Keysight Technologies,
Inc., a leading technology company that helps enterprises, service
providers and governments accelerate innovation to connect and secure the world, today announced the addition of new machine learning (ML)
features in the
Hawkeye active network monitoring platform from
Ixia, a Keysight business. The
addition of machine learning enables Hawkeye to help enterprises shorten
outages and improve network uptime by quickly detecting, identifying and
resolving network anomalies.
As the volume and velocity of
raw network and application data continues to increase, network operations
teams are faced with a flood of alerts. These teams need to reduce alert
fatigue and increase their ability to troubleshoot network and application
issues. In response, machine learning has emerged as an innovative way to gain
insights from vast amounts of data. "By
2022, over 50 percent of new enterprise applications developed will incorporate
machine learning or artificial intelligence models," according to Gartner.
"Keysight's Hawkeye utilizes
the power of machine learning to help network operations teams make sense of
their increasingly complex networks,"
said Recep Ozdag, vice president and general manager of visibility at
Keysight's Network
Applications & Security Group (formerly Ixia Solutions Group).
"Network operations teams struggle to correlate raw performance metrics with
actual network problems. Hawkeye's new machine learning capabilities offer
insight into meaningful variations enabling these teams to quickly be alerted
to real outages, congestion and application performance issues."
Hawkeye features automatic threshold and outlier detection which combines
machine learning-based problem detection with customizable sensitivity
criteria. It cuts through clutter and immediately notifies network operations
teams of potential problems. An outlier dashboard
enables these teams to easily see potential problems in one place offering
built-in, drill down visualizations that assist with root cause analysis and resolution.