AWS marketplace documentation change
Summary
Restructured documentation by moving detailed publishing steps to separate pages, simplified main document to focus on high-level process overview with links to prerequisite and creation guides
Security assessment
Changes are organizational/structural improvements without addressing security vulnerabilities or introducing security features. Removed detailed permissions section but moved it to a linked page as part of documentation restructuring.
Diff
diff --git a/marketplace/latest/userguide/ml-publishing-your-product-in-aws-marketplace.md b/marketplace/latest/userguide/ml-publishing-your-product-in-aws-marketplace.md index bccdb92de..0f943e7ac 100644 --- a/marketplace/latest/userguide/ml-publishing-your-product-in-aws-marketplace.md +++ b/marketplace/latest/userguide/ml-publishing-your-product-in-aws-marketplace.md @@ -5 +5 @@ -PrerequisitesOverview of publishing processPermissions requiredCreating your product listingTesting your productSigning off for publishingUpdating your product +# Listing your product in AWS Marketplace @@ -7,3 +7 @@ PrerequisitesOverview of publishing processPermissions requiredCreating your pro -# Publishing your product in AWS Marketplace - -After you package your code into model package images or algorithm images, upload your images, and create your Amazon SageMaker AI resources, you can publish your machine learning product in AWS Marketplace. The following sections walk you through the publishing process, which includes creating your product listing, testing your product, signing off for publishing, and updating your product. +After you package your code into model package images or algorithm images, upload your images, and create your Amazon SageMaker AI resources, you can publish your machine learning product in AWS Marketplace. The following sections walk you through the publishing process, which includes creating your product listing, testing your product, and signing off for publishing. Once your product is published, you request changes to update your listing. For more information, see [Managing your machine learning products](./ml-product-management.html). @@ -13,375 +11 @@ After you package your code into model package images or algorithm images, uploa - * Prerequisites - - * Overview of publishing process - - * Permissions required - - * Creating your product listing - - * Testing your product - - * Signing off for publishing - - * Updating your product - - - - -## Prerequisites - -Before you can publish your model package or algorithm in AWS Marketplace, you must have the following: - - * An AWS account that is registered as an AWS Marketplace seller. You can do this in the [AWS Marketplace Management Portal](https://aws.amazon.com/marketplace/management/). - - * A completed seller profile under the [Settings](https://aws.amazon.com/marketplace/management/seller-settings) page in the AWS Marketplace Management Portal. - - * For publishing paid products, you must complete the tax interview and bank forms. This is not required for publishing free products. For more information, see [Seller registration process](https://docs.aws.amazon.com/marketplace/latest/userguide/seller-registration-process.html). - - * You must have permissions to access the AWS Marketplace Management Portal and Amazon SageMaker AI. For more information, see Permissions required. - - - - -## Overview of publishing process - -There are four steps in the publishing process: - - 1. **Submit product** – Create a listing with the description, usage information, and other details of your model package or algorithm product. After you submit your product for publishing, it takes about an hour until the status changes to the next step. - - 2. **Test product** – Use your AWS account that is registered as an AWS Marketplace seller to preview the listing in the AWS Marketplace, subscribe to it, and test the product. In addition, other allowed AWS accounts can preview and test the product. If any changes are necessary, you can go back and edit the listing details. - - 3. **Sign off for publishing** – When your product is ready to go live, return to the AWS Marketplace Management Portal, and choose **Sign off and publish**. - - 4. **Product goes live** – Your product is now live in the AWS Marketplace. You can maintain your product by publishing new versions with updates or product fixes. - - - - -## Permissions required - -To publish an Amazon SageMaker AI product, the AWS Identity and Access Management user or role you are signed in as requires one or both of the following IAM actions: - - * **sagemaker:DescribeModelPackage** – For listing a model package - - * **sagemaker:DescribeAlgorithm** – For listing an algorithm - - - - -For the AWS Marketplace permissions needed, or for managing your seller account, see [Policies and permissions for AWS Marketplace sellers](https://docs.aws.amazon.com/marketplace/latest/userguide/detailed-management-portal-permissions.html). - -## Creating your product listing - -The following is a walkthrough for creating your product listing in the AWS Marketplace for both model package and algorithm products. - -###### Note - -Before creating your listing, ensure that you have the required resources specified in [Requirements and best practices for creating machine learning products](./ml-listing-requirements-and-best-practices.html). - -The process has the following steps: - -###### Steps - - * Step 1: Create a new listing - - * Step 2: Provide general product information - - * Step 3: Add your launch option - - * Step 4: Set the pricing and terms - - * Step 5: Submit your product for publishing - - - - -### Step 1: Create a new listing - -###### To create a new machine learning product listing - - 1. Sign in to your seller AWS account and navigate to the [AWS Marketplace Management Portal](https://aws.amazon.com/marketplace/management). - - 2. In the top menu, navigate to **Products** and then **Machine learning**. - - 3. Choose **Create new listing**. - - - - -###### Note - -On the **New Product** page, in the **Product summary** section, you can view the current status, privacy setting, product type, creator, and product ID. - -### Step 2: Provide general product information - -###### To provide general product information - - 1. In the **General product information** section, for **Product descriptions** , choose **Add**. - - 1. For the **Product visibility** section, choose one of the following options: - - * **Public** – The product will initially be available to a limited set of AWS accounts for testing. After you sign off and publish it, the product is publicly discoverable and available for subscription by all customers. - - * **Private** – The product will only be visible to the AWS accounts that you specify. You will not be able to make this product public in the future. - - 2. Enter **Product title** , **Short product description** , **Product overview** ,**Product category 1** , and other details. You can change these values later. For product descriptions, see [Requirements and best practices for creating machine learning products](./ml-listing-requirements-and-best-practices.html). - - 3. Choose **Continue** when complete. - - 2. For **Promotional Resources** , provide a product logo, search keywords, and relevant resource links. You can change these values later. - - 1. Choose **Continue** when complete. - - 3. For **Support Information** , choose whether you are offering support for the product. - - 1. If you choose **Yes** , provide support and contact details. You can change these values later. - - 2. Choose **Continue** when complete. - - 4. For **Region Availability** , choose the specific AWS Regions you want to list your product in. - -The default value is **Make available in all current and future supported Regions**. - - 1. Choose **Continue** when complete. - -###### Note - -After you submit your draft for publishing, you can't change this selection. - - - - -The next step in publishing your product is to provide the launch option, which is the model package or algorithm that you're selling. - -### Step 3: Add your launch option - -###### To add your launch option - - 1. In the **Launch option** section, for **Enter ARN** , enter the Amazon Resource Name (ARN) of your model package or algorithm. - -You can find the ARN in the Amazon SageMaker AI console [Model Packages](https://console.aws.amazon.com/sagemaker/home#/model-packages/my-resources) or [Algorithms](https://console.aws.amazon.com/sagemaker/home#/algorithms/my-resources) pages. - -###### Example ARN for a model package - -`arn:aws:sagemaker:<region>:<account-id>:model-package/<model-package-name>` - -###### Example ARN for an algorithm - -`arn:aws:sagemaker:<region>:<account-id>:algorithm/<algorithm-name>` - - 2. Choose **Add**. - - 3. The following steps differ depending on if you publish a model package or algorithm product. With the exception of the buyer-facing version number, you can change the version details later. - - 1. For **Step 1: Enter version details and Git repository links** , provide the version number, release notes, and URLs to the sample Jupyter notebook and GitHub repository. - - 2. For _algorithm products_ only, for **Step 2: Enter details describing the training data inputs** , describe the training data and include an example training data resource along with an overview of the training algorithm. - -The algorithm metrics, channel specification, and hyperparameters are automatically displayed on the product detail page based on the values you provided when you created the algorithm resource in SageMaker AI. - -The following examples show how the training data inputs details appear to you as a seller, and how training data inputs details appear to the buyer. - -###### Example training data inputs – seller view - - - -###### Example training data inputs – buyer view - - - -The following examples show how the custom attributes (invocation parameters) appear to you as a seller, and how custom attributes (invocation parameters) appear to the buyer. - -###### Example custom attributes (invocation parameters) – seller view - - - -###### Example custom attributes (invocation parameters) – buyer view -