Edge computing is a distributed computing paradigm which brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth.
Adoption of Kubernetes into data centers or cloud has been remarkable since it was released in 2014. As an orchestrator of lightweight application containers, Kubernetes has emerged to handle and schedule diverse IT workloads, from virtualized network functions to AI/ML and GPU hardware resources.
Now, as the focus of many enterprises and technology vendors started to shift to edge, a new architecture may evolve as distributed applications have a different environment with a different type of latency requirement.
The technology world is looking for flexible IT infrastructure that will easily evolve to meet changing data and performance requirements in support of the onslaught of upcoming and lucrative use cases.
Providing lower latency up to 10 microseconds is a new challenge for operators to enable new technologies in the market. For this to happen, data center need to complement the higher broadband network. It forms the base digital innovation to happen in future.
Red Hat team came with an innovative hyperconvergence of OpenStack projects along with Ceph software-defined storage. A solution shows, it is possible to gain better control all edge nodes by reducing control planes and maintain the continuity and sustainability of 5G network along with the performance required by new age applications.
Integration of TF with Akraino edge stack enable enhanced features and utilizes remote compute architecture of TF. A solution can orchestrate all types of workloads like PNFs, VNFs and CNF, implement service chaining at edge sites, workload and data transfer security, automating deployment of control functions and workloads, and more.
Involvement of leading open infrastructure projects such as OpenStack and OSM as MANO suggest that such solutions are possible using open-source projects with the added benefit of controlling developing infrastructure costs.
Edge computing is the critical architecture for enabling most 5G use cases. However, requirements and expectations from edge node in terms of computing resources is in question, and with the growing number of devices and data it could become cumbersome.