Dynatrace taps hypermodal AI for faster application observability

Massachusetts-headquartered Dynatrace, which provides an observability layer to monitor and optimize application development, performance and security, today announced the expansion of its Davis AI engine with new generative AI capabilities. 

The move, Dynatrace says, transforms Davis into the industry’s first hypermodal AI, converging its unique approach to causal AI and predictive intelligence capabilities with generative AI. Davis will now provide enterprises with personalized recommendations based on their unique cloud data, speeding up some work and enabling people to focus on higher-value activities for faster application innovation.

“With the release of the expanded Davis AI, we address … [and] redefine how observability and security solutions work. We expect Davis will enable our customers to achieve 10-20% productivity improvements year-over-year as they drive transformation initiatives related to observability and security,” Bernd Greifeneder, CTO at Dynatrace, said in a statement.

Dynatrace Davis AI for observability

Modern enterprise applications, and the environments they run in, are becoming increasingly complex. Thousands of services, millions of lines of code and trillions of dependencies are active at the same time. With Davis AI sitting at the heart of the Dynatrace platform, enterprises can monitor and keep these complex ecosystems up and running.

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Since its early days, Davis has been using causal AI to analyze observability and security data within the Dynatrace Grail data lakehouse and dependencies mapped by Dynatrace Smartscape topology, to deliver context-rich anomaly detection and automation necessary for issue prevention, remediation and root-cause analysis. The engine also uses predictive intelligence to anticipate future behavior based on past data and observed patterns, allowing teams to address potential application issues that may surface down the line.

The new Davis Copilot 

With the latest move, Dynatrace is adding Davis Copilot to the AI party. The offering works in conjunction with Davis AI’s existing causal and predictive AI capabilities to automatically provide users with recommendations on how to solve specific issues in the context of their environment and situation. 

But Davis Copilot does not use external data to work. Instead, the generative AI recommendations are fueled by precise anomaly context from causal and predictive AI that reflect unique attributes of each organization’s hybrid and multi-cloud ecosystem. This approach ensures highly relevant results and helps boost productivity across business, development, security and operations teams. 

As Greifeneder noted, generative AI is a transformative technology in itself, but combining it with additional AI techniques like causal and predictive AI in this way paves the way to make the most of it.

“This is because only causal AI can deterministically know the root cause of an issue; only predictive AI can see into the future reliably; and only generative AI can tailor recommendations and solutions to specific problems using advanced probabilistic algorithms,” he said.

Once the recommendations are generated, Davis Copilot also creates suggested automation workflows and dashboards to help users quickly address the issue at hand. In addition, users get the option to use the Copilot directly in natural language to explore, solve or complete specific tasks.

Currently, Davis AI continues to be a part of the main Dynatrace platform, but the new Copilot bit of the engine remains out of reach. The company says it will make the expanded offering available sometime later this year.