MLS-C01 · Question #330
MLS-C01 Question #330: Real Exam Question with Answer & Explanation
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Question
An online delivery company wants to choose the fastest courier for each delivery at the moment an order is placed. The company wants to implement this feature for existing users and new users of its application. Data scientists have trained separate models with XGBoost for this purpose, and the models are stored in Amazon S3. There is one model for each city where the company operates. Operation engineers are hosting these models in Amazon EC2 for responding to the web client requests, with one instance for each model, but the instances have only a 5% utilization in CPU and memory. The operation engineers want to avoid managing unnecessary resources. Which solution will enable the company to achieve its goal with the LEAST operational overhead?
Options
- ACreate an Amazon SageMaker notebook instance for pulling all the models from Amazon S3
- BPrepare an Amazon SageMaker Docker container based on the open-source multi-model server.
- CKeep only a single EC2 instance for hosting all the models. Install a model server in the instance
- DPrepare a Docker container based on the prebuilt images in Amazon SageMaker. Replace the
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