The observability platform announced a new feature in its App 360 platform called Anomaly Detection, which provides automated alerts for problems in services and microservices. 

It works by monitoring service latency and error ratios in order to detect abnormal patterns. Admins can customize how sensitive they want the anomaly detector to be, from low, which triggers after three deviations are detected, to high, which triggers after one deviation is detected. 

Admins can specify which of its services are most critical, and Anomaly Detection will focus its efforts and alerts in those services. 

It uses AI and automation to proactively identify issues, providing admins plenty of time to address those issues before they turn into problems that would impact users. 

It also automates much of the analysis process to provide admins with insights into performance of services, eliminating the need for them to manually sort through monitoring data in order to gain insight. 

“We continue to rapidly expand upon and deepen the capabilities of App 360, our groundbreaking application observability solution,” said Asaf Yigal, co-founder and CTO at “Anomaly Detection for App 360 is the kind of AI-driven automation that customers are asking for to help them optimize user experience while increasing efficiency and driving down costs. This added capability helps our customers find the ‘unknown unknowns’ lurking in their complex microservices architectures, cutting through the mountains of available data to focus on priority issues and troubleshoot faster.”

Anomaly Detection has been a feature in’s other product, Open 360, since last February.