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ADOIssue is documented on MSFT ADO for internal trackingIssue is documented on MSFT ADO for internal trackingComputedoc-enhancementproduct-gapproduct gapsproduct gaps
Description
The documentation says that we can attach remote VMs such as "an Azure VM, a remote server in your organization, or on-premises. Specifically, given the IP address and credentials (user name and password, or SSH key), you can use any accessible VM for remote runs."
However, in both the studio as well as the provided code snippet, a resource ID is required.
from azureml.core.compute import RemoteCompute, ComputeTarget
# Create the compute config
compute_target_name = "attach-dsvm"
attach_config = RemoteCompute.attach_configuration(resource_id='<resource_id>',
ssh_port=22,
username='<username>',
password="<password>")
# Attach the compute
compute = ComputeTarget.attach(ws, compute_target_name, attach_config)
compute.wait_for_completion(show_output=True)
As such, I was wondering if it's possible to do as the documentation suggests and attach our SSH-accessible servers to AML.
NathanNZ
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ADOIssue is documented on MSFT ADO for internal trackingIssue is documented on MSFT ADO for internal trackingComputedoc-enhancementproduct-gapproduct gapsproduct gaps