Artificial intelligence and 5G—two of tech’s biggest buzzwords—are intrinsically linked to edge computing and the hybrid cloud. In simplest terms, 5G fuels edge computing in the cloud, which will lead to more opportunities for AI and automation. But those opportunities won’t be realized if having a hybrid cloud is seen as a simple destination or box to be checked. Instead, it must be understood as a whole new operating model.
For a very simple example of edge computing and its relationship to the cloud, consider a Tesla. The car’s many sensors and cameras can only have situational awareness if they can respond to what they’re seeing—whether trees, other cars, or traffic—in near real-time. There isn’t the time, latency, or bandwidth to send data back to a central, public cloud data center. Instead, the cloud must be brought to the edge.
Thus, a Tesla isn’t just a next-generation car; it’s an edge compute node. But even with Tesla, a relatively straightforward use case, building and deploying the edge node is just the beginning. In order to unlock the full promise of these technologies, an entire paradigm shift is required.
Becoming Cloud Native
With cloud at the center of a whole new operating model, organizations will have distributed DevOps teams spinning up new applications in real time. They’re often disconnected from the infrastructure team, which is tasked with managing the cloud architecture. The goal is not to deploy a brand new edge node for every mission. Instead, it’s to build new applications on the existing node to meet changing demands. A Tesla, once again, has hundreds of sensors in it, including cameras on its sides and back. Recently, developers added a functionality to allow dri ..
Support the originator by clicking the read the rest link below.
