Exam AI-900 topic 1 question 38 discussion

Correct. For Prod - AKS and for Dev/Test - use Azure Container Service

Correct: To perform real-time inferencing, you must deploy a pipeline as a real-time endpoint. The real-time endpoint creates an interface between an external application and your scoring model. A call to a real-time endpoint returns prediction results to the application in real-time. To make a call to a real-time endpoint, you pass the API key that was created when you deployed the endpoint. The endpoint is based on REST, a popular architecture choice for web programming projects. Real-time endpoints must be deployed to an Azure Kubernetes Service cluster.

azure container service

AKS is the correct answer

Is this question outdated? AML docs suggests usage of Managed Online Endpoints over AKS. https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online?view=azureml-api-2#why-choose-managed-online-endpoints-over-aci-or-aksv1

correct

I guess the hint here is 'for others to consume,' which implies production. Hence AKS is correct

You can also deploy to Azure Container Instance (ACI) if you select Azure Container Instance for Compute type in the real-time endpoint setting box. Azure Container Instance is used for testing or development. Use ACI for low-scale CPU-based workloads that require less than 48 GB of RAM. https://learn.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy

Answer is correct

AKS - https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy#create-an-inferencing-cluster

Correct!

Azure Kuber ( AKS)

given ans is correct