Davis® AI

Dynatrace uses a sophisticated AI causation engine called Davis® to automatically detect performance anomalies in your applications, services, and infrastructure. Dynatrace uses detected problems to report and alert on abnormal situations, such as performance degradations, improper functionality, or lack of availability (that is, problems represent anomalies in baseline system performance).

Use cases

Detect abnormal behavior in real time based on static or auto-adaptive thresholds, or more complex AI models approach, such as seasonal baselines.
Quickly react and fix anomalies with automated root cause analysis.
Save time on manually reproducing errors by retracing the problem development from its appearance to the current status.
Use DQL to create personalized health dashboards and filter the reported information.

Concepts

Anomaly detection

Learn how Davis AI can detect abnormal behavior and the mechanisms behind the process.

Root cause analysis

Learn about automated root cause analysis and problem lifecycle.

AI models

Learn how can you use AI models to analyze stored metric data, predict future values, and adjust baseline for more precise anomaly detection.

Integrations

Learn about the integration options for Davis AI to optimize your workflow.

Getting started

Investigate the root cause of a problem

Triage, investigate, and remediate incidences in the Problems app.

Configure Anomaly Detection

Configure monitoring strategy and create event triggering templates in the Davis Anomaly Detection app.