title | titleSuffix | description | services | ms.service | ms.subservice | ms.custom | ms.topic | author | ms.author | ms.date | ms.reviewer | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
CLI (v2) Data Lake Store Gen 2 connection YAML schema |
Azure Machine Learning |
Reference documentation for the CLI (v2) Azure Data Lake Store Gen 2 connections YAML schema. |
machine-learning |
machine-learning |
core |
|
reference |
Blackmist |
larryfr |
05/09/2024 |
ambadal |
[!INCLUDE cli v2]
[!INCLUDE schema note]
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. |
||
name |
string | Required. The connection name. | ||
description |
string | The connection description. | ||
tags |
object | The connection tag dictionary. | ||
type |
string | Required. The connection type. | azure_data_lake_gen2 |
azure_data_lake_gen2 |
is_shared |
boolean | true if the connection is shared across other projects in the hub; otherwise, false . |
true |
|
target |
string | Required. The URL of the blob container. | ||
credentials |
object | Credential-based authentication to access Azure Data Lake Store Gen 2. A service principal can be used. Don't specify credentials when using credential-less authentication, set to None . |
||
credentials.type |
string | The type of credential. | service_principal |
|
credentials.client_id |
string | Microsoft Entra ID application ID. | ||
credentials.client_secret |
string | Secret or key. | ||
credentials.tenant_id |
string | Microsoft Entra ID tenant ID. |
While the az ml connection
commands can be used to manage both Azure Machine Learning and Azure AI Studio connections, the Azure Data Lake Store Gen 2 connection is specific to Azure AI Studio.
Visit this GitHub resource for examples. Several are shown here. These examples would be in the form of YAML files and used from the CLI. For example, az ml connection create -f <file-name>.yaml
.
#Connection.yml
name: myadlsgen2_sp
type: azure_data_lake_gen2
target: https://contoso.core.windows.net/contosocontainer
credentials:
type: service_principal
tenant_id: "XXXXXXXXXX"
client_id: "XXXXXXXXXX"
client_secret: "XXXXXXXXXX"
#Connection.yml
name: myadlsgen2_cl
type: azure_data_lake_gen2
target: https://contoso.core.windows.net/contosocontainer