The Critical Risk at the Edge

Virtualized Radio Access Networks (VRAN) are a very specific mobile edge network workload with performance, latency and timing sensitive requirements.

Open source accelerating innovation

Industry edge applications blend the movement of workloads and near real-time data computation closer to customers or specialized devices—like robots, cameras, and sensors—with open cloud-native platforms using microservices.  Open source is driving innovation in both hardware and software, enabling edge services that combine IT, network, operational technology (OT),  and AI/ML workloads across a highly distributed architecture and optimizing for significantly smaller footprints, including ruggedized unmanned locations.  

The software stack is quickly moving towards microservices in containers on bare metal to support the performance, latency and security needs for localized processing of the network, IoT, and AI/ML applications. In some cases, the edge nodes will be optimized for compute, network, and storage with a distributed high-performance bus aggregating telemetry and metadata transmitted to the larger data and applications platform sites.

Virtualized Radio Access Networks (VRAN) are a very specific mobile edge network workload with performance, latency and timing sensitive requirements. Red Hat has been working in the O-RAN community alongside our partners to enable multi-vendor deployments of 5G deployed in containers on bare metal. In many operator environments, vertical industry MEC workloads will be deployed alongside the 5G Core (5GC) user plane function (UPF) upstream from the VRAN access to simplify the networking, security, operational, and slicing requirements for deploying enterprise edge services.

The fact that many of these locations will be unmanned drives the need to have secure boot, zero touch automation of these edge nodes to simplify and assure the scalable delivery of edge services. The innovations are brutal automation of the nodes, the network apps, the enterprise applications, data management, and telemetry in a distributed edge compute environment that can span across on-premises, telco cloud, and multiple hyperscalers.

Distributed edge computing and 5G technologies are rapidly expanding across a hybrid collection of physical, virtual, and containerized cloud-native environments. These environments include open interoperable northbound APIs to abstract the clouds from their respective underlays, with common east-west provider APIs to select locations or environments to deploy them, and southbound APIs to select hardware used to deploy a given workload in that location. They are key to operationalizing edge services at scale.  In addition to the open interoperable APIs abstracting the network and services that enable application of policy and security for the business systems, innovations are developing to automate lifecycle management across multiple cloud environments, including hardware selection, data acceleration for AI/ML and time-sensitive applications.

We are starting to work with our customers and partners to architect a multi-phase continuous integration/continuous delivery (CI/CD) approach for cloud-native infrastructure configurations that span the network and compute domains and are distributed at scale to the edges.

Future of the Edge

In the face of uncertain world dynamics, industry leaders are actively creating living strategic plans and approaches for edge computing and 5G to address a diverse set of challenges: scale, complexity, growing services demands, data privacy protection, and location, as well as business process and organization structure.

Within these plans, many businesses focus on minimizing the attack surface with security by design across edge computing hardware, software, applications, data and networking technologies. They are also focusing their investments in open technologies and platforms that automate data management and governance at the edge to further reduce their potential business risks. While there is great promise from technology innovation, there is still an ongoing challenge of mindset and vision within organizations to think more like software application companies. This means they need to think about how they can focus on their core competencies and unique insights but also identify key areas where they must adapt and change.

The future of the edge is creating a new dynamic, one that encourages new types of edge services worldwide that securely combine data, 5G, and human-enhanced machine learning to achieve the ultimate effect of improving the quality of our lives around the world.


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