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Guidance for Industrial Data Fabric with EOT on AWS

Overview

This Guidance helps you deploy an industrial data fabric for operational data using products from AWS Partner, EOT. EOT works with energy customers to collect, organize, and analyze operational data in the cloud. This Guidance illustrates how to deploy the three components of EOT's industrial data fabric: (1) Twin Talk for industrial data ingestion, curation, and contextualization; (2) Twin Central, a digital twin builder that provides semantic asset modeling, mapping, and management; and (3) Twin Sight for visualization and navigation through operational and asset models.

How it works

This architecture diagram shows a centralized data repository designed to store, process and analyze structured and unstructured data with components such as Twin Talk, Twin Central, and Twin Sight in addition to AWS Internet of Things (IoT) services. These services provide seamless data management, achieve operational efficiency, reduce downtime, and optimize productivity.

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.

All EOT products in the industrial data fabric (Twin Talk, Twin Central, and Twin Sight) integrate with CloudWatch so users can monitor the health of all AWS services and AWS Partner products from within the same environment. CloudWatch allows industrial customers to collect and visualize logs, metrics, and events for all components of the industrial data fabric in automated dashboards. You can use that information to streamline infrastructure management, monitor performance of all services and AWS Partner products in this Guidance, and optimize resources proactively.

Read the Operational Excellence whitepaper 

Twin Talk uses role-based access control to connect to AWS services for credentials that are managed from IAM andstored encrypted on the Twin Talk server. This Guidance uses identity federation when consuming data from Aveva PI, allowing Twin Talk to use a local user to connect to the asset framework SDK.

IAM allows IT teams at industrial companies to control who can access AWS services and AWS Partner applications in this Guidance.

Amazon S3 and AWS IoT SiteWise store operational data. AWS IoT SiteWise stores data in other AWS services that encrypt the data at rest by default, and we recommend you set default server-side encryption for Amazon S3 buckets. We also recommend that you use Amazon S3 and AWS IoT SiteWise to encrypt data at rest for all data destinations in the cloud.

Read the Security whitepaper 

We recommend a multi-Availability Zone deployment strategy for the Twin Central and Twin Sight servers, both of which are stateless applications. You can recover configurations in case of server failure because Twin Central stores all relationships in AWS IoT SiteWise and AWS IoT TwinMaker. These services store data redundantly in an AWS Region, and Twin Sight allows users to download dashboard configurations as JSON files that can be stored in Amazon S3 and loaded into a different server in case of failure.

Read the Reliability whitepaper 

Twin Talk collects outgoing messages to AWS IoT SiteWise to prevent hitting throttling exceptions as the number of tags increase. AWS IoT SiteWise and Amazon S3 will scale automatically to accommodate the volume of data needed for storage and the volume of incoming data from industrial devices.

Read the Performance Efficiency whitepaper 

The Twin Talk server allows users to control data transfer into AWS IoT SiteWise and Amazon S3 by selecting only the tags that are necessary for analytics in various groups and by uploading only values with the desired granularity (such as all recorded values, only the most recent values, or aggregated values). AWS IoT SiteWise allows users to store data in two storage tiers: a hot tier optimized for real-time applications and a cold tier for analytics applications that use Amazon S3 and columnar data formats.

By exporting only the tags that will be used in analytics, industrial users can control their data ingestion costs. Additionally, you can store incoming data in your chosen service ( Amazon S3 or AWS IoT SiteWise and in your preferred format (row or columnar and compressed or not compressed) to control data ingestion costs.

Read the Cost Optimization whitepaper 

AWS IoT SiteWise and Amazon S3 provide industrial companies with a global view of their operations. This data helps you understand your environmental impact and strategize mitigation plans. With a global view into operations, you can also better understand your environmental impact through Scope 1 emissions from operational data and through Scope 3 emissions from cloud computing using the Customer Carbon Footprint Tool in the AWS Billing console.

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.