Red Hat Device Edge
Bring cloud consistency to the edge—even on your most resource-constrained devices.
What is Device Edge?
Red Hat Device Edge supports diverse workloads on resource-constrained devices like IoT gateways and industrial controllers. It provides a consistent management experience using lightweight Kubernetes, edge-optimized Linux, and Red Hat Edge Manager, ensuring reliability even in field-deployed environments with limited connectivity or technical support.
What’s included?
Red Hat Enterprise Linux
Generate edge-optimized OS images to handle a variety of use cases and workloads with Red Hat’s secure and stable operating system. Leverage management services, intelligent device updates, and zero-touch provisioning for visibility and control over field-deployed edge devices.
MicroShift
MicroShift is a lightweight Kubernetes container orchestration solution built from the edge capabilities of Red Hat OpenShift®. MicroShift uses a consistent Kubernetes API to extend operational consistency for hybrid cloud deployments, all the way to the edge
Red Hat Edge Manager
Edge Manager provides a simple and scalable experience for managing fleets of edge devices, enhancing control, security capabilities, and visibility for customers.
Features
Use case based deployment
Deploy and manage virtual or containerized workloads on resource-constrained edge devices, orchestrated with or without Kubernetes, on the same edge-optimized operating system, with operations consistency from core to cloud to edge.
Lightweight Kubernetes
Use container orchestration through MicroShift, an open source project built with the edge capabilities of Red Hat OpenShift, optimized for resource constrained devices in remote or disconnected areas.
Edge-optimized OS capabilities
Automated device onboarding, customizable image generation, over-the-air updates, and intelligent rollbacks provided by Red Hat Enterprise Linux minimize the need for on-site expertise.
Consistent Kubernetes API
Deploy and manage virtual or containerized workloads on resource-constrained edge devices, orchestrated with or without Kubernetes, on the same edge-optimized operating system, with operations consistency from core to cloud to edge.
Lifecycle management
Security-focused, full lifecycle management for large-scale fleets of edge devices from deployment to decommissioning.
GitOps for consistency
Use Git code repositories to deploy a consistent platform image across potentially tens of thousands devices.
Benefits
Deploy only what you need
The flexibility to meet the needs of different use cases on devices with limited hardware resources, at various locations, running multiple types of workloads.
Use one platform for your workload journey
Start with Red Hat Enterprise Linux, then add Kubernetes, or deploy both. Red Hat Device Edge provides the flexibility to meet evolving use cases.
Ensure operational consistency
Use the same tools and processes across your edge and hybrid cloud deployments so that your teams can focus on driving innovation as the architecture scales.
Scaling operations
Remotely monitor and centrally configure all edge devices, including disconnected ones, to ensure consistent configuration and boost operational efficiency.
Buying options
Red Hat Device Edge is available at 2 subscription levels.
Red Hat Device Edge (recommended)
Our standard offering, featuring Red Hat Enterprise Linux as the edge-optimized OS, MicroShift for lightweight Kubernetes container orchestration, and Red Hat Ansible Automation Platform for initial device deployments and ongoing management through automation at scale.
- Red Hat Enterprise Linux
- MicroShift
- Red Hat Edge Manager
Red Hat Device Edge Essentials
For users with an existing Ansible Automation Platform subscription, or who plan to use a different management solution, this tier includes edge-optimized Red Hat Enterprise Linux and lightweight Kubernetes with MicroShift.
-
Red Hat Enterprise Linux
-
MicroShift
Use cases
Industrial operations
Industrial operations
Run plant-floor and site systems on the same Linux foundation you use in the rest of the hybrid cloud. Put containers, virtual machines, or both on small, hard-to-reach devices—gateways, controllers, rugged PCs—and keep them on one image and one update process, even when there is no IT staff on site.
Physical AI
Physical AI
Run inference next to the sensor, camera, or machine so the system can perceive, decide, and act without waiting on a cloud round trip. Train and govern models with Red Hat AI in the datacenter or cloud, then deploy them to Device Edge for vision, predictive maintenance, and machine control—including when the device is offline.
Fleets and assets in motion
Fleets and assets in motion
Treat vehicles, meters, aircraft, and other field assets as one fleet instead of thousands of unique boxes. Devices pull a known-good operating system and application image when they have a connection, stay on the last working image when they do not, and do not need a specialist on site to stay in service.
Disconnected / limited connectivity
Disconnected / limited connectivity
Keep software current and consistent when the network is slow, intermittent, or gone. Devices reach out when they can; you set the desired operating system and application state once. Updates apply fully or roll back, so field systems are not left in a partial state.
Keep reading
Datasheet
Deploy workloads in resource-constrained devices at the far edge
Red Hat® Device Edge comes equipped with the capabilities needed to deploy and manage edge devices and their workloads at scale.
Press release
Red Hat Introduces Red Hat Edge Manager for Overseeing Fleets of Devices
Red Hat Edge Manager delivers greater scalability and lets you manage thousands of edge devices from a single console.
Article
Extend Red Hat OpenShift capabilities to edge computing environments
Edge computing with Red Hat OpenShift provides consistent, reliable, and flexible infrastructure and tooling.
Blog
Red Hat Device Edge on NVIDIA Jetson Orin and IGX Orin now available in tech preview
Red Hat Device Edge provides the necessary capacities for AI processes in the cloud and at the edge.
