MantisNet's recently published whitepaper, Solutions for the Next Generation of 5G and IoT Network Deployments, focuses on the enablement of real-time network intelligence, monitoring and analysis at the edge. This topic is very timely as telecommunications carriers are readying their fifth generation, or 5G, network deployments. The promise of higher speeds, lower latency and greater throughput has arrived to deliver improved digital experiences and further enable the continual growth of Internet of Things (IoT) connectivity and interactions.
5G and IoT experiences are anything from augmented or virtual reality (AR/VR) consumer experiences, enterprise communications, streaming content, connected cities, autonomous vehicles, interactive digital health, industrial automation and connected homes - the need for reliable 5G connectivity among the increased density of devices leveraging those networks is here.
So, with more devices connecting this creates new concerns around performance and security for network and security operations teams. What can enterprise networks do from a 5G network visibility, intelligence and monitoring aspect to prepare to handle the deluge of data coming their way from additional end-points?
First, “the edge”, or the edge of networks receiving data is the fundamental location to focus on for optimizing traffic delivering 5G and IoT experiences. These next generation networks will increasingly rely on hybrid SDN and advanced analytics specifically working in conjunction with analytic workflows for business process logic execution. Therefore, we see a critical focus on implementing monitoring and analytics to enable network intelligence at the edge.
The only way to effectively manage and control complex network topologies and the sheer volume of traffic is to move the intelligence closer to where the data is generated. Handing traffic from this point will help to more efficiently route various network layer traffic to where it needs to go before entering any backhaul networks for telecommunications and definitely before direct ingestion at the data center or colocation. Pre-filtering and managing network traffic closer to the edge (by specific network protocol as an example) will make more efficient use of legacy technologies designed to handle the traffic. Additionally, by handling traffic at the edge network and security operations teams get a front row seat and immediate visibility to the real-time management needs to maintain performance and security operations of these network data flows.
For additional information you can download the whitepaper.
