Red Hat Device Edge Enhances Low Latency and AI Edge Workloads with Latest Update

Red Hat Device Edge helps unlock new opportunities for edge innovation by fueling quicker and more consistent response times

SALT LAKE CITY – KUBECON + CLOUDNATIVECON NA -

Red Hat, Inc., the world's leading provider of open source solutions, today announced Red Hat Device Edge 4.17, with updates intended to help modernize how businesses handle time-critical workloads in their most remote and distributed locations. These new low latency and near-real-time capabilities are designed to better meet the growing demand for faster, more reliable response times.

Red Hat Device Edge combines an enterprise-ready and supported distribution of the Red Hat-led open source community project MicroShift (a lightweight Kubernetes distribution derived from the edge capabilities of Red Hat OpenShift) along with Red Hat Enterprise Linux and Red Hat Ansible Automation Platform. Red Hat Device Edge provides a more consistent platform for resource-constrained edge environments, where small form factor devices and compute resources require lower-latency operations to more effectively collect, analyze and respond to actions and data in near real-time.

From industrial environments and autonomous vehicles to online gaming and smart cities, these environments are a driving force in requiring applications that are more timely, more responsive and more consistent. To support use cases demanding predictability and low latency, organizations can now implement solutions with latency requirements well below one millisecond, while also providing reliable, deterministic performance to ensure consistent outcomes. With support for these increasingly critical workloads, Red Hat Device Edge 4.17 provides a path to bringing an entirely new class of edge use cases into reality, even if they require near-real-time response times and data processing.

Unlocking AI’s potential at the edge

Speed and agility remain constant demands for IT leaders, with artificial intelligence and machine learning (AI/ML) at the edge providing a powerful combination of capabilities to enable faster, more nimble operations. By extending AI to the edge, businesses can collect data, process images, train models, run inference and more, but need to meet the expectations of real-time responses, offline functionality, and enhanced security. Factory floors, for example, can experience success or failure in a given operation with a delay of just 20 milliseconds.

Low and predictable latency capabilities can help enable AI-driven controls and functions to streamline processes. Red Hat Device Edge 4.17 enhances these workloads by adding functionality to better support them. Red Hat recently announced the tech preview of Red Hat Device Edge on NVIDIA Jetson Orin™ and NVIDIA IGX Orin™, with Red Hat Enterprise Linux 9.4 providing additional support for FIPS-enabled edge images. This range of solutions, from the Jetson Orin Nano to the enterprise-ready NVIDIA IGX platform, empowers businesses to achieve near-real-time precision and innovation without sacrificing baseline operational IT needs like enhanced system security.

IPV6 support with single- and dual- stack integration

Red Hat Device Edge also adds additional updates around IPv6 support that allows for enhanced networking capabilities, whether it's for single-stack IPv6 deployments or dual-stack (IPv4 and IPv6) configurations, adding flexibility to infrastructure management.

Supporting Quotes

Francis Chow, vice president and general manager, In-Vehicle Operating System and Edge, Red Hat
“Edge computing is transforming industries worldwide, and Red Hat is dedicated to empowering organizations to harness its full potential. With the latest features, Red Hat Device Edge will not only help businesses unlock a wealth of new opportunities and use cases but also lower the barrier to entry for adopting edge and AI technologies. This means businesses of all sizes can stay competitive while seamlessly leveraging AI at the edge.”

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