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AWS Solutions Library

Guidance for Water Use Efficiency on AWS

Overview

Important: This Guidance requires the use of Amazon Forecast, which is no longer available to new customers. Existing customers of Amazon Forecast can continue using and deploying this Guidance as normal.

This Guidance demonstrates how industrial operations and water utilities can collect and monitor water usage data. It displays how you can improve your water use efficiency through the use of advanced analytics, such as forecasting. By adopting sustainable water management practices and investing in water-efficient technologies, you may reduce your business’s water usage and mitigate some of the operational risks of water scarcity.

How it works

Overview

This architecture diagram provides an overview of the data workflow for collecting, monitoring, and optimizing telemetry data for water use efficiency. For more details about the different stages of the data workflow, open the other tabs.

Download the architecture diagram
Architecture diagram illustrating water use efficiency on AWS. The flow shows data sources such as industrial operations, water utilities, and other enterprise data feeding telemetry and other data into the AWS Cloud. Data ingestion is categorized into telemetry data and other enterprise data, followed by data storage and processing through hot or cold data stores. The stages include raw storage, preprocessing, and processed storage for time series and batch data. The diagram concludes with data consumption for visualization, reporting, advanced analytics, and notifications.

Part 1

This architecture diagram provides a more detailed description about data sources and ingestion. Follow the steps in this architecture diagram to deploy Part 1 of the Guidance. 

Download the architecture diagram
Architecture diagram illustrating AWS Cloud-based water use efficiency solution, showing data sources (industrial operations, water utilities, enterprise data) flowing into AWS IoT SiteWise, AWS IoT Core, Amazon Kinesis, Amazon Timestream, AWS Glue, Amazon API Gateway, and Amazon S3.

Part 2

This architecture diagram provides a more detailed description about storing and processing data in hot and cold storage. Follow the steps in this architecture diagram to deploy Part 2 of the Guidance.

Download the architecture diagram
Architecture diagram showing AWS services for water use efficiency data storage and processing. It depicts hot and cold data store flows using AWS IoT SiteWise, Amazon Timestream, Amazon S3, AWS Lambda, AWS Glue, and Amazon Redshift, with steps for raw storage, preprocessing, and processed storage.

Part 3

This architecture diagram provides a more detailed description about processing and storing data for visualization and analytics. Follow the steps in this architecture diagram to deploy Part 3 of the Guidance.

Download the architecture diagram
Architecture diagram illustrating an AWS Cloud solution for water use efficiency. Shows processed storage using AWS IoT SiteWise, Amazon Timestream, Amazon S3, and Amazon Redshift, with visualization and reporting tools (Amazon Managed Grafana, AWS Amplify, Amazon API Gateway, Amazon Athena, Amazon QuickSight), advanced analytics (Amazon SageMaker), management and security (Amazon CloudWatch, AWS Systems Manager, AWS KMS, AWS IAM), and notifications and alerting (AWS IoT Events, Amazon SNS) for analysts and operations managers.

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.

This Guidance uses AWS IoT Events to continuously monitor Internet of Things (IoT) sensor data for equipment failures. Amazon SNS alerts you when it detects an event.

Read the Operational Excellence whitepaper 

IAM policies and roles protect resources, following the least-privilege principle. It encrypts IoT data in transit using Transport Layer Security (TLS), and it encrypts and protects data at rest using AWS KMS .

Read the Security whitepaper 

This Guidance follows an event-driven architecture with loosely coupled dependencies, making it easy for you to isolate behaviors and increase resilience and agility. You can also use CloudWatch metrics and alarms to monitor the application and send notifications when thresholds breach. Specify an automation runbook in Systems Manager Incident Manager to enable automated responses to critical issues.

Read the Reliability whitepaper 

The services in this Guidance are purpose-built to perform required functions. For example, AWS IoT SiteWise is built to collect, organize, and analyze data from industrial equipment at scale. It reads data from on-site equipment using industrial protocols, such as OPC UA. Timestream is built to store and manage time-series data from telemetry. Forecast is made for time-series forecasting based on machine learning.

Read the Performance Efficiency whitepaper 

This Guidance uses services that scale automatically according to demand, so you only pay for what you use. Timestream manages the life cycle of timeseries data, keeping recent data in memory and moving historical data to a cost-optimized storage tier based on user-defined policies.

Read the Cost Optimization whitepaper 

This Guidance follows an event-driven architecture and uses fully managed services such as Timestream , AWS Glue , and Amazon S3 . These services scale automatically according to workload, helping you avoid overprovisioning resources. Additionally, you can use the Amazon S3 Intelligent-Tiering storage class to automatically move data to the most sustainable access tier in Amazon S3 .

Read the Sustainability whitepaper 

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.