Customer Story:

Real-Time Innovations (RTI)

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RTI needed to build a monitoring solution that would meet the unique architectural requirements of monitoring Industrial Internet of Things (IIoT) data for its industrial customers. The IIoT is transforming industries across the board by infusing and connecting billions of connected devices with digital intelligence. Through low-cost computing and networking, today’s systems enable far greater amounts of data, at far greater speeds, to be connected throughout distributed systems. As the amount of data increases exponentially, however, there needs to be a new way to monitor it in real time without overwhelming existing systems.

Building a monitoring architecture for IIoT requires a collective software stack for data collection, storage, analysis and visualization. In today’s connected world, however, the software components of the monitoring framework may be deployed in a distributed manner and over geographically-dispersed locations, requiring them to be seamlessly integrated over multiple networks.

RTI uses InfluxDB in IIoT system monitoring. They created an architecture that meets the software framework requirements by combining the capabilities of the The Object Management Group (OMG) Data Distribution ServiceTM (DDS) standard for real-time data exchange with InfluxDB. DDS is a middleware protocol and API standard that provides data connectivity, extreme reliability and a scalable architecture to meet IIoT application requirements.

The time series monitoring architecture that RTI built over WAN uses the Telegraf plugins they developed for Connext DDS. The Telegraf plugin monitors and provides alerts throughout distributed IIoT systems.

Versatility

RTI was able to quickly build a DDS Telegraf plugin

Subscribe to DDS data

DDS can be seamlessly consolidated in InfluxDB.

Analysis and action

Process and aggregate DDS metrics for improved analysis and action.

Technologies Used

“InfluxDB supports built-in time series functions that can select and aggregate or even predict metrics. These time series functions are essential to normalize and analyze an enormous amount of data collected for monitoring and alerting.”

- Kyoungho An, Senior Research Engineer, RTI

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