Dynatrace has launched Dynatrace Intelligence, an “agentic operations system” that combines deterministic AI with agentic AI, alongside a set of domain-specific automation agents aimed at site reliability, development and security teams.
The company introduced the products at its Perform user conference in Las Vegas. Dynatrace positioned the announcements as a shift towards more automated operations for organisations running complex cloud and AI-native workloads.
Product detail
Dynatrace Intelligence sits within the Dynatrace platform and uses two AI approaches. Dynatrace described deterministic AI as grounded in a real-time causal context. It outlined agentic AI as a set of coordinated agents that can reason, make decisions and take action within defined guardrails.
The company said the system targets environments where teams need to identify unexpected behaviours, assess downstream impact and deploy fixes quickly. Dynatrace also said customers face rising complexity as they adopt AI and other technologies, and they face pressure to show progress on AI initiatives.
Dynatrace stated that Dynatrace Intelligence builds a “real-time digital twin” from observability data across cloud and AI-native environments. It also uses its existing Grail data layer and Smartscape dependency mapping technology as part of the system.
Dynatrace said it benchmarked an external SRE agent working together with its deterministic agents. It said 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.
Partner ecosystem
Dynatrace said customers can orchestrate built-in and partner agents, with bidirectional integrations across third-party services. It named ServiceNow, AWS, Microsoft Azure, Google Cloud, Atlassian, GitHub and Red Hat among the integrations.
The company said its architecture includes agents that provide operational context, prediction and real-time intelligence, and agents that focus on specific functional areas. It also described ecosystem agents that connect with partner platforms.
Dynatrace said organisations could adopt the system in phases. It described a path that starts with AI-driven insights and recommendations, then moves to automation for supervised operations with human oversight, and then to autonomous operations with guardrails and controls.
“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, Dynatrace. “Dynatrace Intelligence fuses deterministic and agentic AI, removing the guesswork and delivering AI‐powered observability organisations can trust.”
Autodesk framed the announcements as consistent with its own direction of travel for IT operations.
“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, 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.”
Domain agents
Alongside Dynatrace Intelligence, the company announced Dynatrace Intelligence Agents. Dynatrace described these as ready-to-use domain-specific agents that “augment” SRE, development and security teams with autonomous action.
Dynatrace said the agents cover several roles. It listed foundational agents for causal reasoning, prediction and oversight. It also enumerated domain agents for SRE and DevOps issue prevention and remediation, business observability, and security operations for vulnerability identification and resolution. Dynatrace also described assist agents that interpret situations and guide actions using natural language.
Dynatrace said the agents can mobilise when the system detects anomalies or receives requests from users or partner agents. It said they can execute actions through existing tools that teams use to communicate, track work and deliver fixes.
The company also described agentic workflows with policy-driven controls and approvals. It said customers could use them for standard workflows and custom use cases.
Industry view
IDC linked the rise of AI agents to changes in observability and operations models.
“The evolution of observability platforms is moving from manual root cause analysis to preventive operations. Organisations 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, IDC.
Rob Strechay, Principal Analyst at TheCUBE research & Smuget Consulting, argued that deterministic approaches reduce risk and cost compared with prompt-driven large language models.
“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 organisations 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.
Dynatrace said its agent integrations depend on deterministic insight into how agents interact across systems.
“Organisations will see an explosion of AI agents in the coming year,” said Steve Tack, Chief Product Officer, 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, optimise performance, and achieve zero-outage outcomes.”
Dynatrace said Dynatrace Intelligence Agents are available now, and it expects more agents to follow.