
Answer-first summary for fast verification
Answer: Configure SageMaker to use a VPC with an S3 endpoint.
## Explanation **Correct Answer: C - Configure SageMaker to use a VPC with an S3 endpoint** ### Why this is correct: 1. **VPC with S3 Endpoint**: When SageMaker Studio notebooks are configured to run within a VPC, you can create a VPC endpoint for Amazon S3 (Gateway Endpoint). This allows secure, private connectivity between the SageMaker notebooks and S3 without traversing the public internet. 2. **Data Flow Management**: This configuration enables controlled data transfer between S3 and SageMaker, ensuring data remains within the AWS network and providing better security, lower latency, and potentially lower costs. 3. **Security and Compliance**: Using VPC endpoints helps meet security requirements by keeping data transfer within the AWS private network. ### Why other options are incorrect: **A. Use Amazon Inspector to monitor SageMaker Studio.** - Amazon Inspector is an automated security assessment service that helps improve security and compliance of applications deployed on AWS. - It's for security vulnerability assessment, not for managing data flow between services. **B. Use Amazon Macie to monitor SageMaker Studio.** - Amazon Macie is a security service that uses machine learning to discover, classify, and protect sensitive data in AWS. - It's for data discovery and classification, not for managing data flow between services. **D. Configure SageMaker to use S3 Glacier Deep Archive.** - S3 Glacier Deep Archive is a storage class for long-term data archival with retrieval times of 12 hours. - This is for data storage, not for managing data flow between SageMaker and S3. ### Key AWS Concepts: - **VPC Endpoints for S3**: Enable private connectivity between your VPC and S3 without internet gateways, NAT devices, or VPN connections. - **SageMaker Studio VPC Configuration**: SageMaker Studio can be configured to run within a VPC for enhanced network isolation and security. - **Data Flow Management**: Controlling how data moves between AWS services is crucial for security, compliance, and cost optimization.
Author: Ritesh Yadav
Ultimate access to all questions.
No comments yet.
A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks. Which solution will meet this requirement?
A
Use Amazon Inspector to monitor SageMaker Studio.
B
Use Amazon Macie to monitor SageMaker Studio.
C
Configure SageMaker to use a VPC with an S3 endpoint.
D
Configure SageMaker to use S3 Glacier Deep Archive.