Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 27 discussion

Use Amazon SageMaker Serverless Inference to deploy the model: Amazon SageMaker Serverless Inference allows you to deploy machine learning models in a fully managed, serverless environment. You don't need to manage the underlying infrastructure (such as EC2 instances) to handle predictions. This is ideal for scenarios like yours, where the model needs to be deployed and used by a web application, and scalability and infrastructure management should be abstracted away.

A is the correct answer

Amazon SageMaker helps to host the model, and serve predictions without managing infrastructure provisioning and configurations.

A. Use Amazon SageMaker Serverless Inference to deploy the model. Amazon SageMaker Serverless Inference is specifically designed for hosting ML models and serving predictions without requiring the management of underlying infrastructure. It automatically provisions compute resources as needed and is ideal for use cases like the one described.

A: Use Amazon SageMaker Serverless Inference to deploy the model. Explanation: Amazon SageMaker Serverless Inference is a fully managed solution for deploying machine learning models without managing the underlying infrastructure. It automatically provisions compute capacity, scales based on request traffic, and serves predictions efficiently. This makes it an ideal choice for hosting a model and serving predictions for a web application with minimal management overhead. Why not the other options? B: Use Amazon CloudFront to deploy the model: Amazon CloudFront is a content delivery network (CDN) C: Use Amazon API Gateway to host the model and serve predictions: Amazon API Gateway is used to create APIs for accessing services. D: Use AWS Batch to host the model and serve predictions: AWS Batch is designed for batch processing and job scheduling, not for real-time inference or hosting ML models for web applications.

Serverless deployment: SageMaker Serverless Inference allows you to deploy ML models without managing any underlying infrastructure, which directly meets the company's requirement.

A. Use Amazon SageMaker Serverless Inference to deploy the model. With serverless inference, there's no need to manage any infra.