_example
type: azure_blob
description: Datastore pointing to a blob container.
account_name: mytestblobstore
container_name: data-container
credentials:
  account_key: XXXxxxXXXxXXXXxxXXXXXxXXXXXxXxxXxXXXxXXXxXXxxxXXxxXXXxXxXXXxxXxxXXXXxxxxxXXxxxxxxXXXxXXX

YAML: wasbs protocol

$schema: https://azuremlschemas.azureedge.net/latest/azureBlob.schema.json
name: blob_protocol_example
type: azure_blob
description: Datastore pointing to a blob container using wasbs protocol.
account_name: mytestblobstore
protocol: wasbs
container_name: data-container
credentials:
  account_key: XXXxxxXXXxXXXXxxXXXXXxXXXXXxXxxXxXXXxXXXxXXxxxXXxxXXXxXxXXXxxXxxXXXXxxxxxXXxxxxxxXXXxXXX

YAML: sas token

$schema: https://azuremlschemas.azureedge.net/latest/azureBlob.schema.json
name: blob_sas_example
type: azure_blob
description: Datastore pointing to a blob container using SAS token.
account_name: mytestblobstore
container_name: data-container
credentials:
  sas_token: ?xx=XXXX-XX-XX&xx=xxxx&xxx=xxx&xx=xxxxxxxxxxx&xx=XXXX-XX-XXXXX:XX:XXX&xx=XXXX-XX-XXXXX:XX:XXX&xxx=xxxxx&xxx=XXxXXXxxxxxXXXXXXXxXxxxXXXXXxxXXXXXxXXXXxXXXxXXxXX

Next steps