AWS sagemaker documentation change
Summary
Updated references from 'AWS CloudFormation' to 'CloudFormation' for terminology consistency
Security assessment
The changes are purely terminological (shortening 'AWS CloudFormation' to 'CloudFormation') without altering security context. No security vulnerabilities, configurations, or features are mentioned or modified.
Diff
diff --git a/sagemaker/latest/dg/studio-notebooks-emr-cluster.md b/sagemaker/latest/dg/studio-notebooks-emr-cluster.md index 4876f4da1..667d11961 100644 --- a//sagemaker/latest/dg/studio-notebooks-emr-cluster.md +++ b//sagemaker/latest/dg/studio-notebooks-emr-cluster.md @@ -19 +19 @@ Amazon SageMaker Studio and Studio Classic come with built-in integration with [ -Administrators can create [AWS CloudFormation templates](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html) that define Amazon EMR clusters. They can then make those cluster templates available in the [AWS Service Catalog](https://docs.aws.amazon.com/servicecatalog/latest/userguide/end-user-console.html) for Studio and Studio Classic users to launch. Data scientists can then choose a predefined template to self-provision an Amazon EMR cluster directly from their Studio environment. Administrators can further parameterize the templates to let users choose aspects of the cluster within predefined values. For example, users may want to specify the number of core nodes or select the instance type of a node from a dropdown menu. +Administrators can create [CloudFormation templates](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.html) that define Amazon EMR clusters. They can then make those cluster templates available in the [AWS Service Catalog](https://docs.aws.amazon.com/servicecatalog/latest/userguide/end-user-console.html) for Studio and Studio Classic users to launch. Data scientists can then choose a predefined template to self-provision an Amazon EMR cluster directly from their Studio environment. Administrators can further parameterize the templates to let users choose aspects of the cluster within predefined values. For example, users may want to specify the number of core nodes or select the instance type of a node from a dropdown menu. @@ -21 +21 @@ Administrators can create [AWS CloudFormation templates](https://docs.aws.amazon -Using AWS CloudFormation, administrators can control the organizational, security, and networking setup of Amazon EMR clusters. Data scientists and data engineers can then customize those templates for their workloads to create on-demand Amazon EMR clusters directly from Studio and Studio Classic without setting up complex configurations. Users can terminate Amazon EMR clusters after use. +Using CloudFormation, administrators can control the organizational, security, and networking setup of Amazon EMR clusters. Data scientists and data engineers can then customize those templates for their workloads to create on-demand Amazon EMR clusters directly from Studio and Studio Classic without setting up complex configurations. Users can terminate Amazon EMR clusters after use.