I'm trying to run the automl code from the examples (https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization) in Azure MLS which is not in virtual network. While running the experiment, it is getting failed with the below error.
AzureMLCompute job failed.
BFSMountError: Unable to mount blob fuse file system
Info: Could not mount Azure Blob Container azureml-blobstore-xxxx at workspaceblobstore: Unauthorized. Cannot access the storage account with the given account key. Please verify that the account key is valid.
Info: Failed to setup runtime for job execution: Job environment preparation failed on 10.0.0.4 with err exit status 1.
Not sure why the AzureML is not able to access its own blobstorage to place the model artifacts.
The AzureML and the workspace blob both are not in virtual network.
1) Tried to register the workspace blob container (azureml-blobstore-<ID>) as per the link here (https://docs.microsoft.com/en-us/azure/machine-learning/how-to-access-data), but still getting the same error.
Note: The workspace blob storage keys are synced and can able to access the notebooks and data in AzureML, Is this causing the issue?
Are the storage keys cached in the storage connection strings at the backend ? however the error message is different, in the reference ticket it says not able to access the resource, but in my case it is not able mount to the azure-ml-<ID> container.
Could you please help on it.
Thanks in advance.