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Dynatrace Adds Agentic AI Capabilities

Dynatrace is extending the Dynatrace platform with agentic AI capabilities. 

Designed to predict and prevent disruptions, protect systems and data, and optimize operations autonomously, these advancements mark a new era of productivity and agility, fundamentally redefining how businesses manage digital transformation.

Dynatrace leverages agentic AI to enabling enterprises to transition from manual oversight to autonomous, AI-driven workflows that streamline operations and foster innovation.

“We anticipated the growing complexity of digital systems outpacing the capabilities of traditional observability solutions reliant on human intervention,” said Bernd Greifeneder, Founder and CTO, Dynatrace. “This is why we built the next generation of our platform to help customers leverage advanced AI to offload work and unlock entirely new possibilities. By unifying observability, security, and business data in a revolutionary data lakehouse architecture, we’ve created the foundation for AI to deliver real-time insights and act autonomously in ways that were unimaginable a few years ago.”

The core of Dynatrace is a purpose-built foundation for agentic AI, seamlessly unifying observability, security, and business data in a schema-free, indexless data lakehouse. This foundation empowers intelligent decision-making and autonomous action, enabling enterprises to transition from human oversight to intelligent, self-operating systems. Together, the platform serves as the knowledge, reasoning, planning, and actioning framework of agentic AI, delivering trustworthy precision and adaptability.

  • Grail, an indexless, schema-free data lakehouse, hot/hot by design, provides real-time access to petabytes of data in context, eliminating the inefficiencies of re-indexing and rehydration, to address the complexity and scale of agentic AI systems.
  • Smartscape, a dynamic, real-time topology discovery, maps causal dependencies across complex digital ecosystems, enhancing the platform’s ability to deliver precise insights and automation, fueling Dynatrace AI for fact-based reasoning.
  • Davis AI combines causal, predictive, and generative AI techniques to analyze unified data, deliver trustworthy insights, and intelligently plan actions to minimize hallucinations, maximize precision in insights and answers, and adhere to responsible AI practices and compliance requirements.
  • AutomationEngine executes autonomous tasks and integrates seamlessly with first-party and third-party AI agents, driving differentiated efficiency and adaptability, all in a safe and privacy-protected manner for controlled agentic AI actions.

Through sustained innovation, Dynatrace provides the intelligence and autonomy developers, business leaders, and organizations need to tackle digital complexity and achieve extraordinary outcomes.

“These innovations provide the transparency, automation, and agility enterprises need to stay ahead in a rapidly evolving technology landscape,” Greifeneder added. “The result is a platform capable of autonomously preventing potential issues, optimizing resource use, and adapting to unforeseen challenges. Agentic AI represents a fundamental transformation in enterprise technology. Our platform not only delivers insights but actively enables businesses to anticipate challenges, adapt to changing conditions, and achieve their boldest ambitions. This evolution embodies our long-standing vision to empower organizations through trustworthy automation and actionable intelligence.”

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Dynatrace Adds Agentic AI Capabilities

Dynatrace is extending the Dynatrace platform with agentic AI capabilities. 

Designed to predict and prevent disruptions, protect systems and data, and optimize operations autonomously, these advancements mark a new era of productivity and agility, fundamentally redefining how businesses manage digital transformation.

Dynatrace leverages agentic AI to enabling enterprises to transition from manual oversight to autonomous, AI-driven workflows that streamline operations and foster innovation.

“We anticipated the growing complexity of digital systems outpacing the capabilities of traditional observability solutions reliant on human intervention,” said Bernd Greifeneder, Founder and CTO, Dynatrace. “This is why we built the next generation of our platform to help customers leverage advanced AI to offload work and unlock entirely new possibilities. By unifying observability, security, and business data in a revolutionary data lakehouse architecture, we’ve created the foundation for AI to deliver real-time insights and act autonomously in ways that were unimaginable a few years ago.”

The core of Dynatrace is a purpose-built foundation for agentic AI, seamlessly unifying observability, security, and business data in a schema-free, indexless data lakehouse. This foundation empowers intelligent decision-making and autonomous action, enabling enterprises to transition from human oversight to intelligent, self-operating systems. Together, the platform serves as the knowledge, reasoning, planning, and actioning framework of agentic AI, delivering trustworthy precision and adaptability.

  • Grail, an indexless, schema-free data lakehouse, hot/hot by design, provides real-time access to petabytes of data in context, eliminating the inefficiencies of re-indexing and rehydration, to address the complexity and scale of agentic AI systems.
  • Smartscape, a dynamic, real-time topology discovery, maps causal dependencies across complex digital ecosystems, enhancing the platform’s ability to deliver precise insights and automation, fueling Dynatrace AI for fact-based reasoning.
  • Davis AI combines causal, predictive, and generative AI techniques to analyze unified data, deliver trustworthy insights, and intelligently plan actions to minimize hallucinations, maximize precision in insights and answers, and adhere to responsible AI practices and compliance requirements.
  • AutomationEngine executes autonomous tasks and integrates seamlessly with first-party and third-party AI agents, driving differentiated efficiency and adaptability, all in a safe and privacy-protected manner for controlled agentic AI actions.

Through sustained innovation, Dynatrace provides the intelligence and autonomy developers, business leaders, and organizations need to tackle digital complexity and achieve extraordinary outcomes.

“These innovations provide the transparency, automation, and agility enterprises need to stay ahead in a rapidly evolving technology landscape,” Greifeneder added. “The result is a platform capable of autonomously preventing potential issues, optimizing resource use, and adapting to unforeseen challenges. Agentic AI represents a fundamental transformation in enterprise technology. Our platform not only delivers insights but actively enables businesses to anticipate challenges, adapt to changing conditions, and achieve their boldest ambitions. This evolution embodies our long-standing vision to empower organizations through trustworthy automation and actionable intelligence.”

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The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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