What is hyperconvergence?
Of the multitude of definitions of hyperconvergence that have been tossed around by vendors over the past decade, here is the one that should cover all grounds: A data center that employs hyperconvergence (HCI) enables workloads (software) to be deployed, hosted, and managed in a data center, using hardware designed to scale and adjust for those workloads' varying requirements, along with the data center's own changing operating circumstances. The needs of the software are answered and addressed by all the hardware in the facility or in the hyperconverged cluster, acting collectively.
HCI is hardware
The key difference here is the hardware. There is a multitude of workload deployment and orchestration systems in data centers today. You're familiar with Kubernetes. You may also be familiar with the most prominent branded versions of Kubernetes today, such as VMware's Tanzu, HPE's Ezmeral, and Red Hat's OpenShift. All of these systems enable new classes of containerized workloads to be developed, tested, deployed, and managed in fully orchestrated systems, using substantial amounts of automation. And Kubernetes is promoted by champions who have publicly argued that the orchestrator fulfills the fundamental objectives of hyperconvergence, thus rendering HCI support by the hardware unnecessary and even obsolete.
But Kubernetes is not baked into hardware -- at least, not yet. By everyone's definition, HCI is hard-wired into servers. If HCI is any one thing, it is this: the hard-wiring of servers' control planes in hardware. The crux of the HCI value proposition at present is that having control in hardware, expedites processes and accelerates productivity.
Typically, the relocation of control over the network, storage, management, and security from software to hardware should result in faster processes with lower latency and broader access to system resources.
Image Source: VMware