Driving productivity with data insights
Softing’s edgeConnector product family offers a secure and scalable way to link production lines and machines to the cloud. Seamlessly integrating with AWS cloud services for the Internet of Things, edgeConnector products will get an IIoT solution started quickly Depending on the user's needs, the solution can be easily extended and modified.
Connect your production assets and machines with AWS
Machine connectivity is a critical component of Industrial IoT solutions and relevant for most IIoT applications. Softing edgeConnector products enable users to handle the technical challenges of OT/IT integration efficiently, and scale their IIoT solutions with ease. Key features and benefits include:
Deploy on standard hardware
edgeConnector products come packaged as Docker container, which means that they can be flexibly and easily deployed on standard hardware.
Seamless integration
edgeConnector products support standardized interfaces and protocols such as OPC UA and MQTT, offering multiple options how to integrate machine and production data with AWS.
Manageability by IT
Docker container technology is commonly used by IT, and it is also supported by AWS IoT Greengrass. This means that edgeConnector products can be efficiently managed by IT and via the central AWS platform, like many other software modules for industrial edge.
Secure and proven
edgeConnector products leverage Softing’s 30+ years experience with industrial communication and connectivity solutions, offering reliable and secure operation in demanding production environments.
The AWS Quick Start: Getting started in 10 minutes
The AWS Quick Start automates the deployment of Softing’s edgeConnector Siemens and AWS IoT SiteWise in the AWS cloud. This involves generating data with a simulated Siemens S7-1500 PLC, sending it to AWS via edgeConnector Siemens, and visualizing it with AWS IoT SiteWise. The entire deployment on AWS takes not more than 10 minutes.
The edgeConnector Siemens that is running in the AWS cloud behaves exactly the same as if it were deployed in the shopfloor, connecting a real Siemens PLC. Users without access to a PLC can try out possible applications and gain experience with an Industrial IoT solution scenario. Users with limited AWS experience will greatly benefit from the automated deployment of AWS IoT SiteWise.
AWS CloudFormation templates are used to automate this setup. They allow to descriptively specify the definitions of the necessary cloud resources and services to build a software stack from ground up, either in a fully cloud-hosted or hybrid structure. Automation scripts are open source and can be modified for individual projects as needed.
Users do not have to license edgeConnector Siemens: It is running in “demo mode”, which means that the full feature set of the product is available for 72 hours. Afterwards the product has to be restarted and will run another 72 hours. And if a user would like to transition from the virtual deployment in the AWS cloud to a deployment of edgeConnector Siemens on an edge device, connecting a real PLC, larger parts of the Quick Start scenario can be reused.
About edgeConnector Siemens
edgeConnector Siemens connects Siemens SIMATIC S7-300/400, and S7-1200/1500 controller and provides access to data via an OPC UA server interface. In addition, the data can also be transmitted to MQTT brokers using MQTT. The application is easy to configure locally via a built-in Web interface. It can also be managed remotely via its REST API. Configuration is flexible and includes fine-tuned security settings (e.g. role based access rights for OPC UA client applications).
About AWS IoT SiteWise
AWS IoT SiteWise is a managed service that makes it easy to collect, store, organize, and monitor data from industrial equipment at scale to help users make better, data-driven decisions. AWS IoT SiteWise can be used to monitor operations across facilities, quickly compute common industrial performance metrics, and create applications that analyze industrial equipment data to prevent costly equipment issues and reduce gaps in production. This allows users to collect data consistently across devices, identify issues with remote monitoring more quickly, and improve multi-site processes with centralized data.
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