Aerohive introduces Client 360, machine-learning, client-comparative analytics

Aerohive Networks has introduced a new machine learning, client-comparative analytics capability for real-time and client-experience performance monitoring and optimization. Client 360 is available in all of Aerohive’s deployment options (Public Cloud, Private Cloud, and On-Premises).

Client 360 leverages Aerohive’s microservices cloud architecture and native machine-learning capability to collect, process, and analyze data and distill the data to consumable and actionable insights.

Client 360 tracks the client experience using a time-slider that adjusts for day, week, and month along several vectors such as:

  • Day, Week, Month client usage and health when the client was actually connected to the network,
  • Session and aggregate views of client location and experience, where the client sent and received the most data when connected to the network,
  • Session and aggregate views of client location and experience, where the client spent the most time when connected to the network,
  • Client trail as the client roams across the network with corresponding roaming and network services health (i.e. DHCP, DNS, Auth, Internet Access, etc.), comparing and measuring individual client experiences against expected behavior through machine-learning capabilities.

Aerohive pioneered cloud networking to simplify licensing, deploying, monitoring, scaling, and upgrading access points, switches, and branch routers for the distributed enterprise.

With Client 360 Aerohive has now extended its cloud-networking and native machine-learning capability to simplify an IT Administrator’s ability to check on, verify, and/or troubleshoot a client’s experience in a single view.

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Aerohive introduces Client 360, machine-learning, client-comparative analytics