The edge-optimized Kubernetes and Linux deployment targets resource-constrained devices
Red Hat on Tuesday announced Red Hat Device Edge, a new Kubernetes and Linux deployment aimed at resource-constrained edge devices. The new deployment is currently in development, but is planned as a developer preview early next year, and expected to be generally available with full support later in 2023.
Device Edge is suitable for deployment on small devices like robots, IoT gateways, points of sale, public transportation and more, according to the company. The solution was developed using MicroShift, a lightweight open-source Kubernetes orchestrator built from Red Hat’s OpenShift.
“Red Hat Device Edge will be aimed at organizations who require small factor edge devices with support for bare metal, virtualized or containerized applications, regardless of industry,” the company said.
Red Hat Device Edge will enable IT teams already familiar with Kubernetes to build cloud-native edge computing apps with a greater consistency of operations across the hybrid cloud, Red Hat said. Red Hat Device Edge reduces compute requirements by up to 50%, compared to traditional Kubernetes edge configurations. The edge-optimized Linux operating system is tailored for small edge devices by supporting “intelligent” updates that use minimum bandwidth. The software also features smart management characteristics with advanced features like zero-touch provisioning, system health visibility, and updates with automatic rollbacks.
Red Hat counts Lockheed Martin among the early adopters of Red Hat Device Edge. The company had already been collaborating with Red Hat on the MicroShift product, it noted. Red Hat and Lockheed Martin have demonstrated Red Hat Device Edge’s use with Lockheed Martin’s Stalker Unmanned Aerial System (UAS), a military drone platform used for reconnaissance and target acquisition.
“The new software – now managed on platform by Red Hat Device Edge – enabled the Stalker to deploy updated AI-based computer vision capabilities, also known as automated target recognition capabilities. As a result, Stalker was able to more accurately classify the military target, providing more useful ISR data and enhancing the situational awareness of the threat environment for U.S. military decision-makers,” said Red Hat.
Lockheed Martin’s efforts with Red Hat Device Edge aren’t limited to defense operations work; the company is also using it in wildfire management and in outer space, Red Hat said. Another early adopter is Swiss multinational ABB, known for robotics and automation tech – the company has adopted Red Hat Device Edge for use with its Ability Edgenius, its cloud-managed edge platform for industrial software apps. ABB is planning to use Red Hat Device Edge for ABB Ability Edgenius on resource-constrained devices, Red Hat said.
Other potential applications for Red Hat Device Edge include public transportation nodes, where edge devices require faster AI/ML-led processing to analyze data locally, in real-time, such as railway operations, mining, in cars or autonomous vehicles. Weather monitoring stations are another area where Red Hat sees Device Edge coming in handy, along with “emerging edge constrained scenarios where thousands of edge devices may be running applications in locations that make weight, temperature and connectivity all major concerns.”
Edge solutions took center stage at Red Hat Summit this past May. Red Hat’s edge play consists of “a set of new cross-portfolio edge features and capabilities,” it said, with the goal of helping Red Hat customers adapt to edge computing. Red Hat wants to make it easer and faster to deploy edge solutions, and thinks it can help by improving edge security and app lifecycle management.
Red Hat Edge comprises a broad set of technologies, according to the company. It starts with edge-centric changes to the company’s Enterprise Linux and OpenShift deployments as the foundation. Red Hat’s Ansible adds IT edge deployment automation, with Red Hat’s Advanced Cluster Management for Kubernetes providing cloud app orchestration and OpenShift Data Foundation edge storage.
