MLA-C01 Question 255
Single answerA company is developing a machine learning model to predict customer churn. The data scientists have completed model training and now want to deploy the model for real-time inference. They need a fully managed service that can handle automatic scaling, integrates easily with their existing AWS services, and provides endpoint monitoring capabilities. Which AWS service should they use to deploy the model?
- A
Amazon SageMaker
- B
AWS Lambda
- C
Amazon EC2
- D
Amazon Elastic Kubernetes Service (EKS)
Show answer and explanation
Correct answer: A
Explanation
Amazon SageMaker is the best choice for deploying a machine learning model for real-time inference in this scenario. It is specifically designed for machine learning workflows, offering features such as automatic scaling, endpoint monitoring, and integration with other AWS services. While other services like Lambda, EC2, and EKS can technically deploy models, they either lack essential ML-specific features or require additional effort to manage the infrastructure.
- A. Correct.
Amazon SageMaker is a fully managed service that supports model deployment for real-time inference, automatic scaling, endpoint monitoring, and easy integration with other AWS services. It is the most suitable option for this scenario.
- B. Incorrect.
AWS Lambda can be used for deploying models in a serverless environment, but it is not designed specifically for machine learning deployments and does not provide endpoint monitoring or automatic scaling for inference workloads.
- C. Incorrect.
Amazon EC2 provides a general-purpose compute environment. While it can be used for deploying models, it requires manual setup and management of infrastructure, which adds complexity compared to SageMaker.
- D. Incorrect.
Amazon Elastic Kubernetes Service (EKS) is a managed Kubernetes service that can deploy machine learning models, but it requires significant expertise in Kubernetes and does not offer the out-of-the-box features for model deployment like SageMaker does.