Introduction to Anomaly Detection based on DQL

#Dynatrace Davis AI has been solving the challenge of anomaly detection on high cardinal data for many years and with that, reduces alert noise and avoids alert fatigue. As announced at #Perform2024, Dynatrace brings the Davis AI Analyzer into Notebooks, Dashboards, and Workflows to leverage anomaly detection on ANY data that can be queried through DQL (Dynatrace Query Language).
To get a preview of the new extended capabilities, we have David Bruendl, Product Manager at Dynatrace, walking us through a full end-2-end scenario of leveraging the Davis AI Analyzer and configuring custom anomaly detection events.We will follow up with more use case-specific sessions in the coming weeks, but please make yourself familiar with the core capabilities.
Additional Links Discussed:
Dynatrace Anomaly detection doc: dynatr.ac/49MwaXz
Dynatrace SaaS Trial: bit.ly/dtsaastrial
Dynatrace Playground: dt-url.net/discover
Chapter List:
00:00 - Introduction
02:23 - What you'll learn today
03:27 - The Scale of Cloud Observability
03:56 - The Challenge of anomaly detection in high cardinal data
05:50 - Reduce alert noise and avoid alert fatigue
09:49 - Davis AI supports you in every context
10:30 - Live Demo
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[@bleuf6]

This is a game changer as it leverages the Grail latent power

[@sahilwaghmare9758]

Dammnnn....looking forward for this feature :)

[@rbeg-sounddesign]

Good but we need now to create a problem when Davis AI detects an alert, like seasonal metric events did ...

[@denisl.598]

Can we say good bye to the THROTTLED Metric Event configs with this new feature?

[@grabnerandi]

yeah. this is a new approach to anomaly detection using all data in Grail and our davis AI capabilities in Notebooks, Dashboards and Workflows. Whats your use case though so we can help you better