The ms-air-aiagility.vss-services-azureml.azureml-model-deploy-task.AMLModelDeploy@0 task in the azdo-ci-build-train is failing for AKS because the compute_target_name parameter is not correctly filled by the Azure CLI command.
Using the Python SDK is providing a more stable and successful experience to deploy the model to a compute target.
Command produced by the task:
az ml model deploy --ct akscomputetarget -n aks-name --model sklearn_model.pkl:1 --ic /__w/1/src/azureml/code/score/inference_config.json --dc /__w/1/src/azureml/code/score/deployment_config_aks.json -g rg-main -w aml-main --overwrite
Error issued:
ERROR: {\'Azure-cli-ml Version\': \'1.0.83\', \'Error\': MlCliError({\'Error\': \'Error parsing --deploy-config-file. Must be valid JSON or YAML file.\', \'Response Content\': TypeError("deploy_configuration() got an unexpected keyword argument \'compute_target_name\
The ms-air-aiagility.vss-services-azureml.azureml-model-deploy-task.AMLModelDeploy@0 task in the azdo-ci-build-train is failing for AKS because the compute_target_name parameter is not correctly filled by the Azure CLI command.
Using the Python SDK is providing a more stable and successful experience to deploy the model to a compute target.
Command produced by the task:
az ml model deploy --ct akscomputetarget -n aks-name --model sklearn_model.pkl:1 --ic /__w/1/src/azureml/code/score/inference_config.json --dc /__w/1/src/azureml/code/score/deployment_config_aks.json -g rg-main -w aml-main --overwriteError issued:
ERROR: {\'Azure-cli-ml Version\': \'1.0.83\', \'Error\': MlCliError({\'Error\': \'Error parsing --deploy-config-file. Must be valid JSON or YAML file.\', \'Response Content\': TypeError("deploy_configuration() got an unexpected keyword argument \'compute_target_name\