How to fix ML_Client can not connect to the workspace

Question

Hi there,

I am trying to connect the ML workspace on my notebook.

Here's my code

# import required libraries
from azure.ai.ml import MLClient
from azure.ai.ml.entities import Environment, BuildContext
from azure.identity import DefaultAzureCredential


# Enter details of your AML workspace
subscription_id = ""
resource_group = ""
workspace = ""

# get a handle to the workspace
ml_client = MLClient(
    DefaultAzureCredential(), subscription_id, resource_group, workspace
)

Then I got the following errors

ClientAuthenticationError: DefaultAzureCredential failed to retrieve a token from the included credentials. Attempted credentials: EnvironmentCredential: EnvironmentCredential authentication unavailable. Environment variables are not fully configured. Visit 

Any suggestion?

Thanks&Regards,

zmsoft

Answer 1

Hello @zmsoft ,

Thank you for reaching out on Microsoft Q&A. I apologize for any inconvenience you may be experiencing.

The error message you are encountering suggests that the DefaultAzureCredential is unable to authenticate due to improperly configured environment variables. The DefaultAzureCredential class attempts to authenticate using multiple methods in a specific order, and it appears that the environment variables required for the EnvironmentCredential method are not set up correctly.

To help you troubleshoot and resolve this issue, please follow these steps:

1. Set Up Environment Variables: To utilize EnvironmentCredential, you need to configure the following environment variables with your Azure service principal credentials:

• AZURE_CLIENT_ID: The client ID of your Azure service principal.
• AZURE_TENANT_ID: The tenant ID of your Azure Active Directory.
• AZURE_CLIENT_SECRET: The client secret of your Azure service principal.

You can set these environment variables directly in your notebook or through your operating system. Here’s an example of how to set them in Python:

import os
os.environ["AZURE_CLIENT_ID"] = "<your-client-id>"
os.environ["AZURE_TENANT_ID"] = "<your-tenant-id>"
os.environ["AZURE_CLIENT_SECRET"] = "<your-client-secret>"

2. Use Azure CLI Authentication: If you have the Azure CLI installed and are logged in, you can opt for AzureCliCredential, which does not require setting environment variables:

from azure.identity import AzureCliCredential
ml_client = MLClient(
    AzureCliCredential(), subscription_id, resource_group, workspace)

1. Check Azure Role Assignments: Ensure that the service principal or user account you are using has the necessary permissions to access the Azure Machine Learning workspace. Typically, the role should be set to "Contributor" or "Owner" for the resource group or workspace.
2. Verify Subscription and Resource Group: Double-check that the subscription_id, resource_group, and workspace variables are correctly configured and correspond to the Azure resources you are trying to access.
3. Test Authentication: You can verify if the authentication is functioning correctly by attempting to list the workspaces in your subscription:

from azure.ai.ml import MLClient
from azure.identity import DefaultAzureCredential
credential = DefaultAzureCredential()
ml_client = MLClient(credential, subscription_id, resource_group)
# List workspaces
workspaces = ml_client.workspaces.list()
for ws in workspaces:
    print(ws.name)

You can refer the below docs for your reference:

• Azure Identity Library for Python
• Azure Machine Learning SDK for Python

By following these steps, you should be able to resolve the authentication issue and successfully connect to your Azure Machine Learning workspace. If you continue to experience difficulties, please provide additional details about your setup, and I would be happy to assist you further.

Thank you