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Guidance for Sustainability Insights Framework on AWS

Overview

This Guidance demonstrates how you can automate your carbon footprint tracking with the Sustainability Insights Framework (SIF) on AWS. If you are looking to build a new carbon footprint tracking system or to improve an existing one, this Guidance will help you accelerate the design and automate tracking processes.

How it works

Overview

The SIF is composed of a suite of modules focusing on a specific set of features. This conceptual architecture shows these modules and their interactions.

Download the architecture diagram
Architecture overview diagram of the AWS Sustainability Insights Framework, illustrating SIF user interactions with key modules: Access Management, Reference Datasets, Impacts, Calculations, Pipelines, Pipeline Processor, and Calculator.

Access Management

The Access Management Module uses the concepts of users and groups to allows for permissions management and segregation of resources within SIF. SIF users can define users and groups through an external REST API. 

Download the architecture diagram
Architecture diagram of the AWS Sustainability Insights Framework access management flow, illustrating the integration of Amazon API Gateway, Cognito User Pool, Lambda, DynamoDB, and EventBridge within a tenant silo in the AWS Cloud.

Impacts

The Impacts Module enables users to manage impact-related resources. These resources can be referenced from within the Calculations and Pipelines modules when performing data processing calculations, such as emissions. 

Download the architecture diagram
Architecture diagram illustrating the AWS Sustainability Insights Framework Impacts, showing the interaction between users, Amazon API Gateway, AWS Lambda, Amazon Cognito User Pool, Amazon SQS, Amazon DynamoDB, and Amazon EventBridge within a tenant silo.

Reference Datasets

The Reference Datasets Module enables users to manage datasets, such as lookup tables. These datasets can be referenced from within the Calculations and Pipelines modules when performing data processing calculations, such as emissions. 

Download the architecture diagram
Architecture diagram illustrating the AWS Sustainability Insights Framework Reference Datasets solution, featuring components such as Amazon Cognito, API Gateway, AWS Lambda, Amazon S3, DynamoDB, SQS, Step Functions, and EventBridge. The flow shows user interaction through API modules, access management, and reference dataset indexing in a cloud environment.

How it works (continued)

Calculations

The Calculations Module enables users to define and manage equations or functions. These equations or functions can then be referenced in other Calculations or Pipelines modules when performing data processing calculations, such as emissions. 

Download the architecture diagram
Architecture diagram illustrating the AWS Sustainability Insights Framework Calculations solution. The diagram shows how users interact with an API Gateway, connecting to Lambda functions, Cognito User Pools for authentication, DynamoDB for calculations storage, SQS for task queueing, and EventBridge for shared resources, all within an AWS cloud and tenant silo structure.

Pipelines

The Pipelines Module enables users to manage Pipeline configurations. These configurations define data processing pipelines used to perform calculations, such as emissions. A Pipeline can be configured to aggregate outputs across executions and groups into metrics. Metrics capture key performance indicators (KPIs), such as total emissions over time.

Download the architecture diagram
Architecture diagram of the AWS Sustainability Insights Framework pipelines, showing integration of Amazon API Gateway, AWS Lambda, Amazon Cognito User Pool, Amazon DynamoDB, Amazon SQS, and Amazon EventBridge within an AWS Cloud region for access management, pipeline management, and shared resources.

Pipeline Processor

The Pipeline Processor Module is responsible for the orchestration of Pipelines. This includes starting a pipeline execution in response to input files provided by a user and performing any aggregations defined in the pipeline configuration. The Pipeline Processor module also provides the status of pipeline executions.

Download the architecture diagram
Architecture diagram illustrating the AWS Sustainability Insights Framework pipeline processor modules and integration, featuring services such as Amazon API Gateway, AWS Lambda, Amazon Cognito, Amazon EventBridge, Amazon Aurora, and Amazon DynamoDB.

Calculator

The Calculator Module is a backend component which parses and executes the operations defined within a pipeline. This can include arithmetic operations or lookups of resources, such as Reference Datasets and Impacts. 

Download the architecture diagram
Diagram of an AWS cloud architecture showing interconnected modules including AWS Lambda, Amazon DynamoDB, Amazon Kinesis, Amazon Aurora, and Amazon S3, organized within a tenant silo and shared resources.

Deploy with confidence

Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs. 

Go to sample code:

Well-Architected Pillars

The architecture diagram above is an example of a Solution created with Well-Architected best practices in mind. To be fully Well-Architected, you should follow as many Well-Architected best practices as possible.

Deployments for infrastructure and application code changes can be done through AWS CloudFormation and the AWS Cloud Development Kit (AWS CDK). Integration tests exist for all of the modules in addition to tests for end-to-end scenarios. These tests can be run to verify deployments.


Read the Operational Excellence whitepaper 

The infrastructure components of this Guidance were selected to help secure your workloads and minimize your security maintenance tasks. Amazon Cognito and the Access Management module are utilized for user authentication and authorization, respectively. Database services use encryption at rest, where permissions are set between tenants and tenant data is separated. Both external and internal interfaces are implemented in services that require TLS (HTTPS/SSL) to enforce data encryption in transit. Customer managed keys in AWS Key Management (AWS KMS) are used to encrypt data in Kinesis Data Firehose.

Read the Security whitepaper 

For a workload to perform its intended function correctly and consistently, managed services including Lambda (for computing), API Gateway (for API), and Amazon SQS (for messaging) are used. This ensures that your core services are deployed across multiple Availability Zones.

Key components in this Guidance are split into separate microservices with clear REST interfaces defined between the services. Retries with backoff limits are implemented in clients between services, allowing for reliable application-level architecture.

Deployment of this Guidance can be done through infrastructure as code (IaC). This makes it possible to deploy one-off deployments and hooks in continuous integration and continuous deployment (CI/CD) pipelines. Parameters and environment variables for the applications are handled through standard mechanisms such as AWS Systems Manager Parameter Store.

Read the Reliability whitepaper 

Database services in this Guidance were chosen based on the access patterns and use cases required. DynamoDB was chosen for the NoSQL datastore use cases, and Aurora Serverless v2 was chosen for the data layer requiring relational access patterns. Additionally, deployment of this Guidance can be done through IaC. Customers can quickly deploy and test this Guidance with their data and use case, and they can terminate services just as quickly when they are done. Customers are able to select their preferred AWS Region to deploy this Guidance using the provided IaC tooling.

Read the Performance Efficiency whitepaper 

To help you build and operate cost-aware workloads, this Guidance gives you the option to enable a flexible pricing model. Compute Savings Plans can be enabled for Lambda to help reduce your costs. You can also assign cost-allocation tags to organize your resources and track your AWS costs on a detailed level. To help you scale using only the minimum resources, this Guidance utilizes services in layers. The compute layer uses Lambda while the data layer incorporates the auto scaling capabilities for Aurora and DynamoDB, ensuring resources are scaled based on demand. 

Read the Cost Optimization whitepaper 

Primary services within the architecture, such as Lambda, DynamoDB, and Aurora, offer automated scaling, which optimizes resource utilization. These services can scale from zero to peak demands to ensure the minimum provisioned capacity is used to meet demand. This Guidance also follows a serverless architecture, in which compute can be scaled up and down with demand.

Read the Sustainability whitepaper 

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Disclaimer

The sample code; software libraries; command line tools; proofs of concept; templates; or other related technology (including any of the foregoing that are provided by our personnel) is provided to you as AWS Content under the AWS Customer Agreement, or the relevant written agreement between you and AWS (whichever applies). You should not use this AWS Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the AWS Content, such as sample code, as appropriate for production grade use based on your specific quality control practices and standards. Deploying AWS Content may incur AWS charges for creating or using AWS chargeable resources, such as running Amazon EC2 instances or using Amazon S3 storage.