AWS Certified Generative AI Developer - Professional AIP-C01

By Amazon · Question Mode

QuestionQ40

Implementation and Integration

An insurance company uses its existing Amazon SageMaker AI infrastructure to support a web-based application that lets customers predict their insurance premiums. The company keeps the customer data used to train the SageMaker AI model in an Amazon S3 bucket. The dataset is growing rapidly.

The company needs a solution to continuously retrain the model. When an employee uploads a new customer-data file to the S3 bucket, the solution must automatically retrain and redeploy the model to the application.

Which solution meets these requirements?

Explanation

An Amazon S3 upload can trigger a Lambda function, and a Step Functions Standard workflow can coordinate the subsequent model-building process. A SageMaker Pipeline can include the training and model-deployment steps, so starting the pipeline after the upload retrains the model using the updated dataset and redeploys it to the application. SageMaker Pipelines supports deployment steps, and AWS documents EventBridge/S3-driven automation of pipeline executions. Define a pipeline — Amazon SageMaker AI

Learn more

Community Discussion

No comments yet. Be the first to start the discussion!