Whether financial, healthcare, energy, manufacturing, or web enterprises, across all industries, a common goal is digitizing the organization as fast as possible. This allows businesses to take advantage of the many technologies that now enable greater speed and agility, and ultimately promise more revenue. As part of the movement, organizations are also looking to benefit from the Internet of Things (IoT).
As IoT adoption in the enterprise continues to take shape, organizations are finding that the diverse capabilities represent another massive increase in the number of devices and the data volumes generated by these devices in enterprise networks.
IoT infrastructure represents a broad diversity of technology. New data streams, protocols, security guidelines, and backup procedures challenge network and security operations staff. The higher volume of IoT network traffic makes capacity planning and network management more difficult, especially as new IoT deployments emerge. Also, IoT devices with inadequate security safeguards are easy targets to hijack with malware that weaponizes them for DDoS attacks. This has the potential to disrupt infrastructure as already seen in widely publicized IoT-based DDoS attacks.
So, how can digital businesses cope with these challenges without giving up on IoT? How will network monitoring tools evolve to accommodate this ever-changing IoT network landscape?
Network-based analytics is critical to managing IoT infrastructure. Network analytics has the power to examine details of the IoT communications patterns made through various protocols and correlate these to data paths traversed throughout the network. Normal or baseline performance measurements are established, and this information can then be used to identify suboptimal paths, packet loss, congestion points, or security threats.
Traffic analytics is without a doubt a very powerful tool for network staff troubleshooting IoT solutions. But many network management tools weren’t architected to handle the scale of today’s networks, none-the-less the scale of traffic introduced by millions of IoT devices. Network management tools need to address IoT network analytics challenges head-on, starting with some key requirements. They must:
So, how do legacy network management tools stack up against these requirements? Appliance-based network management solutions are too resource-constrained to handle the vast volume of data generated by IoT infrastructure. And software-based network management tools silo flow data, imposing severe constraints on analytics methods that require network data correlation across many network locations. This leads us to a big data approach to capture and report on this unstructured IoT data.
Kentik’s adoption of a big data architecture is at the core of the network monitoring platform, Kentik Detect®. This brings some real advantages for IoT analytics, because big data is not only about handling large volumes of data, but also letting network operations staff navigate through and explore that data very quickly. Key advantages include:
No matter how quickly an organization embraces IoT, it’s important to remember that the business value to be observed is not from the type of IoT device or how the device connects to the network, but rather from the types of insights that the device’s data is able to create. This data is used to understand how businesses are operating from second to second, and IoT analytics is at the heart of this revolution. To see how Kentik Detect can help your organization analyze, monitor, and react IoT traffic patterns, request a demo or sign up for a free trial today.