Transform log data into actionable metrics and have Davis AI do the work for you

Dynatrace enhances its log monitoring capabilities by transforming numerical log attributes into metrics for AI-driven problem detection and root cause analysis, which aids DevOps teams in minimizing alert noise and reducing mean time to recovery (MTTR) during incidents. The platform now supports log data from various sources, including Kubernetes, multicloud platforms like AWS, GCP, and Azure, and open-source log frameworks, allowing for the automation of anomaly detection and analysis through its AI engine, Davis. By turning log data into metrics, Dynatrace enables comprehensive monitoring of system performance and business metrics, breaking down data silos and providing insights into real-user behavior and infrastructure performance. The platform’s automation features, such as automated thresholding and multidimensional baselining, eliminate the need for manual monitoring and adjustments, offering a scalable solution for modern enterprises. Users can start with a free trial to explore these capabilities, utilizing the log ingestion API and custom metric creation to integrate meaningful insights into their workflows.

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