Keysight Network Management Solution, HawkEye
Companies reduce network downtime and
Support to improve uptime


As the scale and speed of raw network and application data continue to increase, network operations teams are facing a ceaseless barrage of alerts. Operations teams must reduce alert-induced fatigue and enhance their capabilities to troubleshoot network and application issues.

To this end, machine learning has emerged as a method to gain insights from large amounts of data.

Keysight Network Solutions announced on the 19th that it has added new machine learning capabilities to its network quality management solution, Hawkeye. With the addition of machine learning capabilities, Hawkeye helps enterprises reduce network downtime and improve network uptime.

Hawk-Eye supports automatic threshold and anomaly detection capabilities that combine machine learning-based problem detection with customizable sensitivity criteria. This feature organizes complex items and immediately notifies operations teams of potential issues. In addition, the anomaly dashboard helps operations teams easily identify potential issues in one place and analyze and resolve root causes through built-in drill-down visualizations.

Recep Ozdag, General Manager and Vice President of Visibility for Keysight Network Solutions, stated, “Network operations teams struggle to connect raw performance metrics with actual network issues,” adding, “Hawkeye’s new machine learning capabilities help operations teams quickly stay alert regarding real outages, congestion, and application performance issues.”

Meanwhile, Gartner predicted that by around 2022, more than 50% of newly developed enterprise applications would be based on machine learning or AI models.