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MLA-C01 · Question #141

MLA-C01 Question #141: Real Exam Question with Answer & Explanation

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Deployment and Orchestration of ML Workflows

Question

A company wants to use Amazon SageMaker to host an ML model that runs on CPU for real-time predictions. The model will have intermittent traffic during business hours and will have periods of no traffic after business hours. The company needs a solution that will serve inference requests in the most cost-effective manner. Which hosting option will meet these requirements?

Options

  • ADeploy the model to a SageMaker real-time endpoint. Add a schedule-based auto scaling policy
  • BDeploy the model to a SageMaker Serverless Inference endpoint. Configure increased
  • CDeploy the model to a SageMaker Asynchronous Inference endpoint. Configure an auto scaling
  • DDeploy the model to a SageMaker real-time endpoint. Create a scheduled AWS Lambda function

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Topics

#SageMaker Inference Endpoints#Serverless ML#Cost Optimization#Real-time Prediction
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