Precision OT launching optical SDN analytics

At the SCTE/ISBE Cable-Tec Expo in Atlanta, Precision OT will be launching its machine learning-powered software-defined networking ...

Oct 22nd, 2018
Precision OT launching optical SDN analytics
Precision OT launching optical SDN analytics

At the SCTE/ISBE Cable-Tec Expo in Atlanta,Precision OT will be launching its machine learning-powered software-defined networking (SDN) application designed to monitor and analyze the physical layer of an optical software-defined network. Named Lightseer, the software is designed to provide network administrators with real-time data all the way down to transceivers and individual optical links. It is intended to help operators manage and automate the logistics of monitoring and configuring increasingly complicated networks.

Lightseer addresses data at the optical level and is designed to avoid vendor lock by streamlining optical network monitoring across white boxes and legacy devices.

"At Precision OT, we believe software-defined networks and white box technologies will aid in the operability of 5G networks, Metro Ethernet, hybrid fiber/coax networks and more," said Todd Davis, CEO of Precision OT. "By covering all aspects of real-time optical monitoring and being compatible with a wide variety of white box networking equipment, Lightseer meets the demand to ease logistical complexity and improve network intelligence. As today's telecom companies prepare their software-defined networks for IoT and AI applications, we're filling the gap for custom solutions that can improve the intelligence and agility of optical networks."

Features include:

  • Real-time optical monitoring showing the state and integrity of the optical network (ability to view from high level down to individual optical links)
  • Wavelength density monitoring for CWDM/DWDM networks
  • Compatible throughout a variety of white box networking equipment and off-the-shelf SDN controllers
  • Integration with legacy networking equipment
  • Live management and configuration of optics deployed in the software-defined network (inventory, tuning, etc.)
  • Machine learning for predictive analytics to forecast optical failures and anomalies before they cause network downtime
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