Reputation: 1890
I am currently deploying a model trained using AzureML to an AKS cluster as follows:
deployment_config_aks = AksWebservice.deploy_configuration(
cpu_cores = 1,
memory_gb = 1)
service = Model.deploy(ws, "test", [model], inference_config, deployment_config_aks, aks_target)
I would like this service to be scheduled on a specific nodepool. With normal Kubernetes deployment, I can specify a nodeSelector
like:
spec:
nodeSelector:
myNodeName: alpha
How do I specify a nodeSelector
while deploying an Azure ML model to an AKS Cluster? Or in general, is there a way to merge my custom pod spec with the one generated by Azure ML library?
Upvotes: 0
Views: 2649
Reputation: 1864
How do I specify a nodeSelector while deploying an Azure ML model to an AKS Cluster? Or in general, is there a way to merge my custom pod spec with the one generated by Azure ML library?
As per Configure Kubernetes clusters for machine learning:
nodeSelector
: Set the node selector so the extension components and the training/inference workloads will only be deployed to the nodes with all specified selectors.
For example:
nodeSelector.key=value
, nodeSelector.node-purpose=worker
and nodeSelector.node-region=eastus
You can refer to Assigning Pods to Nodes and Cannot create nodepool with node-restriction.kubernetes.io/ prefix label
Upvotes: 1