Control data access to Amazon S3 from Amazon SageMaker Studio with Amazon S3 Access Grants
Machine Learning Blog
This article explains how to control data access to Amazon S3 from Amazon SageMaker Studio using Amazon S3 Access Grants. It demonstrates a solution to simplify data access for different user personas like data scientists and ML engineers using IAM principals with S3 Access Grants.
Specifically, the article covers:
- Overview of the solution and architecture
- Prerequisites and deploying resources using AWS CloudFormation
- Validating the S3 bucket data, SageMaker domain, user profiles, and S3 Access Grants setup
- Running a PySpark processing job from SageMaker Studio to validate access grants
- Cleaning up resources
- Conclusion
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