LAS VEGAS: The Internet of Things (IoT) is set to be the next big growth area for Splunk deployments, as the company builds out its platform and helps its customers harvest data from connected devices and apps.
With the latest version of Splunk Enterprise offering an HTTP event collector that facilitates better collection of IoT data, the company is clearly aiming to be at the forefront of this burgeoning market.
In an interview with V3 at Splunk's .conf conference, Brian Gilmore, solution expert for IoT at Splunk, explained the company has data science teams and developers looking at adding more capabilities to the core Splunk operational analytics platform to better crunch IoT data.
"As the demands for IoT have changed the type of analytics we have to do, we brought in teams who focus on areas [of IoT data]," he said, adding that Splunk has introduced the ability to add geolocation information to support insights gleaned through data analysis.
"What's really exciting for me is that as we continue to put resources into our cyber security capabilities, into our machine learning capabilities or into our advanced visualisation capabilities and anything we would build for business and operational analytics," he said.
"Those premium [products] for Splunk will likely either have components or an entire [service] that will apply very well to the IoT data streaming from these environments."
While many technology companies may be eyeing-up the IoT arena or developing products to support and manage it, Gilmore noted that Splunk already has a platform in place that enables sophisticated data analytics for existing IoT networks.
As such, the company has the likes of BMW on its books, with the carmaker using Splunk to monitor data from sensors in its hybrid electric cars, and to analyse industrial data fed back into its Splunk deployments from its factory assembly lines.
Given much of the data generated in the IoT world is real-time operational machine data - the kind Splunk is focused on analysing - the company see itsself as having a headstart by being able to push deeper into the sector, with a platform ready to handle the streams of data produced from the IoT in industrial, commercial and consumer sectors.
"Splunk is a horizontal platform. It is great for machine data advanced analytics; it allows collection of large volumes of streaming structured, unstructured, and semi-structured data. While our platform was built originally to solve issues around data sources in IT, those types of data are the ones we're seeing in IoT as well," Gilmore said.
He noted that while Splunk's core platform was designed to handle data that allows users to work out what is happening in their web servers and IT infrastructure, those servers have effectively been repackaged into IoT devices but still serve up the same types of data.
"What's interesting has been to see how much forethought the engineers and founders had in terms of their acknowledgement that the future will bring in new things," he said.
"It is a really solid platform for analysing streaming machine data, and that is going to be an absolute requirement for the IoT and industrial environments," he added.
Gilmore said that while Splunk offers an open platform not targeted at any specific industry, rather allowing its customers to dictate how its analytics products are used, Splunk does see manufacturing, transport and logistics industries as major areas that will use Splunk deployments to analyse IoT data.
These industries will primarily use such analytics to facilitate predictive maintenance to minimise downtime in operations and drive business efficiency.
But Splunk can also be used with consumer devices and products, with Gilmore explaining that app developers and consumer device brands can use analytics to see how their products are being used by their customers, even if that data is anonymised.
This will allow companies to ensure their existing products are satisfactory and help inform the development of future offerings.
While Splunk may be pushing deeper into the IoT, it has also bolstered its main product offerings with a suite of updates, and has also added a dose of machine learning into its security products.
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