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Dynatrace Intelligence Redefines Observability with Trusted Agentic Automation

First-of-its-kind system fusing deterministic and agentic AI to power safe, autonomous operations

At Perform, its flagship annual user conference, Dynatrace unveiled Dynatrace Intelligence, a new agentic operations system that fuses deterministic and agentic AI. 

This differentiated combination delivers reliable, agentic AI-powered observability to customers. Built to observe and optimize dynamic AI workloads, Dynatrace Intelligence empowers organizations to build more resilient applications, elevate customer experiences, and drive autonomous action across modern digital ecosystems.

Dynatrace Intelligence represents the next phase in the evolution of the Dynatrace platform, helping the world’s largest enterprises move from reactive to preventive and advances them toward autonomous operations while ensuring teams remain firmly in control.

Why Dynatrace Intelligence Matters

Organizations are confronting rising complexity as they continue to adopt new technologies. For example, global AI investment is expected to reach nearly $2 trillion in 2026 and organizations are under increasing pressure to show meaningful progress. Yet many struggle with the unpredictable and dynamic nature of AI and agentic systems. Teams must quickly identify unexpected behaviors, understand downstream impact, and deploy fixes before customer experience or business performance suffers.

Dynatrace Intelligence addresses these challenges with deep, real-time visibility into system behavior and performance across cloud and AI-native environments, creating a real-time digital twin. It removes guesswork by fusing the precise deterministic AI insights with reasoning from coordinated AI agents that drive self-healing systems. The result is reliable autonomous action, reduced operational burden, and more time for strategic decision-making.

The Dynatrace Difference: Fusing Deterministic with Agentic AI

Dynatrace Intelligence uniquely combines deterministic AI, grounded in real-time causal context, and agentic AI, capable of safe reasoning, decision-making, and action within defined guardrails.

This system is powered by the Dynatrace 3rd generation platform, including:

  • Grail, an industry leading, unified data lakehouse that stores metrics, logs, traces, events, user sessions, and business and security data with precise, contextual integrity.
  • Smartscape, the real-time dependency graph that continuously and automatically maps relationships and fuels trustworthy, causal insights.

By anchoring agents in environment-specific facts, Dynatrace Intelligence provides a safer, faster, more reliable foundation for autonomous operations.  When Dynatrace benchmarked an external SRE agent working together with its deterministic agents, problems were solved up to 12 times more often, three times faster, and at half the cost compared to tests that did not use deterministic agents.

An Ecosystem of AI Agents

Enterprises can orchestrate built‑in and partner agents, with bidirectional integrations across the broader ecosystem, including ServiceNow, AWS, Microsoft Azure, Google Cloud, Atlassian, GitHub, Red Hat, and more.

The agentic architecture includes:

  • Agents that deliver foundational capabilities for trusted operational context through causal reasoning, prediction, and real-time intelligence, and oversight.
  • Agents that expand teams by providing insight and guidance to targeted functional areas and personas.
  • Ecosystem agents that connect with partner platforms expanding the scope of autonomous action across complex environments.

Advancing Autonomous Operations

With Dynatrace Intelligence, organizations can achieve:

  • Self-healing systems in dynamic, AI-driven environments
  • Proactive prevention, remediation, and optimization
  • Reliable autonomous action, leveraging both built-in agents and collaboration with partner agents, with full visibility and control

Teams remain in command while the system continuously manages operational complexity in the background.

The Journey to Autonomous Operations

Dynatrace Intelligence supports customers on a phased journey toward autonomy. Organizations can start by using AI-driven insights and recommendations, progress to leverage automation for supervised operations with human oversight, and ultimately advance to fully autonomous operations with guardrails and controls. This approach allows customers to safely adopt auto-prevention, auto-remediation, and auto-optimization, while maintaining control and building trust at every step.

“Agentic AI offers enormous potential, but many businesses still struggle to ensure it operates reliably, securely, and with consistent performance in real‑world environments,” said Bernd Greifeneder, Chief Technology Officer and Founder at Dynatrace. “Dynatrace Intelligence fuses deterministic and agentic AI, removing the guesswork and delivering AI‑powered observability organizations can trust.”

“As our digital environment grows more complex, we’re looking to move beyond reactive operations and manual intervention,” said Alexander Bicalho, Senior Director of Engineering at Autodesk. “What Dynatrace is outlining with Dynatrace Intelligence aligns with where we want to go—using trusted data and insights to support more autonomous operations. An approach that connects insight to action, while keeping our teams in control, could significantly improve performance and reliability as we scale. It’s observability that doesn’t just detect problems—it understands them and acts on them reliably.”

“The evolution of observability platforms is moving from manual root cause analysis to preventive operations. Organizations are progressing beyond reactive monitoring toward autonomous operations models that combine deterministic AI with agentic AI systems, with AI agents operating at different autonomy levels to orchestrate workflows across integrated ecosystems that span cloud platforms, development tools, and IT service management systems,” said Stephen Elliot, Group Vice President at IDC.

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Dynatrace Intelligence Redefines Observability with Trusted Agentic Automation

First-of-its-kind system fusing deterministic and agentic AI to power safe, autonomous operations

At Perform, its flagship annual user conference, Dynatrace unveiled Dynatrace Intelligence, a new agentic operations system that fuses deterministic and agentic AI. 

This differentiated combination delivers reliable, agentic AI-powered observability to customers. Built to observe and optimize dynamic AI workloads, Dynatrace Intelligence empowers organizations to build more resilient applications, elevate customer experiences, and drive autonomous action across modern digital ecosystems.

Dynatrace Intelligence represents the next phase in the evolution of the Dynatrace platform, helping the world’s largest enterprises move from reactive to preventive and advances them toward autonomous operations while ensuring teams remain firmly in control.

Why Dynatrace Intelligence Matters

Organizations are confronting rising complexity as they continue to adopt new technologies. For example, global AI investment is expected to reach nearly $2 trillion in 2026 and organizations are under increasing pressure to show meaningful progress. Yet many struggle with the unpredictable and dynamic nature of AI and agentic systems. Teams must quickly identify unexpected behaviors, understand downstream impact, and deploy fixes before customer experience or business performance suffers.

Dynatrace Intelligence addresses these challenges with deep, real-time visibility into system behavior and performance across cloud and AI-native environments, creating a real-time digital twin. It removes guesswork by fusing the precise deterministic AI insights with reasoning from coordinated AI agents that drive self-healing systems. The result is reliable autonomous action, reduced operational burden, and more time for strategic decision-making.

The Dynatrace Difference: Fusing Deterministic with Agentic AI

Dynatrace Intelligence uniquely combines deterministic AI, grounded in real-time causal context, and agentic AI, capable of safe reasoning, decision-making, and action within defined guardrails.

This system is powered by the Dynatrace 3rd generation platform, including:

  • Grail, an industry leading, unified data lakehouse that stores metrics, logs, traces, events, user sessions, and business and security data with precise, contextual integrity.
  • Smartscape, the real-time dependency graph that continuously and automatically maps relationships and fuels trustworthy, causal insights.

By anchoring agents in environment-specific facts, Dynatrace Intelligence provides a safer, faster, more reliable foundation for autonomous operations.  When Dynatrace benchmarked an external SRE agent working together with its deterministic agents, problems were solved up to 12 times more often, three times faster, and at half the cost compared to tests that did not use deterministic agents.

An Ecosystem of AI Agents

Enterprises can orchestrate built‑in and partner agents, with bidirectional integrations across the broader ecosystem, including ServiceNow, AWS, Microsoft Azure, Google Cloud, Atlassian, GitHub, Red Hat, and more.

The agentic architecture includes:

  • Agents that deliver foundational capabilities for trusted operational context through causal reasoning, prediction, and real-time intelligence, and oversight.
  • Agents that expand teams by providing insight and guidance to targeted functional areas and personas.
  • Ecosystem agents that connect with partner platforms expanding the scope of autonomous action across complex environments.

Advancing Autonomous Operations

With Dynatrace Intelligence, organizations can achieve:

  • Self-healing systems in dynamic, AI-driven environments
  • Proactive prevention, remediation, and optimization
  • Reliable autonomous action, leveraging both built-in agents and collaboration with partner agents, with full visibility and control

Teams remain in command while the system continuously manages operational complexity in the background.

The Journey to Autonomous Operations

Dynatrace Intelligence supports customers on a phased journey toward autonomy. Organizations can start by using AI-driven insights and recommendations, progress to leverage automation for supervised operations with human oversight, and ultimately advance to fully autonomous operations with guardrails and controls. This approach allows customers to safely adopt auto-prevention, auto-remediation, and auto-optimization, while maintaining control and building trust at every step.

“Agentic AI offers enormous potential, but many businesses still struggle to ensure it operates reliably, securely, and with consistent performance in real‑world environments,” said Bernd Greifeneder, Chief Technology Officer and Founder at Dynatrace. “Dynatrace Intelligence fuses deterministic and agentic AI, removing the guesswork and delivering AI‑powered observability organizations can trust.”

“As our digital environment grows more complex, we’re looking to move beyond reactive operations and manual intervention,” said Alexander Bicalho, Senior Director of Engineering at Autodesk. “What Dynatrace is outlining with Dynatrace Intelligence aligns with where we want to go—using trusted data and insights to support more autonomous operations. An approach that connects insight to action, while keeping our teams in control, could significantly improve performance and reliability as we scale. It’s observability that doesn’t just detect problems—it understands them and acts on them reliably.”

“The evolution of observability platforms is moving from manual root cause analysis to preventive operations. Organizations are progressing beyond reactive monitoring toward autonomous operations models that combine deterministic AI with agentic AI systems, with AI agents operating at different autonomy levels to orchestrate workflows across integrated ecosystems that span cloud platforms, development tools, and IT service management systems,” said Stephen Elliot, Group Vice President at IDC.

The Latest

Outages aren't new. What's new is how quickly they spread across systems, vendors, regions and customer workflows. The moment that performance degrades, expectations escalate fast. In today's always-on environment, an outage isn't just a technical event. It's a trust event ...

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...