AWS solutions documentation change
Summary
The documentation was updated to streamline the content by removing redundant line breaks and consolidating notes into single lines. The changes include formatting adjustments and minor text reorganization without altering the core technical content.
Security assessment
The changes are primarily formatting and organizational improvements. There is no evidence of addressing a specific security issue or adding new security-related content.
Diff
diff --git a/solutions/latest/mlops-workload-orchestrator/step-1-launch-the-stack-1.md index 3628c2473..5ec888a7f 100644 --- a/solutions/latest/mlops-workload-orchestrator/step-1-launch-the-stack-1.md +++ b/solutions/latest/mlops-workload-orchestrator/step-1-launch-the-stack-1.md @@ -11,3 +11 @@ Follow the step-by-step instructions in this section to configure and deploy the - 1. Sign in to the [AWS Management Console](https://aws.amazon.com/console/) and select the button to launch the `mlops-workload-orchestrator-multi-account.template` AWS CloudFormation template. - -[  ](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?templateURL=https:%2F%2Fs3.amazonaws.com%2Fsolutions-reference%2Fmlops-workload-orchestrator%2Flatest%2Fmlops-workload-orchestrator-multi-account.template&redirectId=ImplementationGuide) + 1. Sign into [AWS Management Console](https://aws.amazon.com/console) and select the button to launch `mlops-workload-orchestrator-multi-account.template` AWS CloudFormation template. [  ](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?templateURL=https:%2F%2Fs3.amazonaws.com%2Fsolutions-reference%2Fmlops-workload-orchestrator%2Flatest%2Fmlops-workload-orchestrator-multi-account.template&redirectId=ImplementationGuide) @@ -30,15 +28,3 @@ Parameter | Default | Description -**MLOps configuration S3 bucket name** | <Optional input> | Specify the name of an existing S3 bucket where the `mlops-config.json` file will be uploaded to provision the pipeline. - -###### Note - -The S3 bucket must be in the same AWS Region as the stack being deployed. -**Name of an Existing S3 Bucket** | <Optional input> | Optionally, provide the name of an existing S3 bucket to be used as the S3 assets bucket. If an existing bucket is not provided, the solution creates a new S3 bucket. - -###### Note - -If you use an existing S3 bucket for the bucket must meet the following requirements: 1) the bucket must be in the same Region as the MLOps Workload Orchestrator stack, 2) the bucket must allow reading/writing objects to/from the bucket, and 3) versioning must be allowed on the bucket. We recommended blocking public access, enabling S3 server-side encryption, access logging, and secure transport (for example, HTTPS only bucket policy) on your existing S3 bucket. -**Name of an Existing Amazon ECR repository** | <Optional input> | Optionally, provide the name of an existing Amazon ECR repository name to be used for custom algorithms images. If you do not specify an existing repository, the solution creates a new Amazon ECR repository. - -###### Note - -The Amazon ECR repository must be in the same Region where the solution is deployed. +**MLOps configuration S3 bucket name** | `<Optional input>` | Specify the name of an existing S3 bucket where the `mlops-config.json` file will be uploaded to provision the pipeline.NOTE: The S3 bucket must be in the same AWS Region as the stack being deployed. +**Name of an Existing S3 Bucket** | `<Optional input>` | Optionally, provide the name of an existing S3 bucket to be used as the S3 assets bucket. If an existing bucket is not provided, the solution creates a new S3 bucket. NOTE: If you use an existing S3 bucket for the bucket must meet the following requirements: 1) the bucket must be in the same Region as the MLOps Workload Orchestrator stack, 2) the bucket must allow reading/writing objects to/from the bucket, and 3) versioning must be allowed on the bucket. We recommended blocking public access, enabling S3 server-side encryption, access logging, and secure transport (for example, HTTPS only bucket policy) on your existing S3 bucket. +**Name of an Existing Amazon ECR repository** | `<Optional input>` | Optionally, provide the name of an existing Amazon ECR repository name to be used for custom algorithms images. If you do not specify an existing repository, the solution creates a new Amazon ECR repository. NOTE: The Amazon ECR repository must be in the same Region where the solution is deployed. @@ -46,5 +32 @@ The Amazon ECR repository must be in the same Region where the solution is deplo -**Do you want the solution to create a SageMaker AI’s model package group?** | `No` | By default, this value is `No`. If you are using Amazon SageMaker AI Model Registry, you can set this value to `Yes` to instruct the solution to create a Model Registry (for example, model package group). Otherwise, you can use your own model registry created outside the solution. - -###### Note - -If you choose to use a model registry that was not created by this solution, you must set up access permissions for other accounts to access the model registry. For more information refer to [Deploy a Model Version from a Different Account](https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-deploy-xaccount.html) in the _Amazon SageMaker AI Developer Guide._ +* Do you want the solution to create a SageMaker AI’s model package group?* | `No` | By default, this value is `No`. If you are using Amazon SageMaker AI Model Registry, you can set this value to `Yes` to instruct the solution to create a Model Registry (for example, model package group). Otherwise, you can use your own model registry created outside the solution. NOTE: If you choose to use a model registry that was not created by this solution, you must set up access permissions for other accounts to access the model registry. For more information refer to [Deploy a Model Version from a Different Account](https://docs.aws.amazon.com/sagemaker/latest/dg/model-registry-deploy-xaccount.html) in the _Amazon SageMaker AI Developer Guide._ @@ -76 +57,0 @@ In addition to the primary `AWSMLOpsFrameworkPipelineOrchestration` AWS Lambda f -When you run this solution, you will notice both Lambda functions in the AWS console. Only the `AWSMLOpsFrameworkPipelineOrchestration` Lambda function is regularly active. However, you must not delete the `solution-helper` Lambdafunction, since it is necessary to manage associated resources. @@ -79,0 +61 @@ When you run this solution, you will notice both Lambda functions in the AWS con +When you run this solution, you will notice both Lambda functions in the AWS console. Only the `AWSMLOpsFrameworkPipelineOrchestration` Lambda function is regularly active. However, you must not delete the `solution-helper` Lambdafunction, since it is necessary to manage associated resources.