Sternum Enhances IoT Protection and Insights With New Kibana and Grafana Integrations

Sternum users will now be able to gain richer analytics and insights on their IoT devices through some of the most popular open-source analytics tools

Sternum, the pioneer in autonomous security and analytics for IoT devices, announced new integrations with Kibana and Grafana, two leading open-source data analysis and visualization tools. The integration allows IoT device manufacturers using Sternum’s platform to make the most of the deep visibility it provides by exploring and visualizing the incoming data from live devices through tools they are already relying on for analytics.

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“These integrations will help our customers quickly see vital information on the security and performance of their devices, so they can optimize their reliability and functionality.”

The number of connected devices is sky-rocketing, projected to climb over the 25 billion mark in 2030. As their fleets of IoT products expand by the day, device manufacturers struggle to effectively keep track of the devices at scale, missing the valuable operational and business insights the monitoring data holds.

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Through its integrations with Kibana and Grafana, Sternum delivers critical insights to device manufacturers, enabling them to streamline and optimize their resources and efforts. Customers can access, visualize, and analyze Sternum’s alerts, anomaly detections, operational insights, and runtime observability metrics directly in their pre-existing Kibana or Grafana instances. This enables them to rapidly identify and address a wide variety of potential issues, from product faults to security risks to future developments, and keep their IoT fleets protected 24/7 and operating with ironclad runtime integrity.

“The Sternum platform is designed to eliminate the IoT blind spots,” said Natali Tshuva, Sternum’s CEO. “These integrations will help our customers quickly see vital information on the security and performance of their devices, so they can optimize their reliability and functionality.”

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