The press release found its way into my email client proclaiming an update to a “modern edge” product from Litmus. Since I’m a fanatic on defining things, I wound up talking with co-founders Vatsal Shah and John Younes. I had written about the company in September, but it has been around since 2014.
The IT company conferences I’ve been attending have been all over the concept of “edge”, and OT companies have recently picked up the phrase. For an IT company, edge is at the end of the network with a device located in close proximity to where the work is done. I think for OT companies, it’s a similar, but opposite direction, view. The Litmus product is software that can reside on an amazing variety of compute devices.
Litmus contains a number of interesting and useful features. I was most captivated with the implementation of an app marketplace. There is a “public” one for apps from Litmus or third parties that a customer can install. There is also a “private” marketplace. For example, say an engineer in one plant solves a problem with an added app for their Litmus application. That engineer can add it to the private app store for use by engineers in other plants.
At the end of this post, I’ll include some edge definitions from Litmus that I found helpful. First, here is the latest news.
Litmus announced the release of Litmus Edge 3.0, a modern edge platform to collect and analyze data, build and run applications, and integrate edge data with any cloud or enterprise system. Litmus Edge 3.0 adds more device drivers to bring the industry-leading total to more than 250, with enhanced analytics, improved integration connectors, digital twin support, and expanded device management features.
“Litmus Edge is the only modern edge platform on the market that connects to all industrial assets and provides a complete data picture to improve industrial operations,” said Vatsal Shah, co-founder and CEO of Litmus. “Version 3.0 expands upon the product that already leads the industry with more device drivers, pre-built analytics and OT/IT integration capabilities, so customers can capture edge data and use it to perform local analytics or advanced use cases like machine learning and AI in the cloud.”
New features of Litmus Edge 3.0 include:
- Launched second generation industrial communication drivers focusing on security and scalability for southbound communications
- Enhanced Ready Analytics which now includes the ability to run Tensorflow and other machine learning algorithms natively on real-time ingested data
- Flows Manager updated to allow multiple instances of Flows – which can be tightly integrated or scaled or isolated with sandbox and production logics
- Enhanced cloud and enterprise Integration connectors including support for Splunk, Oracle DB, and other databases
- Improved user interface for application marketplace for one-click application orchestration
- Device management improvements including security, backup/restore and digital twin templates
Litmus Edge is a modern edge platform that collects data from any industrial asset, offers pre-built applications, KPIs and analytics, provides the ability to build and run custom applications, and integrates data with any cloud or enterprise system. Litmus Edge is easy to use and easy to deploy, offering the edge connectivity and data intelligence needed to power industrial use cases ranging from predictive maintenance to machine learning.
Litmus transforms the way companies enable Industrial IoT, Industry 4.0 and Digital Transformation with one goal in mind – unmatched time-to-value. Our modern edge platform for industry provides instant data connectivity, ready-to-use analytics, and the ability to orchestrate applications at scale. Litmus liberates the data locked in any industrial system to transform critical edge data into actionable intelligence that can power predictive maintenance, condition-based monitoring, and machine learning. Customers include 10+ Fortune 500 manufacturing companies, while partners like Siemens, HPE, Intel and SNC Lavalin expand the Company’s path to market.
The edge is focused on bringing computing as close to the data source as possible. The edge means running fewer processes in cloud and enterprise systems and moving them closer to the devices generating data, such as a standalone computer, an IoT device, or an edge server. Localizing computing minimizes the amount of long-distance communication between a client and server, thus transforming the way data is handled, processed, and delivered.
Industrial edge computing refers to the process of connecting all assets used in manufacturing, oil and gas, energy, transportation and more. Industrial edge computing analyzes all of the data at the asset and processes it instantly for real-time analytics or to integrate optimized data into cloud systems for further processing.
Edge and cloud technologies need to work together. To suggest one offers greater value over the other is simply not true. The edge is valuable for its ability to process high-volume data in real-time and handle complex analytics at the data source. The cloud is valuable for its ability to aggregate and analyze volumes of data from all data sources, including the edge.
The edge has three main components. Edge connectivity is the ability to connect to any industrial system and collect and normalize data for immediate use. Edge intelligence is concentrating data processing and analytics functions at the edge to take action and derive value at the data source. Edge orchestration is the ability to create, deploy, manage and update edge applications.
The vast importance of the edge is beginning to come to light as more industrial use cases are enabled. The edge powers preventative maintenance, condition-based monitoring, OEE, vision systems, quality improvements and more. Edge data can also power more advanced use cases like artificial intelligence and machine learning in the cloud. The intelligent edge is powering significant operations and process improvements.