Keysight Technologies, Inc. announced the addition of new machine learning (ML) features in the Hawkeye active network monitoring platform from Ixia. 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% of new enterprise applications developed will incorporate machine learning or artificial intelligence models,” according to Gartner. 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.