Juniper Networks Adds AI to Pump Up Automation Capabilities

Juniper Networks today announced several new features and products that enhance its AI-powered networking capabilities. The company has expanded its Mist technology to work over the wired network, data center and, most recently, SD-WAN.

In 2019, Juniper paid just over $400 million to acquire Fog systems, which now seems like a steal as it has become the cornerstone of the company’s AI strategy. At the time of acquisition, Mist was arguably the best AI engine for Wi-Fi. The company started with wireless LAN, which can be the most difficult network area to troubleshoot because the root cause is difficult to diagnose. Our research has shown that some technicians spend up to a quarter of their time doing nothing but fixing Wi-Fi issues.

This most recent batch of announcements builds on current capabilities and enhances Juniper’s “Experience-First Networking” vision, where the network must be able to deliver the best user and customer experiences. New capabilities include:

Improved wireless performance with automatic placement and orientation of Juniper Access Points (APs)

The placement of APs is both essential to a great wireless experience and challenging to get right. Usually, IT professionals will conduct a site survey and then use that as the plan for how to place them and how to orient them. Site surveys can often overlook things in buildings that can affect performance. It is also easy for a network engineer to misread the plan and put the APs in the wrong location.

Another factor is that things are changing in a building and the site survey may now be correct, but things like new equipment, floor redesign or electronics may justify the need for new AP placement.

Juniper Mist now automatically validates the actual placement and orientation of APs after installation and highlights misplaced APs that need to be corrected. The function uses the Juniper Wired Assurance Servicewho uses the company virtual Bluetooth Low Energy (vBLE) antenna arrays combined with machine learning-based algorithms to automatically map Mist Wi-Fi 6 or 6E APs to a map in the Juniper Mist dashboard.

The location, orientation and distance between APs are calculated and displayed to reduce or even eliminate implementation problems. As the environment changes, the dashboard indicates where to move APs to.

Reduction of average repair time through AIops actions and network insights

Mist includes a virtual network assistant called marvis that allows network administrators to interact with the network through conversational AI. Marvis includes several “Actions‘, which is a simple way of saying that it identifies a condition that is causing a network problem. With this release, Juniper has added new actions to address common but disruptive network issues such as DHCP error ranges and wired authentication. These actions help reduce the mean time to resolution, which ultimately increases user and customer experience†

Juniper is also releasing a Marvis Windows client to complement the current Android client. When installed on a Windows computer, Mist has a better understanding of network issues that can affect performance and connectivity. The information is sent to Mist AI so that Marvis can make informed decisions about what to recommend. Using a client eliminates the need for an overlay sensor network.

Increased scalability with less complexity through a new Ethernet switch

Juniper added a new switch to his EX family of switches† The EX4100 is optimized for high scalability with simplified operations. The new switch takes the complexity out of deploying an EVPN-VXLAN fabric that extends to the distribution and access layers. It also includes some key security capabilities, such as MACsec AES 256 and standards-based micro-segmentation using group-based policies. This becomes important as the number of IoT devices in an enterprise grows.

Overall, the company is bringing cloud principles to the network to ensure enhanced user and network engineering experiences. For example, Mist AI accelerates deployment times through zero-touch provisioning and automated workflows. It also enables rapid troubleshooting with full-stack event correlation and proactive anomaly detection, which can address issues before they affect the user. Our research has shown that about three-quarters of trouble tickets are opened by users, not IT, who constantly leave network engineers behind. Juniper’s goal is to reverse this trend using network data and AI analysis†

As a company, Juniper has done a great job moving from a company that brings technology, speeds and feeds to market to one that can articulate its value in business terms. Companies compete on both user and customer experience, and Juniper’s use of AI allows it to directly influence both. This is important not only for IT professionals, but also for business leaders.

Chris Preimesberger is a former editor of eWEEK and a regular VentureBeat contributor who has been reporting and analyzing IT trends and products for more than two decades.

Zeus Kerravala is the founder and lead analyst with ZK Research† He spent 10 years at Yankee Group, previously holding a number of corporate IT positions. Kerravala is considered one of the top 10 IT analysts in the world by Apollo Research, which evaluated 3,960 technology analysts and their individual statistics on press coverage.