AWS sagemaker-unified-studio documentation change
Summary
Updated documentation for Visual ETL permission modes with more detailed explanations of fine-grained access control and data source compatibility
Security assessment
The changes clarify security-related permission modes (fine-grained access control vs full-table access) but do not indicate a specific security vulnerability being addressed. The enhanced descriptions better document existing security features.
Diff
diff --git a/sagemaker-unified-studio/latest/userguide/getting-started-visual-etl.md b/sagemaker-unified-studio/latest/userguide/getting-started-visual-etl.md index e63e7ca71..2f249262d 100644 --- a/sagemaker-unified-studio/latest/userguide/getting-started-visual-etl.md +++ b/sagemaker-unified-studio/latest/userguide/getting-started-visual-etl.md @@ -17 +17 @@ To create a flow using Visual ETL in Amazon SageMaker Unified Studio: -If this is your first time using Visual ETL flows in Amazon SageMaker Unified Studio, you are asked to choose a default compute permission mode option based on your data access preference. For more information, see [Configuring permission mode](./compute-glue-permissions-mode.html). +If this is your first time using Visual ETL flows in Amazon SageMaker Unified Studio, you are asked to choose a default compute permission mode option based on your data access preference. For more information, see [Configuring permission mode for Glue ETL in Amazon SageMaker Unified Studio](./compute-permissions-mode-glue.html). @@ -23 +23 @@ If this is your first time using Visual ETL flows in Amazon SageMaker Unified St - * Select **project.spark.fineGrained** to configure permission mode to support fine-grained access control. Choosing this option configures your Visual ETL flow to work with data product subscriptions from Amazon SageMaker catalog. + * Select **project.spark.fineGrained** for data managed using fine-grained access, meaning the compute engine can only access specific rows and columns from the full dataset. Choosing this option configures your compute to work with data asset subscriptions from Amazon SageMaker catalog. @@ -25 +25 @@ If this is your first time using Visual ETL flows in Amazon SageMaker Unified St - * Select **project.spark.compatibility** to configure permission mode to be compatible with data managed using full-table access, meaning the compute engine can access all rows and columns in the data. Choosing this option configures your Visual ETL flow to work with data assets that you connect to from your project. + * Select **project.spark.compatibility** to configure permission mode to be compatible with data managed using full-table access, meaning the compute engine can access all rows and columns in the data. Choosing this option configures your compute to work with data assets from AWS and from external systems that you connect to from your project.