November 2016 Summaries

At New Relic, they're leveraging advanced algorithms and machine learning to provide customers with more accurate insights into their dynamic environments. The company's latest advancement, Dynamic Baseline Alerts, aims to address the challenges posed by increasingly complex systems, where traditional monitoring tools may struggle to keep up. By analyzing historical data, seasonality, and recent behavior, Dynamic Baseline Alerts can predict future performance and create dynamic alert thresholds that account for changing system behavior. This feature is particularly useful for managing unknown or newly introduced systems, as well as those with dynamic performance profiles and distinct seasonality. The benefits of Dynamic Baseline Alerts include confident alert thresholds, minute-scale granularity, and fast alerts configuration, making it an exciting addition to New Relic's product suite.

New Relic has introduced Dynamic Baseline Alerts, leveraging advanced algorithms and machine learning to provide more accurate insights into increasingly complex software environments. This feature, previewed at FutureStack16, addresses the challenges posed by dynamic software systems, such as the rapid evolution from monolithic applications to microservices and server-less stacks. By analyzing historical data for recent behavior, trends, and seasonality, Dynamic Baseline Alerts create predictive alert thresholds, allowing operations teams to better manage systems with unknown or dynamic performance profiles. These alerts offer minute-scale granularity and a Chart Preview feature for fine-tuning thresholds, enabling faster alert configuration even with limited data. Currently in limited release, New Relic plans to roll out Dynamic Baseline Alerts to customers in phases, aiming to enhance operational efficiency and reduce the risk of false alarms.