Azure ML Kubernetes - Private IP

Question

I have an AKS cluster in a VNET/Subnet. My AKS is linked to AzureML.

I successfully deployed an Azure ML service to that AKS.

However, I see that the azureml-fe service is responding to a public IP and not a private IP from my VNET/Subnet.

How can I make it so my AzureML inference service is exposed with a private IP?

Answer 1

Maybe you need to use an internal load balancer, then it will use a private IP address. Here is the example code for Python:

from azureml.core.compute.aks import AksUpdateConfiguration
from azureml.core.compute import AksCompute, ComputeTarget

# When you create an AKS cluster, you can specify Internal Load Balancer to be created with provisioning_config object
provisioning_config = AksCompute.provisioning_configuration(load_balancer_type = 'InternalLoadBalancer')

# when you attach an AKS cluster, you can update the cluster to use internal load balancer after attach
aks_target = AksCompute(ws,"myaks")

# Change to the name of the subnet that contains AKS
subnet_name = "default"
# Update AKS configuration to use an internal load balancer
update_config = AksUpdateConfiguration(None, "InternalLoadBalancer", subnet_name)
aks_target.update(update_config)
# Wait for the operation to complete
aks_target.wait_for_completion(show_output = True)