Aruba Snaps Up Cape Networks, Announces AI-Powered Analytics And Assurance Solutions

Image of Keerti Melkote, Co-Founder and President of Aruba Networks, on stage at Atmosphere 2018 discussing NetInsight and the Adaptive Network Edge
Keerti Melkote, Co-Founder and President of Aruba Networks, shares the company’s vision for the Adaptive Network Edge

Wired and wireless networks have existed for decades, but that doesn’t mean innovation has stalled. Despite years of enhancements, there’s still room for improvement in areas such as managing and securing networks. Increasingly Artificial Intelligence (AI) technologies, such as machine learning, will improve networking products. While a majority of the AI buzz surrounds solving globally important problems such as curing cancer and eliminating traffic congestion with self-driving vehicles, there are far simpler problems that AI can address today. Minimizing the complexity of troubleshooting network issues, predicting problems before they impact a user’s network experience and preventing security threats are three areas where AI technology can drive significant improvements for IT and end users.

Improving performance, simplifying the management and increasing security for an IoT-enabled world were key themes at the Aruba Network‘s Atmosphere conference in Las Vegas. Aruba shared its vision for how acquisitions such as Niara, Rasa Networks and the newly acquired Cape Networks will deliver machine learning powered products. By connecting to both Aruba and non-Aruba data sources, machine learning algorithms can provide faster insight into network and application performance issues, suggest configuration changes to improve performance and enable better threat detection inside the network.

Why networking and why now? In some ways, it’s a simple matter of all of the right technologies being available at the right time. We have large amounts of relatively inexpensive computing power at our disposal. We have vast amounts of network and device data. Companies can store this data with big data solutions, and new cloud computing solutions offer ways to kick-starting machine learning efforts. By combining those elements, networking vendors can leverage machine learning to extract patterns from multiple data sources, surfacing information that matters from the noisiness of alerts.

Given this theme, it makes sense that Hewlett Packard Enterprise announced the acquisition of privately-held Cape Networks based in Cape Town, South Africa, and San Francisco. The company will become a part of Aruba Networks, as part of the division’s effort to expand its Artificial Intelligence (AI) powered networking capabilities. Cape Networks adds a sensor-based service assurance solution that gives customers a set of network-agnostic tools for measuring and monitoring SaaS, application, and network services. The solution helps IT to get ahead of service quality issues before they occur, accelerate time to resolution, and lower cost of operations. Of course, the downside is the addition of the sensor. However, Cape Networks customers obviously believe performance gains have outweighed the challenges of adding a sensor to their networks.

In addition to the acquisition, Aruba also announced NetInsight, an AI-based analytics and assurance solution for optimizing network performance. NetInsight uses machine learning algorithms to detect problems, eliminate false positives when the network is not performing as expected and offer prescriptive recommendations to pinpoint what needs to change. The company also discussed how its Clearpass and Introspect solutions leverage machine learning to deliver behavioral analytics and can provide a closed loop from threat detection to shutting down a suspicious session.

As one of the leading wireless networking vendors, it’s nice to see Aruba pursue AI-driven simplification and automation. The company isn’t alone in this pursuit. Cisco made considerable noise about its Intent-based Networking last June which is designed to add more intelligence into networking and automate mundane tasks such as configuring network access for thousands of IoT devices. Meanwhile, upstart Mist Systems also describes itself as a new approach to wireless that applies machine learning, data science and the latest cloud technologies to deliver a smart wireless experience. It’s a competitive environment where the need to acquire machine learning expertise and apply these technologies to products has emerged as the new battleground in networking. Fortunately, the winners in this world are IT professionals that gain better dashboards, better security and enhanced performance.

This article was originally posted on my contributor column at  You can also follow me on LinkedIn as well as Twitter.