Cirrus Link Solutions provide software to bridge the gap for OT data to be ingested and utilized within AWS services to enable digital transformation and big data solutions such as predictive maintenance and machine learning. Solutions include the following:
The Cirrus Link Modules for Ignition:
AWS Cloud Injector Module:
The AWS Cloud Injector module easily connects any tag data from the Ignition into the Amazon Web Services (AWS) cloud infrastructure. With a simple configuration, tag data will flow into the AWS Kinesis Streams & Firehose or DynamoDB using an easy to read JSON representation to take full advantage of AWS and all the benefits it offers.
AWS SiteWise Engine Module:
Adds functionality to the Inductive Automation Ignition Platform to interface with AWS IoT SiteWise service to automatically discover assets and create tags providing an enhanced HTML5 mobile-ready visualization solution.
The Cirrus Link Solutions for AWS:
The AWS Injector module easily connects any tag data from the Ignition into the Amazon Web Services (AWS) cloud infrastructure. With a simple configuration, tag data will flow into the AWS Kinesis Streams & Firehose or DynamoDB using an easy to read JSON representation to take full advantage of AWS and all the benefits it offers.
- Connects to any Ignition TAG Data
- Easy to Configure
- For use on the Ignition Gateway or Ignition Edge
- Supports Store & Forward
The diagram below shows how using the AWS Injector Module connects OT data into the AWS Web Services. Data is streamed into AWS Kinesis for real-time, streaming or batch analytics. For solutions using AWS Greengrass, please click here for information on the MQTT Transmission module.
For the tutorials, support and latest documentation, please go here.
Download the data sheet here: AWS Injector Module Data Sheet.
The Cirrus Link AWS SiteWise Engine module adds functionality to the Inductive Automation Ignition platform to interface with AWS IoT SiteWise service to automatically discover assets and create tags providing an enhanced HTML5 mobile-ready visualization solution.
AWS IoT SiteWise is a fully managed AWS IoT service that you can use to collect, organize, and analyze data from industrial equipment at scale. AWS IoT SiteWise enables you to collect data to be collected from on the plant floor from sensors, equipment, or a local on-premises gateway. The data ingested and modeled in AWS IoT SiteWise is stored in a scalable and time-optimized internal data store. Once data is stored in AWS IoT SiteWise, you can stream live data in near real-time in a consistent model it can be queried and query historical data to build downstream IoT applications.
The SiteWise engine module does the following:
- Connects to AWS SiteWise
- Auto-Discovers New Assets and Data Models
- Auto-Discovers Tags and Tag Updates
- Creates UDTs and Tags in Ignition
- Ignition Perspective Module Provides Advanced HTML 5 Visualization Tool
- Runs on Ignition as a Service in AWS
With the use of Inductive Automation's Ignition platform, and Cirrus Link MQTT modules and Sparkplug SiteWise Bridge, OT data from Industrial applications is delivered to AWS IoT SiteWise with minimal configuration and zero coding. Simply point the Cirrus Link module at the AWS IoT service and the asset model, properties and hierarchy are 100% self-discovered by SiteWise. Then real time data is securely and efficiently delivered directly to the SiteWise time series database for Big Data Analytics, ML and AI. This solution provides the simplest data ingest for AWS SiteWise delivering the Digital Transformation organizations are striving to achieve.
- Automatically Discovery of Assets
- Automatically Creates Asset model
- Automatically Defines Asset properties
- Automatically Defines Asset hierarchy
- Efficiently pushes Tag Data into SiteWise Time Series Database
- Requires No Coding, just a little Configuration!
What is AWS IoT SiteWise? it is a fully managed AWS IoT service that you can use to collect, organize, and analyze data from industrial equipment at scale. AWS IoT SiteWise enables data to be collected from plant floor sensors, equipment, or a local on-premises gateway. The data ingested and modeled in AWS IoT SiteWise is stored in a scalable and time-optimized internal data store. Once data is stored in AWS IoT SiteWise in a consistent model it can be quired to build downstream IoT applications.
There are a lot of challenges in bridging the OT - IT gap to make use of IT services in the industrial operating environments. To understand the difficulty of this process it is important to first understand the difference between OT data and IT data requirements for enabling Big Data services such as Predictive Maintenance or Machine Learning.
OT Data Consists of
● Proprietary Protocols
● Multiple Data Formats
● No Contextual Information
● Designed for Operations
● Poll / Response Date Retrieval
● Directly Coupled to Applications
● Isolated Networks
IT Data Needs
· Data Objects/Modeling
· Standard Data Formats
· Contextual Information
· Decoupled to Enterprise
· Publish / Subscribe Methodology
· Easy to Integrate
The Ignition platform enabled with the Cirrus Link MQTT Transmission module provides an easily deployable solution. As shown in the diagram below the solution connects the OT data sources at the Edge and converts into IT defined data as specified by Eclipse TAHU Open MQTT standard specification called Sparkplug.
Sparkplug provides the contextual information on the OT data for consumption into AWS IOT SiteWise using MQTT. The Sparkplug specification offers the auto-discovery of assets for the asset-modeling and real-time OT data consumption.
The diagram below shows how the application called “Sparkplug SiteWise Bridge” receives MQTT Sparkplug data from an MQTT Broker, either AWS IoT Core or any 3.1.1 compliant Broker and sends it to SiteWise using the API’s. This application developed by Cirrus Link is available to purchase via the AWS Marketplace.
The Sparkplug SiteWise Bridge Offers:
- Service consuming MQTT Sparkplug Data (Asset Model and Properties)
- Auto-Creates Asset Model
- Auto-Discovers Assets
- Auto-Defines the Asset Hierarchy
- Pushes Data into AWS SiteWise Time Series DB – Property Values and Time Stamps
There are many ways the data can be used inside AWS Cloud, described below are two common use cases for Big Data.
The first using an Ignition MQTT only approach where both the Asset Models and Real-Time data is ingested through MQTT as shown in the diagram below.
This use case is where the OT data is being used by 3rd Party applications in the cloud to perform Big Data Analytics
The second option is to enable the ingest through using AWS Greengrass. This solution is shown in the diagram below.
This scenario would be used where Machine Learning from SageMaker is being utilized to create an ML model that will be run locally in the plant using AWS Greengrass.