Equipment malfunction are now closely monitored and quickly rectified using distributed automated systems

 Take for example modern, high-speed manufacturing processes with video and sensors to ensure higher quality and safety. In the oil & gas industry, leak detection and equipment malfunction are now closely monitored and quickly rectified using distributed automated systems. In the public sector, smart cities will rely on cameras, sensors, and other IoT devices to monitor public safety, optimize traffic, maintain infrastructure, and promote energy efficiency. 

In all industries, a variety of infrastructure – compute/GPUs, VMs, containerized apps, storage (HCI, AI, and ML) and wireless, wired, and WAN network devices will be needed to support these requirements at the “edge.”

According to IDC, by 2023, more than 50% of new enterprise IT infrastructure will be allocated to edge environments, and these edge environments will have to be connected reliably and securely to computer engineering definition and cloud networks. But as enterprises make this shift, many find themselves unprepared. An increasing number of enterprise edges are built on siloed compute and storage systems, with disjointed network architectures not only in the campus, data center, and branch, but now at emerging edge locations. With this explosion of centers of data, achieving scale using legacy approaches is hard. Perhaps impossible.