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How Machine Learning Could Power the WAN for Handling Data

By:
2 min read

The enterprise network is feeling the pressure. From increased data flow from cloud solutions to expanding endpoints and data from Internet of Things (IoT) devices, the network is handling a lot. And if you’re watching network trends, the shift is moving towards autonomous, artificial intelligence-powered network solutions for the wide area network (WAN).

You may have begun investing in cloud applications as part of a bigger digital transformation, or if your enterprise has been adding more devices with sensors, you’re likely seeing a significant increase in your network traffic, potentially causing congestion, jitter and other performance issues. If you’re not yet feeling this pinch, you will. Analysts at IHS Markit predict that by 2030, there will be 125 billion IoT devices in use, up from 27 billion in 2017.

The future of the network
One of the network trends influencing enterprise IT is the adoption of software-defined wide area networking (SD-WAN). By employing a virtual overlay for the physical network, SD-WAN can automatically route different types of network traffic to optimize performance. As artificial intelligence and machine learning principles are added to the SD-WAN benefits, the network becomes zero-touch and adaptive to changes in the infrastructure. SD-WAN becomes stronger, faster and smarter.

The combination of SD-WAN with machine learning is an error-free network with the ability to preemptively detect potential interruptions and re-route traffic before any problem is detected. End-users don’t know that their transmission has been redirected; they simply enjoy uninterrupted connectivity.

Improved security
One of the benefits of SD-WAN is the high level of visibility that allows your engineers to quickly identify a potential breach and then isolate it to protect the rest of the network. With the added benefit of machine learning elements, your network will be able to detect abnormal activity automatically. A smart approach is becoming more critical as mobile employees may eventually outnumber their in-office counterparts.

A WAN equipped with machine learning can not only detect abnormalities in the network, it can even know the difference between a relevant user that’s logging in at unusual times versus a user that’s logging in at unusual times because Beyonce tickets just went on sale in their city at midnight.

As WAN and machine learning technologies are increasingly combined, the next step will be end-to-end automation. These network trends are emerging from necessity; there’s a need for quick troubleshooting and issue resolution that will minimize downtime in a setting with ever-increasing data flows.

When you’re interested in exploring options for your multi-location network, TailWind is your “always on” partner for high-speed broadband, asset management, and expert field technician help. Contact us at TailWind to find out how you can optimize your WAN with the industry’s most advanced offerings.

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