How to Analyze and Visualize IoT Data Using Splunk and HiveMQ
Watch the Webinar
Chapters
- 14:44 - About SVA.
- 22:05 - The use case: A typical Smart Factory.
- 28:19 - Introducing: The HiveMQ-Splunk extension.
- 46:49 - Practical example of running the extension.
- 54:25 - Reaping what we sowed: Smart factory insights with Splunk.
- 59:09 - Splunk demo.
Webinar Overview
In this webinar, Dominik Pilat, Falk Flößel, Philipp Redlinger, Ronald Perzul and Ian Skerrett demonstrated the HiveMQ Splunk extension that natively forwards the MQTT data to Splunk.
MQTT has become the de facto protocol for moving IoT data between IoT devices and the cloud. MQTT’s lightweight publish/subscribe protocol makes it easy to connect thousands and even millions of devices that generate vast amounts of data. The ability to analyze and process IoT data can be challenging due to the sheer volumes of data involved. Splunk is a well-known data analysis and visualization platform that is proven to handle large amounts of real-time data from a vast amount of IT sources like servers, web services, or networking equipment. For companies that want to expand their use of Splunk to analyze IoT data, the question that arises is how you can do this in a scalable and reliable way?
HiveMQ and SVA join forces to demonstrate how you can use Splunk and HiveMQ for analysis and visualization of IoT data. During the session, SVA demonstrated the HiveMQ Splunk extension that natively forwards the MQTT data to Splunk. The session also features a demo of using Splunk and HiveMQ to collect, move and analyze Smart Factory data in real-time and historically. Thus, validating that Splunk and HiveMQ can be used as an effective, scalable and reliable IoT-analytics solution.
Read more about the HiveMQ Extensions, and specifically the HiveMQ Extension for Splunk.