AWS marketplace documentation change
Summary
Removed 'Required assets' section, simplified usage information requirements, updated visibility terminology from 'private' to 'limited', removed real-time demo instructions, and restructured input/output documentation to focus on parameters rather than MIME types
Security assessment
Changes focus on documentation structure and clarity rather than addressing security vulnerabilities. The 'limited visibility' terminology update does not explicitly introduce new security controls or address a known vulnerability.
Diff
diff --git a/marketplace/latest/userguide/ml-listing-requirements-and-best-practices.md b/marketplace/latest/userguide/ml-listing-requirements-and-best-practices.md index 174327c72..eeda3fb96 100644 --- a/marketplace/latest/userguide/ml-listing-requirements-and-best-practices.md +++ b/marketplace/latest/userguide/ml-listing-requirements-and-best-practices.md @@ -5 +5 @@ -Required assetsGeneral best practices for ML productsRequirements for usage informationRequirements for inputs and outputsRequirements for Jupyter notebookSummary of requirements and recommendations for ML product listings +General best practices for ML productsRequirements for usage informationRequirements for inputs and outputsRequirements for Jupyter notebookSummary of requirements and recommendations for ML product listings @@ -9 +9 @@ Required assetsGeneral best practices for ML productsRequirements for usage info -It is important that your buyers find it easy to test your model package and algorithm products. The following sections describe the requirements for creating machine learning (ML) product listings and best practices for ML products. For a complete summary of requirements and recommendations, see the Summary of requirements and recommendations for ML product listings. +It is important that your buyers find it easy to test your model package and algorithm products. The following sections describe best practices for ML products. For a complete summary of requirements and recommendations, see the Summary of requirements and recommendations for ML product listings. @@ -17,2 +16,0 @@ An AWS Marketplace representative might contact you to help you meet these requi - * Required assets - @@ -32,19 +29,0 @@ An AWS Marketplace representative might contact you to help you meet these requi -## Required assets - -Before creating a machine learning product listing, ensure that you have the following required assets: - - * **Amazon Resource Name (ARN)** – Provide the ARN of the model package or algorithm resource in the AWS Region that you are publishing from (see [Supported AWS Regions for publishing](./ml-service-restrictions-and-limits.html#ml-supported-aws-regions-for-publishing)). - - * An ARN for a model package has this form: `arn:aws:sagemaker:<region>:<account-id>:model-package/<model-package-name>` - - * An ARN for an algorithm has this form: `arn:aws:sagemaker:<region>:<account-id>:algorithm/<algorithm-name>` - - * Requirements for usage information – Provide details about inputs, outputs, and code examples. - - * Requirements for inputs and outputs – Provide either files or text. - - * Requirements for Jupyter notebook – Demonstrate complete product usage. - - - - @@ -69 +48 @@ Provide the following information for your machine learning product: - * By default, machine learning products are configured to have public visibility. However, you can create a product with private visibility. For more information, see [Creating your product listing](./ml-publishing-your-product-in-aws-marketplace.html#ml-creating-your-listing). + * By default, machine learning products are configured to have public visibility. However, you can create a product with limited visibility. For more information, see [Creating your product listing](./ml-creating-your-listing.html). @@ -73,2 +51,0 @@ Provide the following information for your machine learning product: - * (Optional) For model package products, if you want to enable a real-time product demo on your product listing page, contact the [AWS Marketplace Seller Operations](https://aws.amazon.com/marketplace/management/contact-us/) team. The product demo allows a prospective buyer to try your model directly on the listing page without subscribing to or deploying the model themselves. - @@ -84,3 +61 @@ With each new version of your resource that you add to your product listing, you -To add usage information for a new product that you are publishing for the first time, sign into the AWS Marketplace Management Portal console. From the **Products** dropdown, choose **Machine learning**. Select your product. In the **Product Overview** under **Launch option** , provide the ARN of your model package or algorithm resource, and choose **Add**. - -To edit the existing usage information for a specific version, choose **Edit** under **Launch option** and then **Edit version**. +To edit the existing usage information for a specific version, see [Updating version information](./ml-manage-product-version.html#ml-updating-versions). @@ -90 +65 @@ To edit the existing usage information for a specific version, choose **Edit** u -A clear explanation of your format, with examples of inputs and outputs, is important to help your buyers to understand and use your product. This understanding helps your buyers to perform any necessary transformations on the input data to get the best inference results. +A clear explanation of supported input parameters and returned output parameters with examples is important to help your buyers to understand and use your product. This understanding helps your buyers to perform any necessary transformations on the input data to get the best inference results. @@ -96 +71 @@ You will be prompted for the following when adding your Amazon SageMaker AI reso -For inference input, provide the input format for both the real-time endpoint and batch transform job. Include code snippets for any necessary preprocessing of the data. Include supported MIME content types (for example, **image/jpeg** , **image/png** , **image/bmp**), descriptions of values if applicable, and limitations. Include input samples hosted on [GitHub](https://github.com). +For inference input, provide a description of the input data your product expects for both real-time endpoint and batch transform job. Include code snippets for any necessary preprocessing of the data. Include limitations, if applicable. Provide input samples hosted on [GitHub](https://github.com). @@ -98 +73 @@ For inference input, provide the input format for both the real-time endpoint an -For inference output, provide the output format for the both real-time endpoint and batch transform job. Include output MIME content type (for example, **application/json** , **image/jpeg**) and description of values if applicable. Include output samples hosted on [GitHub](https://github.com). +For inference output, provide a description of the output data your product returns for both real-time endpoint and batch transform job. Include limitations, if applicable. Provide output samples hosted on [GitHub](https://github.com). @@ -104 +79 @@ For samples, provide input files that work with your product. If your model perf -In the **Information to train a model** section, provide the input data format and code snippets for any necessary preprocessing of the data. Include supported MIME content types (for example, **image/jpeg** , **image/png** , **image/bmp**), description of values if applicable, and limitations. Ensure to include input samples hosted on [GitHub](https://github.com). +In the **Information to train a model** section, provide the input data format and code snippets for any necessary preprocessing of the data. Include a description of values and limitations, if applicable. Provide input samples hosted on [GitHub](https://github.com). @@ -142 +117 @@ Describe the algorithm category. For example, “This decision forest regression -For inference, provide the input format for both the real-time endpoint and batch transform job. Include supported MIME content types (for example, **image/jpeg** , **image/png** , **image/bmp**), description of values if applicable, and limitations. See Requirements for inputs and outputs. | Required | Required +For inference, provide a description of the expected input format for both the real-time endpoint and batch transform job. Include limitations, if applicable. See Requirements for inputs and outputs. | Required | Required @@ -144 +119,2 @@ For inference, provide input samples for both the real-time endpoint and batch t -For inference, provide the output format for both the real-time endpoint and batch transform job. Include output MIME content type (for example, **application/json** , **image/jpeg**) and description of values if applicable. See Requirements for inputs and outputs. | Required | Required +For inference, provide the name and description of each input parameter. Provide details about the its limitations and specify if it is required or optional. | Recommended | Recommended +For inference, provide details about the output data your product returns for both the real-time endpoint and batch transform job. Include any limitations, if applicable. See Requirements for inputs and outputs. | Required | Required @@ -147 +123,2 @@ For inference, provide an example of using an endpoint or batch transform job. I -For training, provide input format. Include supported MIME content types (for example, **image/jpeg** , **image/png** , **image/bmp**), description of values if applicable, and limitations (for example, minimum rows of data required). See Requirements for inputs and outputs. | Not applicable | Required +For inference, provide the name and description of each output parameter. Specify if it is always returned. | Recommended | Recommended +For training, provide details about necessary information to train the model such as minimum rows of data required. See Requirements for inputs and outputs. | Not applicable | Required @@ -159 +136 @@ To use the Amazon Web Services Documentation, Javascript must be enabled. Please -Publishing your product in AWS Marketplace +Removing a product @@ -161 +138 @@ Publishing your product in AWS Marketplace -Service restrictions and quotas +Troubleshooting