Splunk introduces OT offering

Splunk Edge Hub combats data deluge by bridging the data collection gap of physical and edge environments.

  • Thursday, 20th July 2023 Posted 1 year ago in by Phil Alsop

Splunk has introduced Splunk Edge Hub, a new solution that simplifies the ingestion and analysis of data generated by sensors, IoT devices and industrial equipment. Unveiled at .conf23, Splunk Edge Hub provides more complete visibility across IT and OT environments by streaming previously hard to access data directly into the Splunk platform. Supported by Splunk partner solutions and optimised to work with the Splunk platform’s predictive analytics, Splunk Edge Hub enables advanced monitoring, investigation and response to help organisations drive digital resilience across their systems.

 

Data Deluge at the Edge

More organisations are realising the significant benefits of edge computing. This distributed computing framework brings data transfer and storage closer to the data sources themselves to improve response times and save bandwidth. While edge computing is emerging as a driver of innovation, the process of identifying and gathering data in large quantities across multiple physical and virtual sources can be incredibly complex, tedious and costly.

 

Extends Splunk’s disruptive technology to highly fragmented environments

Splunk Edge Hub streamlines edge data collection and investigation by breaking down the barriers and silos of data access across physical and virtual environments and acting as a data aggregator from other vendors’ platforms. Working right out of the box, the device can be placed in a physical environment or on top of a customer’s existing OT hardware and easily configured to immediately collect, collate and stream data to the Splunk platform.

When combined with the Splunk platform, Splunk Edge Hub enables customers to:

Monitor environmental conditions, including water, temperature, humidity and gasses to quickly and efficiently identify and remediate problematic conditions.

Perform predictive analytics to identify anomalies in manufacturing processes and surface  early indications of equipment maintenance needs or outages, to minimise operational downtime.

Achieve more comprehensive visibility across IT and OT environments to better detect, investigate and remediate threats and IT stressors from a single platform.

Build custom solutions through industry experts across environments that are historically difficult to extract data from, including transportation, oil and gas and supply chain, among others.