AWS cli documentation change
Summary
Added new parameters TrainingPlanArn and ExecutionRoleSessionNameMode, updated syntax definitions, and incremented CLI version references from 2.34.45 to 2.34.48
Security assessment
The change introduces ExecutionRoleSessionNameMode which enhances security audit trails by allowing session names to reflect user identities. However, there is no evidence of a specific security vulnerability being fixed. The TrainingPlanArn addition is for resource management without security implications.
Diff
diff --git a/cli/latest/reference/sagemaker/create-domain.md b/cli/latest/reference/sagemaker/create-domain.md index 79b225b38..b6d6a1d0a 100644 --- a//cli/latest/reference/sagemaker/create-domain.md +++ b//cli/latest/reference/sagemaker/create-domain.md @@ -15 +15 @@ - * [AWS CLI 2.34.45 Command Reference](../../index.html) » + * [AWS CLI 2.34.48 Command Reference](../../index.html) » @@ -470,0 +471,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -754,0 +769,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -1064,0 +1093,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -1329,0 +1372,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -1829,0 +1886,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -2197,0 +2268,14 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -2867,0 +2952,11 @@ See also: [AWS API Documentation](https://docs.aws.amazon.com/goto/WebAPI/sagema +>> +>> ExecutionRoleSessionNameMode -> (string) +>> +>>> The execution role session name mode. If this value is set to `USER_IDENTITY` , the session name of the execution role corresponds to the user’s identity. For IAM domains, the session name is the IAM session name used to generate the presigned URL. For IAM Identity Center domains, the session name is the username of the associated IAM Identity Center user. If this value is set to `STATIC` or is not set, the session name defaults to `SageMaker` . +>>> +>>> Possible values: +>>> +>>> * `STATIC` +>>> * `USER_IDENTITY` +>>> + @@ -2900 +2995,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -2916 +3012,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -2934 +3031,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -2947 +3045,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -2999 +3098,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -3026 +3126,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -3096 +3197,2 @@ JSON Syntax: - ] + ], + "ExecutionRoleSessionNameMode": "STATIC"|"USER_IDENTITY" @@ -3384,0 +3487,14 @@ JSON Syntax: +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -3607 +3723 @@ Shorthand Syntax: - SecurityGroupIds=string,string,RStudioServerProDomainSettings={DomainExecutionRoleArn=string,RStudioConnectUrl=string,RStudioPackageManagerUrl=string,DefaultResourceSpec={SageMakerImageArn=string,SageMakerImageVersionArn=string,SageMakerImageVersionAlias=string,InstanceType=string,LifecycleConfigArn=string}},ExecutionRoleIdentityConfig=string,TrustedIdentityPropagationSettings={Status=string},DockerSettings={EnableDockerAccess=string,VpcOnlyTrustedAccounts=[string,string],RootlessDocker=string},AmazonQSettings={Status=string,QProfileArn=string},UnifiedStudioSettings={StudioWebPortalAccess=string,DomainAccountId=string,DomainRegion=string,DomainId=string,ProjectId=string,EnvironmentId=string,ProjectS3Path=string,SingleSignOnApplicationArn=string},IpAddressType=string + SecurityGroupIds=string,string,RStudioServerProDomainSettings={DomainExecutionRoleArn=string,RStudioConnectUrl=string,RStudioPackageManagerUrl=string,DefaultResourceSpec={SageMakerImageArn=string,SageMakerImageVersionArn=string,SageMakerImageVersionAlias=string,InstanceType=string,LifecycleConfigArn=string,TrainingPlanArn=string}},ExecutionRoleIdentityConfig=string,TrustedIdentityPropagationSettings={Status=string},DockerSettings={EnableDockerAccess=string,VpcOnlyTrustedAccounts=[string,string],RootlessDocker=string},AmazonQSettings={Status=string,QProfileArn=string},UnifiedStudioSettings={StudioWebPortalAccess=string,DomainAccountId=string,DomainRegion=string,DomainId=string,ProjectId=string,EnvironmentId=string,ProjectS3Path=string,SingleSignOnApplicationArn=string},IpAddressType=string @@ -3624 +3740,2 @@ JSON Syntax: - "LifecycleConfigArn": "string" + "LifecycleConfigArn": "string", + "TrainingPlanArn": "string" @@ -4092,0 +4210,14 @@ JSON Syntax: +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -4376,0 +4508,14 @@ JSON Syntax: +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0` +>>>> * max: `2048` +>>>> * pattern: `(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:training-plan/.*|None)` +>>>> + @@ -4690,0 +4836,14 @@ JSON Syntax: +>>> +>>> TrainingPlanArn -> (string) +>>> +>>>> The ARN of the SageMaker AI Training Plan to use for this app. When you specify a training plan, the app launches on reserved GPU capacity. This field is supported for JupyterLab and CodeEditor app types. +>>>> +>>>> For more information about how to reserve GPU capacity with SageMaker AI Training Plans, see [Using training plans in Studio applications](https://docs.aws.amazon.com/sagemaker/latest/dg/training-plan-utilization-for-studio-apps.html) . +>>>> +>>>> Constraints: +>>>> +>>>> * min: `0`