AI-102 Question 54
Single answerYou are tasked with deploying a containerized machine learning model to Azure. The model must scale automatically based on traffic demand and should integrate seamlessly with other Azure services. Which Azure service should you choose to meet these requirements?
- A
Azure Kubernetes Service (AKS)
- B
Azure Container Instances (ACI)
- C
Azure App Service
- D
Azure Virtual Machines (VMs)
Show answer and explanation
Correct answer: A
Explanation
Azure Kubernetes Service (AKS) is the optimal choice for deploying containerized machine learning models that require automatic scaling and seamless integration with other Azure services. AKS provides robust orchestration capabilities, including support for scaling, load balancing, and managing multiple containers, which are essential for modern AI solutions.
- A. Correct.
Azure Kubernetes Service (AKS) is specifically designed for orchestrating containerized applications. It handles automatic scaling, load balancing, and integrates well with other Azure services, making it ideal for this scenario.
- B. Incorrect.
Azure Container Instances (ACI) is suitable for lightweight, single-container deployments. However, it lacks advanced orchestration features like automatic scaling and is not ideal for managing complex, multi-container applications.
- C. Incorrect.
Azure App Service is designed for hosting web applications and APIs. While it supports Docker containers, it is not optimized for large-scale container orchestration or complex deployments.
- D. Incorrect.
Azure Virtual Machines (VMs) provide high flexibility but require manual configuration and management for container deployment. This approach does not support automatic scaling out of the box, making it less suitable for this scenario.