AI-102 Question 53
Single answerYou are tasked with deploying a pre-trained machine learning model as a containerized web service in Azure. The model must scale automatically based on demand and integrate with other Azure services for logging and monitoring. Which Azure service should you use for this deployment?
- A
Azure Kubernetes Service (AKS)
- B
Azure Container Instances (ACI)
- C
Azure App Service
- D
Azure Functions
Show answer and explanation
Correct answer: A
Explanation
Azure Kubernetes Service (AKS) is the most appropriate choice for deploying containerized machine learning models in this scenario. It provides features such as autoscaling, integration with Azure Monitor and Log Analytics, and the ability to handle complex deployments. The other options either lack the required features or are not designed for managing containerized workloads of this nature.
- A. Correct.
Azure Kubernetes Service (AKS) is the best choice for deploying containerized machine learning models that require features like autoscaling, integration with monitoring tools, and support for complex deployments. It is specifically designed for managing containerized workloads.
- B. Incorrect.
Azure Container Instances (ACI) is suitable for lightweight, single-container workloads but lacks advanced features like autoscaling and seamless integration with monitoring tools, making it less ideal for this scenario.
- C. Incorrect.
Azure App Service is primarily designed for deploying web apps and APIs but is not optimized for managing containerized workloads that require autoscaling and integration with monitoring tools.
- D. Incorrect.
Azure Functions is a serverless compute option for event-driven workloads and is not suitable for deploying persistent, containerized machine learning models as web services.