Microsoft
DP-100 · Question #161
DP-100 Question #161: Real Exam Question with Answer & Explanation
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Train and deploy models
Question
You train a model and register it in your Azure Machine Learning workspace. You are ready to deploy the model as a real-time web service. You deploy the model to an Azure Kubernetes Service (AKS) inference cluster, but the deployment fails because an error occurs when the service runs the entry script that is associated with the model deployment. You need to debug the error by iteratively modifying the code and reloading the service, without requiring a re-deployment of the service for each code update. What should you do?
Options
- AModify the AKS service deployment configuration to enable application insights and re-deploy to
- BCreate an Azure Container Instances (ACI) web service deployment configuration and deploy the
- CAdd a breakpoint to the first line of the entry script and redeploy the service to AKS.
- DCreate a local web service deployment configuration and deploy the model to a local Docker
- ERegister a new version of the model and update the entry script to load the new version of the
- FCreate an Environment object based on the dependencies you specify in the environment yaml
- GCreate an inference configuration (InferenceConfig object) based on the environment and the
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Topics
#Model Deployment#Debugging#Azure Container Instances (ACI)#Azure Kubernetes Service (AKS)