Red Hat brings automation to Kubernetes-powered edge with OpenShift, Cluster Management tool

The company said that the latest version of Red Hat OpenShift and Red Hat Advanced Cluster Management for Kubernetes enable organizations to address the needs of edge workloads such as the use of artificial intelligence (AI) and machine learning (ML) in industrial manufacturing use cases. The goal of the updated software: make it easier to manage and scale hybrid cloud environments from a single control point.

Red Hat cited a survey by Analysys Mason, noting that edge computing is a top strategic priority for many operators with 30% of them already in the process of deploying an edge cloud while 57% are currently outlining their plans to do so in the next year.

There is a good deal of momentum behind the use of Kubernetes in edge computing, with one advantage being that Kubernetes is designed to scale and extend across environments and can offer the same operational consistency at the edge as it does in the cloud. Red Hat notes that the Kubernetes offers interoperability and compatibility with existing core datacenter systems because of its basis in open standards.  while the flexible nature of the container orchestration engine means it can serve as a launchpad for even newer innovations.

Red Hat’s new capabilities intended for edge use cases include:

– 3-node cluster support within Red Hat OpenShift 4.5, bringing the full capabilities of enterprise Kubernetes to bear at the network’s edge in a smaller footprint. Combining supervisor and worker nodes, 3-node clusters scale down the size of a Kubernetes deployment without compromising on capabilities, making it ideal for edge sites that are space-constrained while still needing the breadth of Kubernetes features.

– Management of thousands of edge sites with Red Hat Advanced Cluster Management for Kubernetes along with core sites via a single consistent view across the hybrid cloud making highly scaled-out edge architectures as manageable, consistent, compliant and secure as standard datacenter deployments.

– Evolving the operating system to meet the demands of the edge with the continued leadership and innovation of Red Hat Enterprise Linux, backed by the platform’s long history of running remote workloads.

In an interview with Edge Industry Review, Chad Foster, who is currently responsible for Cross-Industry Sales Development for IBM/Red Hat, said “If you think about things like smart manufacturing, smart farming, automotive, telemedicine, all the use cases that we know that are on the horizon, all of these are going to require a blend of environments.”

“We want CIOs and CTOs to have an optionality of choice of where they run their workloads. And by us focusing on the workloads and making sure that we enable workload compatibility within OpenShift products across multiple cloud environments, we feel like that’s going to be a winning formula because there’s always been some form of lock-in for customers [historically speaking],” Foster said.

Justin Boitano, vice president and general manager, enterprise and edge computing, NVIDIA said that “combining Red Hat OpenShift and the NVIDIA EGX AI platform allows virtually every industry to run their GPU-accelerated AI applications on a unified cloud-native platform from the public cloud to core data center, and now at the edge.”

Article Topics

automation  |  edge compute  |  IIoT  |  Kubernetes  |  open source  |  OpenShift  |  Red Hat