AWS prescriptive-guidance documentation change
Summary
Updated service references from 'AWS Supply Chain' to 'Supply Chain' throughout the document for branding consistency. No functional changes to deployment processes or security configurations.
Security assessment
Changes are purely branding/nomenclature updates (e.g., 'AWS Supply Chain' → 'Supply Chain'). No modifications to security controls, permissions, encryption, or vulnerability mitigations are present. IAM references remain unchanged, and security-related terms like KMS appear without substantive updates.
Diff
diff --git a/prescriptive-guidance/latest/patterns/automate-the-deployment-of-aws-supply-chain-data-lakes.md b/prescriptive-guidance/latest/patterns/automate-the-deployment-of-aws-supply-chain-data-lakes.md index 29f65d2b2..77cf1744b 100644 --- a//prescriptive-guidance/latest/patterns/automate-the-deployment-of-aws-supply-chain-data-lakes.md +++ b//prescriptive-guidance/latest/patterns/automate-the-deployment-of-aws-supply-chain-data-lakes.md @@ -9 +9 @@ SummaryPrerequisites and limitationsArchitectureToolsBest practicesEpicsTroubles -# Automate AWS Supply Chain data lakes deployment in a multi-repository setup +# Automate Supply Chain data lakes deployment in a multi-repository setup @@ -17 +17 @@ This pattern provides an automated approach for deploying and managing AWS Suppl -The solution leverages AWS Supply Chain, AWS Lambda, and Amazon Simple Storage Service (Amazon S3) to establish the data lake infrastructure, while using either deployment method to automate configuration and resource creation. This automation eliminates manual configuration steps and ensures consistent deployments across environments. In addition, AWS Supply Chain eliminates the need for deep expertise in extract, transform, and load (ETL) and can provide insights and analytics powered by Amazon Quick Sight. +The solution leverages Supply Chain, AWS Lambda, and Amazon Simple Storage Service (Amazon S3) to establish the data lake infrastructure, while using either deployment method to automate configuration and resource creation. This automation eliminates manual configuration steps and ensures consistent deployments across environments. In addition, Supply Chain eliminates the need for deep expertise in extract, transform, and load (ETL) and can provide insights and analytics powered by Amazon Quick Sight. @@ -46 +46 @@ Ensure the following are in place before deployment: - * AWS Supply Chain – Full Access preferred for deploying its components like datasets and integration flows, along with accessing it from the AWS Management Console. + * Supply Chain – Full Access preferred for deploying its components like datasets and integration flows, along with accessing it from the AWS Management Console. @@ -52 +52 @@ Ensure the following are in place before deployment: - * Amazon EventBridge – For use by AWS Supply Chain. + * Amazon EventBridge – For use by Supply Chain. @@ -56 +56 @@ Ensure the following are in place before deployment: - * AWS Key Management Service (AWS KMS) – For access to the AWS KMS keys used for the Amazon S3 artifacts bucket and the Amazon S3 AWS Supply Chain staging bucket. + * AWS Key Management Service (AWS KMS) – For access to the AWS KMS keys used for the Amazon S3 artifacts bucket and the Amazon S3 Supply Chain staging bucket. @@ -58 +58 @@ Ensure the following are in place before deployment: - * AWS Lambda – For creating the Lambda functions that deploy the AWS Supply Chain components. + * AWS Lambda – For creating the Lambda functions that deploy the Supply Chain components. @@ -60 +60 @@ Ensure the following are in place before deployment: - * Amazon S3 – For access to the Amazon S3 artifacts bucket, server access logging bucket, and AWS Supply Chain staging bucket. If you’re using manual deployment, permissions for the Amazon S3 Terraform artifacts bucket are also required. + * Amazon S3 – For access to the Amazon S3 artifacts bucket, server access logging bucket, and Supply Chain staging bucket. If you’re using manual deployment, permissions for the Amazon S3 Terraform artifacts bucket are also required. @@ -96 +96 @@ If you prefer to use GitHub Actions workflows for deployment, set up the followi - * The AWS Supply Chain instance doesn’t support complex data transformation techniques. + * The Supply Chain instance doesn’t support complex data transformation techniques. @@ -98 +98 @@ If you prefer to use GitHub Actions workflows for deployment, set up the followi - * AWS Supply Chain is most suited for supply chain domains because it provides built-in analytics and insights. For any other domain, AWS Supply Chain can be used as a data store as part of the data lake architecture. + * Supply Chain is most suited for supply chain domains because it provides built-in analytics and insights. For any other domain, Supply Chain can be used as a data store as part of the data lake architecture. @@ -127 +127 @@ The diagrams show the following workflow: - 1. Deploy AWS Supply Chain service datasets infrastructure and databases using one of the following deployment methods: + 1. Deploy Supply Chain service datasets infrastructure and databases using one of the following deployment methods: @@ -133 +133 @@ The diagrams show the following workflow: - 2. Create the supporting AWS resources that are required for AWS Supply Chain service operation: + 2. Create the supporting AWS resources that are required for Supply Chain service operation: @@ -143 +143 @@ The diagrams show the following workflow: - * Lambda functions that manage (create, update, and delete) the AWS Supply Chain service instance, namespaces, and datasets. + * Lambda functions that manage (create, update, and delete) the Supply Chain service instance, namespaces, and datasets. @@ -145 +145 @@ The diagrams show the following workflow: - * AWS Supply Chain staging Amazon S3 bucket for data ingestion + * Supply Chain staging Amazon S3 bucket for data ingestion @@ -147 +147 @@ The diagrams show the following workflow: - 4. Deploy the Lambda function that manages integration flows between the staging bucket and AWS Supply Chain datasets. After deployment is complete, the remaining workflow steps manage data ingestion and analysis. + 4. Deploy the Lambda function that manages integration flows between the staging bucket and Supply Chain datasets. After deployment is complete, the remaining workflow steps manage data ingestion and analysis. @@ -149 +149 @@ The diagrams show the following workflow: - 5. Configure source data ingestion to the AWS Supply Chain staging Amazon S3 bucket. + 5. Configure source data ingestion to the Supply Chain staging Amazon S3 bucket. @@ -151 +151 @@ The diagrams show the following workflow: - 6. After data is added to the AWS Supply Chain staging Amazon S3 bucket, the service automatically triggers the integration flow to the AWS Supply Chain datasets. + 6. After data is added to the Supply Chain staging Amazon S3 bucket, the service automatically triggers the integration flow to the Supply Chain datasets. @@ -153 +153 @@ The diagrams show the following workflow: - 7. AWS Supply Chain integrates with Quick Sight Analytics to produce dashboards based on the ingested data. + 7. Supply Chain integrates with Quick Sight Analytics to produce dashboards based on the ingested data. @@ -178 +178 @@ The diagrams show the following workflow: - * [Amazon Q](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/qinasc.html) in AWS Supply Chain is an interactive generative AI assistant that helps you operate your supply chain more efficiently by analyzing the data in your AWS Supply Chain data lake. + * [Amazon Q](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/qinasc.html) in Supply Chain is an interactive generative AI assistant that helps you operate your supply chain more efficiently by analyzing the data in your Supply Chain data lake. @@ -184 +184 @@ The diagrams show the following workflow: - * [AWS Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/adminguide/getting-started.html) is a cloud-based managed application that can be used as a data store in organizations for supply chain domains, which can be used to generate insights and perform analysis on the ingested data. + * [Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/adminguide/getting-started.html) is a cloud-based managed application that can be used as a data store in organizations for supply chain domains, which can be used to generate insights and perform analysis on the ingested data. @@ -199 +199 @@ The diagrams show the following workflow: - * [Python](https://www.python.org/) is a general-purpose computer programming language. This pattern uses Python for the AWS function’s code to interact with AWS Supply Chain + * [Python](https://www.python.org/) is a general-purpose computer programming language. This pattern uses Python for the AWS function’s code to interact with Supply Chain @@ -229 +229 @@ Clone the repository.| To clone this pattern’s repository, run the following c -(Manual option) Prepare for deployment of AWS Supply Chain datasets.| To go to the `terraform-deployment` directory of `ASC-Datasets`, run the following command: +(Manual option) Prepare for deployment of Supply Chain datasets.| To go to the `terraform-deployment` directory of `ASC-Datasets`, run the following command: @@ -254 +254 @@ To configure and export the environment variables, run the following commands: -(Manual option) Prepare for managing AWS Supply Chain integration flows in deployment.| To go to the `terraform-deployment` directory of `ASC-Integration-Flows`, run the following command: +(Manual option) Prepare for managing Supply Chain integration flows in deployment.| To go to the `terraform-deployment` directory of `ASC-Integration-Flows`, run the following command: @@ -542,2 +542,2 @@ Upload sample CSV files.| To upload sample CSV files for the datasets, use the f - 2. Fetch the AWS Supply Chain instance ID `asc_instance_id` from the [terraform outputs](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Datasets/terraform-deployment/output.tf) directory. - 3. Note the Amazon S3 bucket name for AWS Supply Chain that was created in deployment: `aws-supply-chain-data-<Instance_ID>` + 2. Fetch the Supply Chain instance ID `asc_instance_id` from the [terraform outputs](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Datasets/terraform-deployment/output.tf) directory. + 3. Note the Amazon S3 bucket name for Supply Chain that was created in deployment: `aws-supply-chain-data-<Instance_ID>` @@ -558 +558 @@ Task| Description| Skills required -Set up AWS Supply Chain access.| To set up AWS Supply Chain access from the AWS Management Console, use the following steps: +Set up Supply Chain access.| To set up Supply Chain access from the AWS Management Console, use the following steps: @@ -560 +560 @@ Set up AWS Supply Chain access.| To set up AWS Supply Chain access from the AWS - 1. Sign in to the AWS Management Console and search for the AWS Supply Chain service. + 1. Sign in to the AWS Management Console and search for the Supply Chain service. @@ -562 +562 @@ Set up AWS Supply Chain access.| To set up AWS Supply Chain access from the AWS - 3. This pattern uses IAM Identity Center to manage user access to the AWS Supply Chain instance. To ensure complete access to this solution, sign in as the Administrator of the application. + 3. This pattern uses IAM Identity Center to manage user access to the Supply Chain instance. To ensure complete access to this solution, sign in as the Administrator of the application. @@ -587 +587 @@ Set up the Terraform backend and providers configuration.| To set up the Terrafo -Generate infrastructure destruction plan.| To prepare for the controlled destruction of your AWS infrastructure by generating a detailed teardown plan, run the following commands. The process initializes Terraform, incorporates AWS Supply Chain dataset configurations, and creates a destruction plan that you can review before executing. +Generate infrastructure destruction plan.| To prepare for the controlled destruction of your AWS infrastructure by generating a detailed teardown plan, run the following commands. The process initializes Terraform, incorporates Supply Chain dataset configurations, and creates a destruction plan that you can review before executing. @@ -644 +644 @@ Set up the Terraform backend and providers configuration.| To set up the Terrafo -Generate infrastructure destruction plan.| To create a plan for destroying AWS Supply Chain dataset resources, run the following commands: +Generate infrastructure destruction plan.| To create a plan for destroying Supply Chain dataset resources, run the following commands: @@ -671 +671 @@ Empty Amazon S3 buckets.| To empty all Amazon S3 buckets (except the server acce -Execute infrastructure destruction plan.| To execute the planned destruction of your AWS Supply Chain dataset infrastructure using the generated plan, run the following command: +Execute infrastructure destruction plan.| To execute the planned destruction of your Supply Chain dataset infrastructure using the generated plan, run the following command: @@ -690,2 +690,2 @@ Issue| Solution -An AWS Supply Chain dataset or integration flow did not deploy correctly because of AWS Supply Chain internal errors or insufficient IAM permissions for the service role.| First, clean up all resources. Then, redeploy the AWS Supply Chain [dataset resources](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Datasets/README.md) and then redeploy the AWS Supply Chain [integration flow resources](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Integration-Flows/README.md). -The AWS Supply Chain integration flow doesn’t fetch the new data files uploaded for the AWS Supply Chain datasets.| +An Supply Chain dataset or integration flow did not deploy correctly because of Supply Chain internal errors or insufficient IAM permissions for the service role.| First, clean up all resources. Then, redeploy the Supply Chain [dataset resources](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Datasets/README.md) and then redeploy the Supply Chain [integration flow resources](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Integration-Flows/README.md). +The Supply Chain integration flow doesn’t fetch the new data files uploaded for the Supply Chain datasets.| @@ -693,2 +693,2 @@ The AWS Supply Chain integration flow doesn’t fetch the new data files uploade - 1. Check that the prefix of the AWS Supply Chain integration flow [configuration](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Integration-Flows/terraform-deployment/integration-flows-config.tf) matches the prefix used when uploading the sample data files. - 2. If the resources for the AWS Supply Chain datasets were re-created, their associated Amazon Resource Names (ARNs) change internally. Therefore, redeploy the resources for the AWS Supply Chain service integration flows resources. + 1. Check that the prefix of the Supply Chain integration flow [configuration](https://github.com/aws-samples/sample-automate-aws-supply-chain-deployment/blob/main/ASC-Integration-Flows/terraform-deployment/integration-flows-config.tf) matches the prefix used when uploading the sample data files. + 2. If the resources for the Supply Chain datasets were re-created, their associated Amazon Resource Names (ARNs) change internally. Therefore, redeploy the resources for the Supply Chain service integration flows resources. @@ -702 +702 @@ The AWS Supply Chain integration flow doesn’t fetch the new data files uploade - * [AWS Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/adminguide/getting-started.html) + * [Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/adminguide/getting-started.html) @@ -716 +716 @@ The AWS Supply Chain integration flow doesn’t fetch the new data files uploade -This solution can be replicated for more datasets and can be queried for further analysis, through prebuilt dashboards provided with AWS Supply Chain or custom integration with Amazon Quick Sight. In addition, you can use Amazon Q to ask questions related to your AWS Supply Chain instance. +This solution can be replicated for more datasets and can be queried for further analysis, through prebuilt dashboards provided with Supply Chain or custom integration with Amazon Quick Sight. In addition, you can use Amazon Q to ask questions related to your Supply Chain instance. @@ -718 +718 @@ This solution can be replicated for more datasets and can be queried for further -**Analyze data with AWS Supply Chain Analytics** +**Analyze data with Supply Chain Analytics** @@ -720 +720 @@ This solution can be replicated for more datasets and can be queried for further -For instructions to set up AWS Supply Chain Analytics, see [Setting AWS Supply Chain Analytics](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/setting_analytics.html) in the AWS Supply Chain documentation. +For instructions to set up Supply Chain Analytics, see [Setting Supply Chain Analytics](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/setting_analytics.html) in the Supply Chain documentation. @@ -724 +724 @@ This pattern demonstrated the creation of **Calendar** and **Outbound_Order_Line - 1. To analyze the datasets, use the **Seasonality Analysis** dashboard. To add the dashboard, follow the steps in [Prebuilt dashboards](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/prebuilt_dashboards.html) in the AWS Supply Chain documentation. + 1. To analyze the datasets, use the **Seasonality Analysis** dashboard. To add the dashboard, follow the steps in [Prebuilt dashboards](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/prebuilt_dashboards.html) in the Supply Chain documentation. @@ -733 +733 @@ The dashboard provides insights on demand over the years based on the ingested d -**Use Amazon Q to ask questions related to your AWS Supply Chain instance** +**Use Amazon Q to ask questions related to your Supply Chain instance** @@ -735 +735 @@ The dashboard provides insights on demand over the years based on the ingested d -[Amazon Q in AWS Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/qinasc.html) is an interactive generative AI assistant that helps you operate your supply chain more efficiently. Amazon Q can do the following: +[Amazon Q in Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/qinasc.html) is an interactive generative AI assistant that helps you operate your supply chain more efficiently. Amazon Q can do the following: @@ -737 +737 @@ The dashboard provides insights on demand over the years based on the ingested d - * Analyze the data in your AWS Supply Chain data lake. + * Analyze the data in your Supply Chain data lake. @@ -746 +746 @@ The dashboard provides insights on demand over the years based on the ingested d -For more information about using Amazon Q, see [Enabling Amazon Q in AWS Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/enabling_QinASC.html) and [Using Amazon Q in AWS Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/using_QinASC.html) in the AWS Supply Chain documentation. +For more information about using Amazon Q, see [Enabling Amazon Q in Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/enabling_QinASC.html) and [Using Amazon Q in Supply Chain](https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/using_QinASC.html) in the Supply Chain documentation.