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Dynatrace Perform 2026 Ignites a New Era of Autonomous Intelligence and Innovation

Event highlights advancements across the Dynatrace platform, and visionary organizations driving transformation through intelligent observability and agentic AI

At Perform, its flagship annual user conference, Dynatrace announced a series of differentiated product enhancements and showcased the notable achievements of customers.

Dynatrace CEO Rick McConnell, CTO Bernd Greifeneder, and Dynatrace product leaders will assemble in a leadership keynote at 9:00 a.m. PT on Wednesday, January 28 to explore these platform innovations and discuss how enterprises can harness data to advance critical AI initiatives and operate with greater speed and confidence. To register to tune in virtually, visit the registration page.

Innovation announcements launched during Perform include:

Dynatrace debuts Dynatrace Intelligence

Fusing deterministic and agentic AI for reliable outcomes, Dynatrace Intelligence represents the next phase in the evolution of the Dynatrace platform.

Dynatrace Intelligence combines deterministic intelligence grounded in real-time causal context, with agentic AI that can safely reason, decide, and act within defined guardrails. Data is stored and unified in Grail™, and continuously and automatically enriched by Smartscape’s causal topology, fuelling deterministic AI to produce trustworthy, explainable insights.

Dynatrace Intelligence Agents turn action into insight

Built on the industry’s first agentic operations system, Dynatrace Intelligence, Dynatrace Intelligence Agents transform answers to outcomes by taking action across workflows with speed, precision, and governance. These agents have been designed to drive closed-loop autonomous outcomes across IT and business operations.

Dynatrace Intelligence Agents introduce an intuitive model for agentic operations, with customers able to use specialized agents that work together across responsibilities and domains.

Expanded cloud operations capabilities unveiled

New cloud-native integrations from Dynatrace, will give enterprises a clearer, unified view across multi-cloud environments thanks to expanded cloud-native integrations across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

The capabilities will bring visibility into one place, helping teams find and fix issues faster and reduce disruption for end users. Powered by the uniqueness of Grail™, an industry-leading data lakehouse, Smartscape real-time dependency graph, and Dynatrace Intelligence, this combination will apply AI to help organizations understand, automate, and operate through this growing complexity.

Enhanced developer experiences launched

Dynatrace also unveiled new capabilities to transform observability into an active system of control for cloud and AI-native software delivery. With these enhancements, enterprises can evolve observability into a dynamic driver of developer productivity, moving beyond insight alone to an intelligent system that actively guides, optimizes, and protects software delivery in real time.

The innovations announced unify frontend, backend, AI telemetry, database, cloud, and mobile into a single developer-facing experience built on Grail™, Smartscape, and Dynatrace Intelligence. This production-first, AI-native foundation – built for agentic and LLM-driven applications – enables both humans and AI agents to reason about live system behavior, safely experiment in production, and take immediate, targeted action when risk is detected, without redeployments or manual intervention.

Cross-industry Customer Success Spotlighted

Dynatrace spotlighted customers showcasing how they are fuelling business growth with Dynatrace AI Observability.

With the Dynatrace platform as the control plane for AI in production, enterprises have the visibility and governance they need as they adopt agentic AI at scale. This evolution is helping customers manage complexity, ensure compliance, and optimize performance across emerging technologies, with various use cases explored that included Canadian telecoms giant, TELUS.

Advanced Real User Monitoring availability

Dynatrace also announced the launch of next-generation Real User Monitoring (RUM) capabilities, combining front-end telemetry with back-end context, to empower teams to better understand and optimize user experience.

As organizations move toward dynamic, cloud-native ecosystems and build AI-driven applications powered by large language models (LLMs) and other advanced AI services, traditional RUM tools are hitting limitations. Powered by Grail™, Smartscape, and advanced AI, users of Dynatrace can now analyze frontend data alongside logs, metrics, traces, and business events, all within a single platform, enabling precise, end-to-end visibility, faster troubleshooting, and smarter decision-making.

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Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

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For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

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AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...

Dynatrace Perform 2026 Ignites a New Era of Autonomous Intelligence and Innovation

Event highlights advancements across the Dynatrace platform, and visionary organizations driving transformation through intelligent observability and agentic AI

At Perform, its flagship annual user conference, Dynatrace announced a series of differentiated product enhancements and showcased the notable achievements of customers.

Dynatrace CEO Rick McConnell, CTO Bernd Greifeneder, and Dynatrace product leaders will assemble in a leadership keynote at 9:00 a.m. PT on Wednesday, January 28 to explore these platform innovations and discuss how enterprises can harness data to advance critical AI initiatives and operate with greater speed and confidence. To register to tune in virtually, visit the registration page.

Innovation announcements launched during Perform include:

Dynatrace debuts Dynatrace Intelligence

Fusing deterministic and agentic AI for reliable outcomes, Dynatrace Intelligence represents the next phase in the evolution of the Dynatrace platform.

Dynatrace Intelligence combines deterministic intelligence grounded in real-time causal context, with agentic AI that can safely reason, decide, and act within defined guardrails. Data is stored and unified in Grail™, and continuously and automatically enriched by Smartscape’s causal topology, fuelling deterministic AI to produce trustworthy, explainable insights.

Dynatrace Intelligence Agents turn action into insight

Built on the industry’s first agentic operations system, Dynatrace Intelligence, Dynatrace Intelligence Agents transform answers to outcomes by taking action across workflows with speed, precision, and governance. These agents have been designed to drive closed-loop autonomous outcomes across IT and business operations.

Dynatrace Intelligence Agents introduce an intuitive model for agentic operations, with customers able to use specialized agents that work together across responsibilities and domains.

Expanded cloud operations capabilities unveiled

New cloud-native integrations from Dynatrace, will give enterprises a clearer, unified view across multi-cloud environments thanks to expanded cloud-native integrations across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

The capabilities will bring visibility into one place, helping teams find and fix issues faster and reduce disruption for end users. Powered by the uniqueness of Grail™, an industry-leading data lakehouse, Smartscape real-time dependency graph, and Dynatrace Intelligence, this combination will apply AI to help organizations understand, automate, and operate through this growing complexity.

Enhanced developer experiences launched

Dynatrace also unveiled new capabilities to transform observability into an active system of control for cloud and AI-native software delivery. With these enhancements, enterprises can evolve observability into a dynamic driver of developer productivity, moving beyond insight alone to an intelligent system that actively guides, optimizes, and protects software delivery in real time.

The innovations announced unify frontend, backend, AI telemetry, database, cloud, and mobile into a single developer-facing experience built on Grail™, Smartscape, and Dynatrace Intelligence. This production-first, AI-native foundation – built for agentic and LLM-driven applications – enables both humans and AI agents to reason about live system behavior, safely experiment in production, and take immediate, targeted action when risk is detected, without redeployments or manual intervention.

Cross-industry Customer Success Spotlighted

Dynatrace spotlighted customers showcasing how they are fuelling business growth with Dynatrace AI Observability.

With the Dynatrace platform as the control plane for AI in production, enterprises have the visibility and governance they need as they adopt agentic AI at scale. This evolution is helping customers manage complexity, ensure compliance, and optimize performance across emerging technologies, with various use cases explored that included Canadian telecoms giant, TELUS.

Advanced Real User Monitoring availability

Dynatrace also announced the launch of next-generation Real User Monitoring (RUM) capabilities, combining front-end telemetry with back-end context, to empower teams to better understand and optimize user experience.

As organizations move toward dynamic, cloud-native ecosystems and build AI-driven applications powered by large language models (LLMs) and other advanced AI services, traditional RUM tools are hitting limitations. Powered by Grail™, Smartscape, and advanced AI, users of Dynatrace can now analyze frontend data alongside logs, metrics, traces, and business events, all within a single platform, enabling precise, end-to-end visibility, faster troubleshooting, and smarter decision-making.

The Latest

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

For years, infrastructure teams have treated compute as a relatively stable input. Capacity was provisioned, costs were forecasted, and performance expectations were set based on the assumption that identical resources behaved identically. That mental model is starting to break down. AI infrastructure is no longer behaving like static cloud capacity. It is increasingly behaving like a market ...

Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...

Mobile users are less tolerant of app instability than ever before. According to a new report from Luciq, No Margin for Error: What Mobile Users Expect and What Mobile Leaders Must Deliver in 2026, even minor performance issues now result in immediate abandonment, lost purchases, and long-term brand impact ...

Artificial intelligence (AI) has become the dominant force shaping enterprise data strategies. Boards expect progress. Executives expect returns. And data leaders are under pressure to prove that their organizations are "AI-ready" ...

Agentic AI is a major buzzword for 2026. Many tech companies are making bold promises about this technology, but many aren't grounded in reality, at least not yet. This coming year will likely be shaped by reality checks for IT teams, and progress will only come from a focus on strong foundations and disciplined execution ...

AI systems are still prone to hallucinations and misjudgments ... To build the trust needed for adoption, AI must be paired with human-in-the-loop (HITL) oversight, or checkpoints where humans verify, guide, and decide what actions are taken. The balance between autonomy and accountability is what will allow AI to deliver on its promise without sacrificing human trust ...

More data center leaders are reducing their reliance on utility grids by investing in onsite power for rapidly scaling data centers, according to the Data Center Power Report from Bloom Energy ...