Q5 — AWS AIF-C01 Ch.1

Question 5 of 100 | ← Chapter 1

A company developed an ML model for image classification. The company wants to deploy this model into production so a web application can use it. The company needs a solution to host the model and provide predictions without managing any underlying infrastructure. Which solution meets these requirements?

• A. Deploy the model using Amazon SageMaker Serverless Inference. ✓
• B. Deploy the model using Amazon CloudFront.
• C. Host the model and provide predictions using Amazon API Gateway.
• D. Host the model and provide predictions using AWS Batch.

Correct Answer: A. Deploy the model using Amazon SageMaker Serverless Inference.

Explanation

This question tests understanding of AWS services and their use cases. To deploy an ML model into production without managing underlying infrastructure while enabling prediction serving, Amazon SageMaker Serverless Inference is ideal—it automatically scales based on request volume and abstracts infrastructure management. Amazon CloudFront is a CDN, not a model hosting service; Amazon API Gateway alone cannot host ML models; AWS Batch is for batch processing, not real-time inference. Thus, option A satisfies all requirements.