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How to use workspace diagnostics (SDK v1)

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APPLIES TO: Python SDK azureml v1

Azure Machine Learning provides a diagnostic API that can be used to identify problems with your workspace. Errors returned in the diagnostics report include information on how to resolve the problem.

In this article, learn how to use the workspace diagnostics from the Azure Machine Learning Python SDK v1.

Prerequisites

Diagnostics from Python

The following snippet demonstrates how to use workspace diagnostics from Python

APPLIES TO: Python SDK azureml v1

from azureml.core import Workspace

ws = Workspace.from_config()

diag_param = {
      "value": {
      }
    }

resp = ws.diagnose_workspace(diag_param)
print(resp)

The response is a JSON document that contains information on any problems detected with the workspace. The following JSON is an example response:

{
    "value": {
        "user_defined_route_results": [], 
        "network_security_rule_results": [], 
        "resource_lock_results": [], 
        "dns_resolution_results": [{
            "code": "CustomDnsInUse", 
            "level": "Warning", 
            "message": "It is detected VNet '/subscriptions/<subscription-id>/resourceGroups/<resource-group-name>/providers/Microsoft.Network/virtualNetworks/<virtual-network-name>' of private endpoint '/subscriptions/<subscription-id>/resourceGroups/larrygroup0916/providers/Microsoft.Network/privateEndpoints/<workspace-private-endpoint>' is not using Azure default DNS. You need to configure your DNS server and check https://learn.microsoft.com/azure/machine-learning/how-to-custom-dns to make sure the custom DNS is set up correctly."
        }], 
        "storage_account_results": [], 
        "key_vault_results": [], 
        "container_registry_results": [], 
        "application_insights_results": [], 
        "other_results": []
    }
}

If no problems are detected, an empty JSON document is returned.

For more information, see the Workspace.diagnose_workspace() reference.

Next steps