Dynatrace has announced enhancements to its error workflow and the Davis AI system, which now automatically detects and reports client-side HTTP and custom errors, providing out-of-the-box solutions to improve observability of customers' digital experiences. This update extends the Davis AI causation engine's awareness, offering comprehensive visibility into real user actions and application behavior, which aids in reducing Mean Time To Identify (MTTI) errors. The new feature allows users to automatically baseline errors and receive alerts for anomalies, eliminating the need for manual error configuration and alert setup. The system provides an in-depth analysis of error-related problems and includes tools for fine-tuning alert settings to align with specific application needs. Users can enable this extended awareness across all applications via a simple interface, which integrates error types into a unified error column for efficient monitoring and alerting. Dynatrace is also working on further updates to enhance Davis's error analysis and alerting capabilities, and they invite user feedback through their community platform.