You are developing a generative AI application that requires large-scale text generation using a pre-trained language model. Which of the following AWS services would be the most suitable for…

The correct answer is B. Amazon SageMaker. Amazon SageMaker is the correct choice because it is AWS's purpose-built machine learning platform with dedicated real-time inference endpoints that support GPU-backed instances, auto-scaling, and model hosting optimized for large language models. AWS Lambda (A) has a 15-minute…

Deployment, Operations, and Optimization

Question

You are developing a generative AI application that requires large-scale text generation using a pre-trained language model. Which of the following AWS services would be the most suitable for deploying the model for real-time inference?

Options

AAWS Lambda
BAmazon SageMaker
CAWS Elastic Beanstalk
DAmazon EC2

How the community answered

(58 responses)

A
3% (2)
B
76% (44)
C
16% (9)
D
5% (3)

Explanation

Amazon SageMaker is the correct choice because it is AWS's purpose-built machine learning platform with dedicated real-time inference endpoints that support GPU-backed instances, auto-scaling, and model hosting optimized for large language models. AWS Lambda (A) has a 15-minute execution limit, constrained memory, and lacks GPU support-making it unsuitable for large model inference. Elastic Beanstalk (C) is a PaaS for web applications and is not optimized for ML workloads. EC2 (D) could technically work but requires significant manual setup for model serving, scaling, and health monitoring-none of which is needed when SageMaker Endpoints handle all of this natively.

Topics

#Model Deployment#Real-time Inference#Amazon SageMaker#Generative AI

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