We are less than one month away from Interop ITX, the leading conference where tech leaders gather to share the latest innovations in the networking industry. Every year, more than 3,000 technology professionals from around the world head to Las Vegas for world-class discussions, networking opportunities and educational sessions, and here at Extreme, we’re gearing up for an exciting announcement and panel discussion at the show.
With an ever-changing technology landscape, conferences like Interop keep tech leaders informed about the newest services, platforms and skills needed to succeed in today’s industry. Interop participants are given opportunities to discuss topics ranging from cybersecurity to Big Data in a community driven environment.
This year, I’m excited to be joining industry leaders from The Networking Nerd, InterOptic and Comcast for a panel session that explores the future of infrastructure and how next-gen wireless technology will meet growing digital demands. While the future of networking is vast and difficult to predict, it’s clear that there are more people relying on wireless networks every day, and acceleration will continue thanks to mega-trends such as IoT. This is causing network engineers to shift focus towards increasing network efficiency and capacity to serve a wider user-base and more diverse device intersection.
Networks are also getting more complicated, and the demand for automation and orchestration services is on the rise – often referred to as SDN. This trend has people speculating about the possibility of utilizing Machine Learning (ML) intelligence, which TechTarget defines as a type of AI that provides computers with the ability to learn without being explicitly programmed. Through ML, it may be possible to predict the behavior of a network and prevent problems from happening. Over time, it could be possible for a network to become self-healing and reconfigure itself without being proactively monitored.
In addition to network automation and orchestration services, we also anticipate that network functionality will become increasingly important in comparison to network bandwidth. For example, sports stadiums are classic high-density venues filled with thousands of people. With more devices joining the network, IT teams may look to ML to coordinate improved efficiencies to enable more devices on the network, increase security and make it easier to deliver complicated applications in dense network environments. Extreme’s goal is to provide network engineers with the tools needed to make the management of these networks easier.