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Dynatrace Introduces Domain Specific Agents, to Extend SRE, Development, and Security Teams with Trusted, Autonomous Action

Enabling teams to drive autonomous operations at scale, built on the trust of deterministic AI

At Perform, its flagship annual user conference, Dynatrace announced ready-to-use domain specific Agents to augment site reliability engineer (SRE), development, and security teams with autonomous action. 

Built on Dynatrace Intelligence – the industry’s first agentic operations system – these agents empower organizations to leverage real-time observability insights to drive fully autonomous outcomes with speed, precision, and governance.

As enterprises expand AI across software and business workflows, operations are becoming more dynamic and complex. Success requires the ability to detect unexpected changes and act with speed and confidence at scale. AI-powered observability helps teams identify, remediate, and prevent issues. Beyond reliability, it accelerates innovation and improves productivity and efficiency, enabling organizations to handle complexity faster and more cost-effectively.

A New Model for Agentic Operations

Dynatrace Intelligence Agents introduce an intuitive model for agentic operations. Customers can use a broad set of specialized agents that serve specific functions and work together, including:

  • Agents that deliver differentiated foundational capabilities for trusted operational context through causal reasoning, prediction, real-time intelligence, and oversight.
  • Domain agents coordinate end-to-end outcomes including SRE and DevOps issue prevention and remediation, business observability for real-time business optimization, and security operations to identify and resolve vulnerabilities.
  • Assist agents interpret situations and guide next best actions through natural language, helping customers onboard quickly and maximize value from Dynatrace across the organization.
  • Agentic workflows orchestrate complex goals with policy-driven controls and approvals, with flexibility for custom use cases.
  • Ecosystem agent integrations connect Dynatrace Intelligence with external systems to drive action across enterprise workflows, DevOps pipelines, and software ecosystems. This ensures teams get the full benefit of agents from key ecosystem partners.

An Agentic Workforce That Mobilizes Automatically

When activated by detected anomalies, or requests are received from users or partner agents, Dynatrace Intelligence automatically mobilize the right agents to assess context, determine urgency, and coordinate next steps. They execute actions directly through the tools teams already use to communicate, track work, and deliver fixes.

Elevated Outcomes Across Teams

Dynatrace Intelligence extends with domain specific agents to what teams can accomplish. They accelerate responses, improve consistency, and free teams for higher-value work. With these agents, teams can:

  • Compress time-to-resolution with coordinated triage, guided remediation, and automated response.
  • Improve customer experiences by optimizing engagement flow, identifying and resolving issues earlier, and preventing recurrence of issues.
  • Reduce operational toil by automating repeatable tasks across service management, reliability, and security operations.
  • Scale best practices by operationalizing expertise into repeatable workflows.
  • Increase confidence and control with policy-driven governance and explainable actions.

Extending Autonomous Operations Across the Partner Ecosystem

Dynatrace Intelligence Agents also collaborate with external platform agents and enterprise systems, enabling action across the full operational landscape without locking organizations into relying on a single vendor. For example, when a high-impact vulnerability appears, Dynatrace Intelligence Agents automatically assess exposure, correlate evidence across logs, traces, vulnerabilities, runtime behavior, and detections, and generate a prioritized response plan. Integrated systems help teams move from alert to action in minutes. For more information on common use cases, please visit the Dynatrace blog.

“The real ROI in Dynatrace Intelligent Agents comes from precision, not prompts. Deterministic AI, unlike LLMs, reduces costs, increases trust, and enables supervised autonomy that enterprises can actually scale. Add the work that Dynatrace has done to build process-oriented agents, such as the SRE, Developer, and Security Agents, and organizations should expect domain-silos to be broken down, leading to fewer cross-team escalations and faster release cycles with fewer production failures,” says Rob Strechay, Principal Analyst, TheCUBE research & Smuget Consulting.

“Organizations will see an explosion of AI agents in the coming year,” said Steve Tack, Chief Product Officer at Dynatrace, “The effectiveness of these initiatives depends on deterministic insight into how agents interact. By anchoring a trusted ecosystem of technology partners, such as AWS, Microsoft Azure, and Google Cloud, to intelligent automation platforms like ServiceNow, we’re helping customers shift from managing incidents to managing intelligence. Together, we’re creating a self-healing foundation that turns cloud complexity into a strategic advantage and enables enterprises to accelerate innovation, optimize performance, and achieve zero-outage outcomes.”

Dynatrace Intelligence Agents are available now, with more to follow.

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...

Dynatrace Introduces Domain Specific Agents, to Extend SRE, Development, and Security Teams with Trusted, Autonomous Action

Enabling teams to drive autonomous operations at scale, built on the trust of deterministic AI

At Perform, its flagship annual user conference, Dynatrace announced ready-to-use domain specific Agents to augment site reliability engineer (SRE), development, and security teams with autonomous action. 

Built on Dynatrace Intelligence – the industry’s first agentic operations system – these agents empower organizations to leverage real-time observability insights to drive fully autonomous outcomes with speed, precision, and governance.

As enterprises expand AI across software and business workflows, operations are becoming more dynamic and complex. Success requires the ability to detect unexpected changes and act with speed and confidence at scale. AI-powered observability helps teams identify, remediate, and prevent issues. Beyond reliability, it accelerates innovation and improves productivity and efficiency, enabling organizations to handle complexity faster and more cost-effectively.

A New Model for Agentic Operations

Dynatrace Intelligence Agents introduce an intuitive model for agentic operations. Customers can use a broad set of specialized agents that serve specific functions and work together, including:

  • Agents that deliver differentiated foundational capabilities for trusted operational context through causal reasoning, prediction, real-time intelligence, and oversight.
  • Domain agents coordinate end-to-end outcomes including SRE and DevOps issue prevention and remediation, business observability for real-time business optimization, and security operations to identify and resolve vulnerabilities.
  • Assist agents interpret situations and guide next best actions through natural language, helping customers onboard quickly and maximize value from Dynatrace across the organization.
  • Agentic workflows orchestrate complex goals with policy-driven controls and approvals, with flexibility for custom use cases.
  • Ecosystem agent integrations connect Dynatrace Intelligence with external systems to drive action across enterprise workflows, DevOps pipelines, and software ecosystems. This ensures teams get the full benefit of agents from key ecosystem partners.

An Agentic Workforce That Mobilizes Automatically

When activated by detected anomalies, or requests are received from users or partner agents, Dynatrace Intelligence automatically mobilize the right agents to assess context, determine urgency, and coordinate next steps. They execute actions directly through the tools teams already use to communicate, track work, and deliver fixes.

Elevated Outcomes Across Teams

Dynatrace Intelligence extends with domain specific agents to what teams can accomplish. They accelerate responses, improve consistency, and free teams for higher-value work. With these agents, teams can:

  • Compress time-to-resolution with coordinated triage, guided remediation, and automated response.
  • Improve customer experiences by optimizing engagement flow, identifying and resolving issues earlier, and preventing recurrence of issues.
  • Reduce operational toil by automating repeatable tasks across service management, reliability, and security operations.
  • Scale best practices by operationalizing expertise into repeatable workflows.
  • Increase confidence and control with policy-driven governance and explainable actions.

Extending Autonomous Operations Across the Partner Ecosystem

Dynatrace Intelligence Agents also collaborate with external platform agents and enterprise systems, enabling action across the full operational landscape without locking organizations into relying on a single vendor. For example, when a high-impact vulnerability appears, Dynatrace Intelligence Agents automatically assess exposure, correlate evidence across logs, traces, vulnerabilities, runtime behavior, and detections, and generate a prioritized response plan. Integrated systems help teams move from alert to action in minutes. For more information on common use cases, please visit the Dynatrace blog.

“The real ROI in Dynatrace Intelligent Agents comes from precision, not prompts. Deterministic AI, unlike LLMs, reduces costs, increases trust, and enables supervised autonomy that enterprises can actually scale. Add the work that Dynatrace has done to build process-oriented agents, such as the SRE, Developer, and Security Agents, and organizations should expect domain-silos to be broken down, leading to fewer cross-team escalations and faster release cycles with fewer production failures,” says Rob Strechay, Principal Analyst, TheCUBE research & Smuget Consulting.

“Organizations will see an explosion of AI agents in the coming year,” said Steve Tack, Chief Product Officer at Dynatrace, “The effectiveness of these initiatives depends on deterministic insight into how agents interact. By anchoring a trusted ecosystem of technology partners, such as AWS, Microsoft Azure, and Google Cloud, to intelligent automation platforms like ServiceNow, we’re helping customers shift from managing incidents to managing intelligence. Together, we’re creating a self-healing foundation that turns cloud complexity into a strategic advantage and enables enterprises to accelerate innovation, optimize performance, and achieve zero-outage outcomes.”

Dynatrace Intelligence Agents are available now, with more to follow.

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...