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MLA-C01 · Question #178

A company is using Amazon SageMaker AI to deploy a new recommendation model for its ecommerce website. The model must use data from all client website interactions as input. Traffic is variable…

The correct answer is D. Serverless inference endpoint. Serverless inference automatically scales compute capacity up and down based on request volume and charges only for the compute used per invocation. This makes it the most cost- effective option for variable traffic patterns while still supporting real-time recommendations from…

Deployment and Orchestration of ML Workflows

Question

A company is using Amazon SageMaker AI to deploy a new recommendation model for its ecommerce website. The model must use data from all client website interactions as input. Traffic is variable throughout the day. The company needs to create an inference endpoint for the model. Which type of inference endpoint will meet these requirements MOST cost-effectively?

Options

  • ABatch transform inference endpoint
  • BAsynchronous inference endpoint
  • CReal-time inference endpoint
  • DServerless inference endpoint

How the community answered

(28 responses)
  • A
    4% (1)
  • B
    4% (1)
  • C
    11% (3)
  • D
    82% (23)

Explanation

Serverless inference automatically scales compute capacity up and down based on request volume and charges only for the compute used per invocation. This makes it the most cost- effective option for variable traffic patterns while still supporting real-time recommendations from client interaction data.

Topics

#SageMaker Inference#Serverless Inference#Cost Optimization#Model Deployment

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