At its flagship annual user conference, Perform, Dynatrace announced a series of product enhancements to its AI-powered observability platform, alongside examples of customer adoption. The updates focus on applying AI to automation, governance, and operations across IT and business environments.
Perform opened with presentations from Dynatrace’s leadership team, outlining several platform updates.
Dynatrace Intelligence
Dynatrace introduced Dynatrace Intelligence, which combines deterministic intelligence based on real-time causal context with agentic AI designed to reason and act within defined guardrails. Data is stored and unified in Grail and enriched through Smartscape’s causal topology to support deterministic AI and produce explainable insights.
The platform also includes Dynatrace Intelligence Agents, which are designed to take action across workflows and support closed-loop operations across IT and business processes.
Expanded cloud operations
Dynatrace expanded its cloud operations capabilities with additional cloud-native integrations across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). The updates aim to provide a unified view across multi-cloud environments so teams can identify and resolve issues more quickly and reduce disruption for end users.
These capabilities are supported by Grail, Smartscape’s real-time dependency graph, and Dynatrace Intelligence to help organisations manage complexity across cloud environments.
Developer experience enhancements
New developer-focused capabilities were also announced to evolve observability into a more active system for cloud- and AI-native software delivery. The enhancements unify frontend, backend, AI telemetry, database, cloud, and mobile data into a single developer experience built on Grail, Smartscape, and Dynatrace Intelligence.
The updates are intended to allow teams and AI agents to analyse live system behaviour, experiment in production environments, and take targeted action when risks are detected without redeployments.
Customer examples
Dynatrace highlighted customer use cases showing how the platform is used to support AI initiatives in production environments. Examples included TELUS, which demonstrated how it applies Dynatrace for visibility, governance, and performance management as AI workloads scale.
Next-generation real user monitoring
Dynatrace also announced new Real User Monitoring (RUM) capabilities that combine front-end telemetry with back-end context. Powered by Grail, Smartscape, and AI, the updated RUM allows organisations to analyse frontend data alongside logs, metrics, traces, and business events within a single platform to support troubleshooting and user experience analysis for cloud-native and AI-driven applications.
Overall, the announcements at Perform reflect Dynatrace’s focus on applying AI and automation to observability, cloud operations, developer workflows, and user experience monitoring as enterprises adopt more complex, AI-driven systems.
