A growing number of use cases across many industries are driving the shift from core data center computing to the edge, where applications and processing power are closer to the devices that create or consume data to enable faster analytics. But this new architecture requires consistent application development and IT management, especially when operating in potentially thousands of locations and clusters.

Known for its hybrid cloud strategy, Red Hat Inc. has extended its capabilities to the edge, allowing Kubernetes to ease the burden of configuring, deploying, managing and monitoring even the largest scale applications. This gives organizations the ability to develop applications once and deploy them anywhere — regardless of location, according to Steve Gordon (pictured), director of product management, cloud platforms, at Red Hat.

“More and more people are not only talking about using Kubernetes for edge, but [are] actually getting in there and doing it,” he said. “They’re really leaning into some of the things that they saw as strengths of Kubernetes, in general, that they’re now able to apply to edge computing use cases in terms of what they can actually do in terms of having a common interface to this very powerful platform that you can take to a growing multitude of footprints.”

Gordon spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during KubeCon + CloudNativeCon. They discussed how Kubernetes can enable innovation at the edge, the benefits of this strategy for developers, and Red Hat’s approach to this market. (* Disclosure below.)

Minimizing impact for developers

One of Red Hat’s main goals in pushing Kubernetes to the edge is to minimize the impact of this new business computing strategy for developers, according to Gordon.

With an edge use case, developers will often have to design apps specifically for a device, and this is a challenging proposition. But there is also the case that the intelligence already exists somewhere in the application, whether it is in the data center or in the cloud, and they just need to move it closer to that endpoint where the data is collected.

“And that’s where I think there’s a really powerful story in terms of being able to use Kubernetes and OpenShift as that interface that the application developer interacts with but can use that same interface, whether they’re running in the cloud maybe for development purposes, but also when they take it to production and it’s running somewhere else,” Gordon explained.

This new reality should accelerate and facilitate the use of artificial intelligence and machine learning, which are very data-centric applications. Instead of sending data collected by sensors and devices to a central structure for analytics, business can apply the models at the edge, minimizing the cost of moving them and the time spent doing so.

“Particularly, people may not be as cognizant of it, but even today, many times we’re talking about sites where that connectivity is actually fairly limited in some of these edge use cases … so what you’re actually putting over the pipe is something you’re still trying to minimize while trying to advance your business and improve your agility by making these decisions closer to the edge,” Gordon concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of KubeCon + CloudNativeCon. (* Disclosure: Red Hat Inc. sponsored this segment of theCUBE. Neither Red Hat nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE