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DevOps for Machine Learning (Azure MLOps Part 5) - Deploy Your Model to Azure Kubernetes Service
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| az extension add -n azure-cli-ml |
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| existingaks=$(az ml computetarget list -g $(azureml.resourceGroup) -w $(azureml.workspaceName) --query "[?name=='$(aks.clusterName)'].name" -o tsv) | |
| [[ -z "$existingaks" ]] && az ml computetarget create aks -g $(azureml.resourceGroup) -w $(azureml.workspaceName) -n $(aks.clusterName) -s $(aks.vmSize) -a $(aks.agentCount) || echo "compute target already exists, skipping..." |
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| az ml model deploy -g $(azureml.resourceGroup) -w $(azureml.workspaceName) -n $(service.name.production) -f ../metadata/model.json --dc aksDeploymentConfig.yml --ic inferenceConfig.yml --ct $(aks.clusterName) --overwrite |
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| $(System.DefaultWorkingDirectory)/_MLOps-YouTube-CI/drop/setup/install_requirements.sh |
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| pytest integration_test.py --doctest-modules --junitxml=junit/test-results.xml --cov=integration_test --cov-report=xml --cov-report=html --scoreurl $(az ml service show -g $(azureml.resourceGroup) -w $(azureml.workspaceName) -n $(service.name.production) --query scoringUri -o tsv) --scorekey $(az ml service get-keys -g $(azureml.resourceGroup) -w $(azureml.workspaceName) -n $(service.name.production) --query primaryKey -o tsv) |
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| **/test-*.xml |
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Hi,
Thanks, it is very useful. I have a situation where I would like to attach the blob in deployment (aks). If you can let me know how we can do that, it will be great