Dynatrace has announced a new generation of its observability platform. With this third iteration, the company aims to further integrate observability, security, and business analytics. AI and automation play a central role in this.
The platform is designed to translate large amounts of data from modern IT environments, such as cloud-native architectures and AI-driven applications, into business decisions and actions more quickly.
At the heart of the revamped platform is Grail, a data lakehouse that brings together different types of data in a scalable architecture. This enables companies to analyze and apply telemetry more efficiently within the organization. The expansion of AI capabilities enables teams to convert data into insights in real time. These insights are then automatically translated into concrete steps.
According to founder and CTO Bernd Greifeneder (photo), the platform aims to convert observability data into directly usable knowledge for AI. This should enable autonomous intelligence. Dynatrace is thus positioning its offering not only as an analysis tool, but as a foundation for automated decision-making in complex IT environments.
The new features include tools for developers to work more easily with serverless and cloud architectures. The introduction of a scalable live debugger without classic breakpoints should help them solve problems faster while maintaining privacy. Integration between observability data and development environments is also possible via the Dynatrace MCP server.
Automated analyses
Another key feature is the application of Agentic AI in the platform. This technology enables proactive response to operational issues. Automated analytics and natural language interfaces allow teams to get to the root cause of disruptions faster and implement solutions with minimal manual intervention.
In the area of log management, Dynatrace introduces direct log analysis within the broader context of observability data. New features in the Logs app and via Davis CoPilot should make it easier to extract valuable insights from large amounts of log data. Support for hot/hot storage with long-term retention and scalable log collection is designed to enable efficient management even in demanding cloud environments.
Also read: Dynatrace-CTO: “Shift left is a disaster for enterprises”