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Litmus Edge Bridge for AWS

Explore the architecture patterns manufacturers use to deliver contextualized industrial data from edge into Amazon Web Services.

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This architecture shows how Litmus Edge connects industrial systems, prepares OT data for the cloud, and delivers contextualized data to Amazon Web Services through the Litmus Edge Data Foundation and AWS-native services.

Architecture Summary

This architecture shows how industrial OT data is collected, normalized, contextualized, and delivered from the edge into Amazon Web Services using Litmus Edge and the Litmus Edge Data Foundation.

  • Litmus Edge (LE) connects to industrial systems, normalizes and contextualizes data, and prepares it for consumption through the Edge Data Foundation.

  • The Edge Data Foundation with Litmus Edge (LE) bridges contextualized industrial data into AWS Services, feeding AWS IoT Core, AWS IoT SiteWise, and AWS S3 for ingestion, storage, and transformation.

  • Litmus Edge Manager enables centralized deployment, monitoring, and lifecycle management of Litmus Edge instances across the factory floor, and can be hosted on cloud or in plant.

End-to-end data flow

1. Connect and collect industrial data
Litmus Edge DeviceHub connects to PLCs, controllers, DCS, industrial robots, CNC machines, IP cameras, databases, file systems, SCADA, MES, and QMS systems to collect raw tags, telemetry, and events using OT Native Connectors, device discovery, and tags & events ingestion.

2. Normalize and prepare data at the edge
Litmus Edge standardizes tags, units, and timestamps, and applies asset & site context so data is reliable before leaving the edge, through tag normalization, unit/timestamp standardization, and data transformation.

3. Store and buffer at the edge
Litmus Edge DataHub stores time-series data, events, and messages locally to support resilience and consistent delivery, using a time-series database, event store, and message buffer.

4. Contextualize cloud-ready data
Litmus Edge Analytics and LE Data Models organize data into asset/process models, contextual data products, and schema-aligned payloads through schema alignment and delivery preparation.

5. Bridge to AWS via the Edge Data Foundation
The Edge Data Foundation with Litmus Edge (LE) bridges contextualized industrial data into AWS Services across three paths:
5a — into AWS IoT Core
5b — into AWS IoT SiteWise
5c — into AWS S3

6. Transform data with AWS services
AWS IoT Core and AWS IoT SiteWise feed AWS Lambda within Transformation Services, applying serverless processing and transformation to prepare data for downstream consumption.

7. Deliver to AWS data consumers
Transformed and stored data flows to AWS consumption endpoints including Amazon Timestream for InfluxDB, Visualization and Dashboard Applications, and downstream Enterprise Consumer Apps such as ERP, CRM, and PLM.

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