Anomaly detection

2-min read

Davis AI monitors your applications, services, and infrastructure to learn baseline metrics and the overall health of each component, including response times. Variables such as geolocation, browser type, operating system, connection bandwidth, and user actions factor into the baseline. This automated baselining enables Dynatrace to detect anomalies at a granular level and notify you of problems in real time. Customize thresholds by adapting the sensitivity of problem detection or by defining your own static thresholds.

Use cases

Use metric events to get alerted about problems in your environment.
Configure manually or use an autoadaptive threshold to detect abnormal behavior.
Set up alerts for custom events.

Concepts

Anomaly detection configuration

Learn about anomaly detection configuration, its components and setting up an alert for missing measurements.

Autoadaptive thresholds for anomaly detection

Learn how Davis adapts thresholds for multiple entities within the scope of an anomaly detection configuration.

Automated multi-dimensional baselining

Learn how Dynatrace AI automatically calculates baselines based on a multi-dimensional baselining scheme.

Static thresholds for anomaly detection

Learn how and when to use a static threshold for anomaly detection.

Getting started

Metric events

Learn about metric events in Dynatrace.

Adjust the sensitivity of anomaly detection

Learn how to adapt the sensitivity of problem detection in Dynatrace.