MLS-C01 Question #188: Real Exam Question with Answer & Explanation

Question

A company is building a demand forecasting model based on machine learning (ML). In the development stage, an ML specialist uses an Amazon SageMaker notebook to perform feature engineering during work hours that consumes low amounts of CPU and memory resources. A data engineer uses the same notebook to perform data preprocessing once a day on average that requires very high memory and completes in only 2 hours. The data preprocessing is not configured to use GPU. All the processes are running well on an ml.m5.4xlarge notebook instance. The company receives an AWS Budgets alert that the billing for this month exceeds the allocated budget. Which solution will result in the MOST cost savings?

Options

• AChange the notebook instance type to a memory optimized instance with the same vCPU
• BKeep the notebook instance type and size the same. Stop the notebook when it is not in
• CChange the notebook instance type to a smaller general purpose instance. Stop the
• DChange the notebook instance type to a smaller general purpose instance. Stop the

Explanation

Initial processing needs less cpu and memory so that can be done on a smaller instance. Second operation is memory intensive so instance type should be changed to R5 type instance.

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