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Amazon Web Services AWS Certified Machine Learning Engineer - Associate MLA-C01 Question # 27 Topic 3 Discussion

Amazon Web Services AWS Certified Machine Learning Engineer - Associate MLA-C01 Question # 27 Topic 3 Discussion

MLA-C01 Exam Topic 3 Question 27 Discussion:
Question #: 27
Topic #: 3

A company must install a custom script on any newly created Amazon SageMaker AI notebook instances.

Which solution will meet this requirement with the LEAST operational overhead?


A.

Create a lifecycle configuration script to install the custom script when a new SageMaker AI notebook is created. Attach the lifecycle configuration to every new SageMaker AI notebook as part of the creation steps.


B.

Create a custom Amazon Elastic Container Registry (Amazon ECR) image that contains the custom script. Push the ECR image to a Docker registry. Attach the Docker image to a SageMaker Studio domain. Select the kernel to run as part of the SageMaker AI notebook.


C.

Create a custom package index repository. Use AWS CodeArtifact to manage the installation of the custom script. Set up AWS PrivateLink endpoints to connect CodeArtifact to the SageMaker AI instance. Install the script.


D.

Store the custom script in Amazon S3. Create an AWS Lambda function to install the custom script on new SageMaker AI notebooks. Configure Amazon EventBridge to invoke the Lambda function when a new SageMaker AI notebook is initialized.


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