Operations | Monitoring | ITSM | DevOps | Cloud

October 2020

Anomaly detection 101

What is anomaly detection? Anomaly detection (aka outlier analysis) is a step in data mining that identifies data points, events, and/or observations that deviate from a dataset’s normal behavior. Anomalous data can indicate critical incidents, such as a technical glitch, or potential opportunities, for instance a change in consumer behavior. Machine learning is progressively being used to automate anomaly detection.

Top 6 Functional AIOps Requirements to Evaluate in Your RFP

AIOps adoption is on the rise. According to Gartner, by 2023 40 percent of DevOps teams will augment application and infrastructure monitoring tools with AIOps platform capabilities. Use cases are also expanding beyond IT to include IT Service Management (ITSM), digital experience monitoring (DEM), DevOps, Application Performance Monitoring (APM) and third party services.