Your company is building custom models that integrate into microservices architecture on Azure Kubernetes Services (AKS). The model is built by using Python and published to AKS. You need to update…

The correct answer is C. the Azure Machine Learning SDK. You can set up Azure Application Insights for Azure Machine Learning. Application Insights gives you the opportunity to monitor: Request rates, response times, and failure rates. Dependency rates, response times, and failure rates. Requirements include an Azure Machine Learning…

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Question

Your company is building custom models that integrate into microservices architecture on Azure Kubernetes Services (AKS). The model is built by using Python and published to AKS. You need to update the model and enable Azure Application Insights for the model. What should you use?

Options

Athe Azure CLI
BMLNET Model Builder
Cthe Azure Machine Learning SDK
Dthe Azure portal

How the community answered

(58 responses)

A
10% (6)
B
2% (1)
C
83% (48)
D
5% (3)

Explanation

You can set up Azure Application Insights for Azure Machine Learning. Application Insights gives you the opportunity to monitor: Request rates, response times, and failure rates. Dependency rates, response times, and failure rates. Requirements include an Azure Machine Learning workspace, a local directory that contains your scripts, and the Azure Machine Learning SDK for Python installed. https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/service/how-to-enable-app-insights

Topics

#Azure ML SDK#AKS deployment#Application Insights#model update

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