Today, we announced the general availability of extended industrial protocol support for AWS IoT SiteWise – a managed service that makes it easy to collect, store, organize and monitor data from industrial equipment at scale to help you make data-driven decisions. AWS IoT SiteWise Edge, a feature of AWS IoT SiteWise, extends the cloud capabilities to collect, organize, process, and monitor equipment data on-premises. Through a new integration with AWS Partner Domatica, customers now have the ability ingest data from 10 additional industrial protocols including Modbus (TCP & RTU), Ethernet/IP, Siemens S7, KNX, LoRaWAN, MQTT, Profinet, Profibus, BACnet and Restfull (REST API) interfaces, in addition to native OPC UA support. Previously, ingesting data from these protocols required acquiring, provisioning, and configuring infrastructure and middleware for data collection and translation resulting in additional cost and time to value.
In this blog post, we will walk through the installation and configuration of AWS IoT SiteWise Edge gateway software with Domatica EasyEdge data collector to ingest equipment data from a Siemens S7 PLC into AWS IoT SiteWise. Refer to Domatica documentation on how to connect additional data sources.
Solution overview
Through the AWS Console, users can simply add AWS Partner Domatica’s EasyEdge software as a data source on their existing AWS IoT SiteWise Edge gateway. AWS IoT SiteWise Edge provides on-premises software to extend the cloud capabilities in AWS IoT SiteWise to the industrial edge. Users then configure the protocols, desired data flows, and data conditioning in the partner application. After configurations are deployed, the equipment data flows seamlessly to AWS IoT SiteWise Edge for local monitoring, storage, and access at the edge. The data flow It is also sent to AWS IoT SiteWise for integration with other industrial data and usage in other AWS Cloud services.
Once the data is ingested into AWS SiteWise, you can visualize the collected data with IoT SiteWise Monitor, a feature of AWS IoT SiteWise; it provides portals in the form of managed web applications where you can create dashboards. You can also leverage Amazon Managed Grafana to visualize and monitor data in dashboards by using the AWS IoT SiteWise data source; or store your data in hot and cold storage tiers of AWS IoT SiteWise: a hot tier optimized for real-time applications and frequently accessed data with lower write-to-read latency, and a cold tier optimized for analytical applications with less-frequently accessed data and historical data, such as business intelligence (BI) dashboards, artificial intelligence (AI) and machine learning (ML) training, historical reports, and backups. For more information on AWS IoT SiteWise, you can visit the AWS IoT SiteWise user guide.
Sections
These sections summarize how to create a SiteWise Edge gateway and include detailed instructions for steps that are specific to adding EasyEdge data source and connect to a Siemens S7 PLC. For this demonstration, we are using a virtual Siemens S7 PLC from this open source GitHub repo.
Key steps to consider
- Create AWS IoT SiteWise Edge Gateway
- Add data source for EasyEdge
- Connect EasyEdge to a Siemens S7 PLC
- Verify data flow into AWS IoT SiteWise
Prerequisites
- At a minimum, AWS IoT SiteWise Edge requires an industrial computer running Linux with a x86 64 bit quad-core processor, 16GB RAM, and 256GB in disk space. The gateway device must allow inbound traffic on port 443 and it must allow outbound traffic on ports 443 and 8883.
- A Siemens S7 PLC
- EasyEdge Studio account
Solution Architecture
Walkthrough
- Create AWS IoT SiteWise Gateway
- Configure EasyEdge Data source
- Connect EasyEdge to the Siemens S7 PLC
- Verify data in AWS IoT SiteWise
About the authors
- Oscar Salcedo – Specialist Solutions Architect for IoT & Robotics at Amazon Web Services (AWS).
- Seibou Gounteni – Specialist Solutions Architect for IoT & Robotics at Amazon Web Services (AWS).
- Intissar Harrabi – Solutions Architect, part of the Canadian Public Sector team at AWS