Dynatrace Notebooks facilitate exploratory data analysis by enabling users to visually collaborate and leverage insights from various team inputs, which can then inform automated actions through anomaly detection. The Dynatrace Grail™ data lakehouse allows for the integration and querying of diverse data sources using the Dynatrace Query Language (DQL), enhancing the ability to identify anomalies. Davis AI offers automated anomaly detection with three specific analyzers—static threshold, auto-adaptive threshold, and seasonal baseline—empowering businesses to customize detection according to their needs. The Davis AI Analyzer can perform anomaly detection across any time series, regardless of its origin, and integrates seamlessly with Notebooks for creating anomaly detectors. With the release of Dynatrace version 1.291, Davis Anomaly Detection is automatically enabled for all Dynatrace SaaS environments, and users are encouraged to explore its capabilities through the Dynatrace Playground and share feedback to enhance its functionalities.