What is Splunk Edge Hub?

Splunk Edge Hub represents a seamlessly integrated hardware and software package complete with built-in sensors and comprehensive connectivity libraries. This all-in-one solution streamlines the process, offering users a swift and user-friendly means of importing their IoT data into the Splunk environment. Edge Hub simplifies the integration of data sourced from environmental sensors, IoT devices, and industrial equipment—a subset of data that has traditionally posed accessibility challenges.

The Splunk Edge Hub is a multi-component solution:

• Edge Hub OS: This comprises an IoT gateway device featuring various sensors, including light, temperature, and sound sensors. It supports protocols like OPC-UA and MQTT, all encased in a robust outer shell boasting an Ingress Protection (IP) rating of IP66. Additionally, it comes preloaded with its own integrated operating system.
• Splunk Platform Compatibility: This entails an instance of the Splunk Platform, version 9.0+, or Splunk Cloud Victoria.
• Splunk Edge Hub Mobile App: Accessible on both IOS and Android platforms, this app facilitates effortless configuration of your device(s).
• Splunkbase Companion Apps: These companion apps are readily available out-of-the-box from Splunkbase.

How can Splunk Edge Hub add value?

It's common knowledge that the more data you gather, the deeper your understanding becomes. When combined with Splunk's robust analytics platform, this not only makes collected data more accessible but also offers more insights, empowering you to optimise your infrastructure, services, and processes.?

By integrating the Splunk platform with the Edge Hub's data collection methodology, you can harness these insights and take actionable steps to maximise your data's potential.

The sensor data captured by the Edge Hub provides crucial insights into process statuses, equipment conditions, system functionalities, and more. When merged with the Splunk platform, it unveils valuable trends and information hidden within this sensor data, aiding in the establishment of precise alert thresholds, KPIs, and informed decision-making.?

Additionally, leveraging the collected sensor data for predictive maintenance allows for the anticipation of potential issues, preemptively addressing them to mitigate downtime and extend equipment lifespan, thereby minimising losses.

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