AI-102 Question 55
Single answerYou are designing a solution to deploy a machine learning model as a containerized application in Azure. The application must allow scaling based on CPU utilization and provide secure access to the container. Which Azure service should you use for this deployment?
- A
Azure Kubernetes Service (AKS)
- B
Azure App Service
- C
Azure Container Instances (ACI)
- D
Azure Virtual Machines (VM)
Show answer and explanation
Correct answer: A
Explanation
Azure Kubernetes Service (AKS) is the most suitable choice for deploying and scaling containerized applications in Azure. It offers advanced orchestration, built-in scaling based on CPU utilization, and secure access controls, aligning with the requirements of the scenario. While other alternatives like ACI or App Service may support containers, they do not provide the level of scalability and orchestration required here.
- A. Correct.
Azure Kubernetes Service (AKS) allows you to deploy, manage, and scale containerized applications efficiently. It provides features like automatic scaling, load balancing, and built-in security mechanisms, making it the best choice for this scenario.
- B. Incorrect.
Azure App Service is primarily designed for web applications and APIs. While it supports containerized deployments, it lacks advanced container orchestration and scaling features compared to AKS.
- C. Incorrect.
Azure Container Instances (ACI) is suitable for simple, single-container deployments or lightweight workloads. It does not provide advanced scaling or orchestration features required for this scenario.
- D. Incorrect.
Azure Virtual Machines (VM) can run containerized applications, but they require manual setup and management for scaling, orchestration, and security, making them less efficient for this scenario.