How Davis Works

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Davis is Dynatrace’s AI engine that is purpose-built for today’s web-scale enterprise clouds. Davis analyzes complex dependencies, creates application topology dynamically and helps you in anomaly detection.

A Highlevel View of the Davis AI Engine

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1. Intelligent anomaly detection

Problems in Dynatrace represent anomalies, i.e. deviations from a normal behavior or state. Such anomalies can be, for example, a slow service or a slow user login to an application. Whenever a problem is detected, Dynatrace raises a specific problem event indicating such an anomaly.

2. Smart Baselines & Problems

Context-rich data collection and baselining are the two fundamental pillars that anomaly detection is built on. A huge amount of high-quality and accurate data is necessary to determine baselines that can effectively be used to distinguish between normal and anomalous situations.

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

3. Causation versus correlation

Davis uses deterministic AI which is a radically different approach to traditional machine learning. It performs an automatic fault-tree analysis, the same methodology NASA and the FAA are using. This is causation not correlation. The resulting root cause analysis is precise and reproducible step by step.

How Dynatrace Davis analyzes a critical situation

Davis processes all data, whether it comes from a mainframe, the infrastructure, a cloud platform or the CI/CD pipeline. This enables Davis to provide the granularity and precision needed to automate the enterprise cloud, unlike traditional AI.

  • Automatic detection of topology and communications - As Oneagent constantly discovers new resources in the environment and builds it into the topology maps. The direction of the communication is shown by the arrow with solid line between entities representing active communication.
  • Metric and event-based detection of abnormal component states - The new AI engine automatically checks all component metrics for suspicious behavior. This involves the near real-time analysis of thousands of topologically related metrics per component and even your own custom metrics.