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LOGICMONITOR BLOG

From Systems of Intelligence to Systems of Action: Innovations Across the Autonomous IT Platform

IT operations are moving from systems that explain to systems that act. Here’s every innovation LogicMonitor announced at Elevate 2026, and where to start.

6–9 minutes
Garth Fort

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The quick download:

IT operations are moving from systems of intelligence to systems of action, and LogicMonitor is announcing innovations across every layer of its Autonomous IT platform to lead that shift.

  • You can’t automate what you can’t see, so the foundation comes first: OpenTelemetry metrics, IIS logs through the OpenTelemetry collector, and infrastructure cost inside the workflows you already run.

  • Context connects telemetry to the services and users they affect: a context graph and topology-aware correlation show which signals belong together.

  • Edwin AI turns meaning into action inside guardrails you control — in Slack, Microsoft Teams, ServiceNow, and LM Envision, with approvals and an audit trail built in.

  • Start with the layer that is your biggest gap today, and let it pull the other two forward.

From Systems of Intelligence to Systems of Action: Innovations Across the Autonomous IT Platform

It’s 2:14 a.m. The online checkout service is slow, the page fires, and the on-call engineer opens the first of nine dashboards. The Kubernetes cluster looks fine. The database looks fine. Forty minutes later someone notices the CDN provider posted an incident an hour ago. Nothing in your stack was broken. Your customers still couldn’t buy anything.

If you run infrastructure and operations, you’ve lived some version of that night. Customer experience degrades, revenue is put at risk, and engineers lose precious time assembling a picture that should already be clear. The answer was never in one tool. It was in the relationships between them, and no one had those relationships written down in a place a machine could read.

For a decade, the tools you bought got better at explaining that night after it happened. Observability let you see. AIOps helped you understand. Neither one acted. That is the shift LogicMonitor is announcing at Elevate 2026: innovations across every layer of our Autonomous IT platform — the AI-ready data foundation, the context that gives data meaning, and Edwin AI acting on it under your governance — to move IT operations from systems of intelligence to systems of action. Here’s what we’re announcing, why the order matters, and where to start. 

Let’s dig in.

Why “more AI” doesn’t fix IT operations

IT teams face three pressures: data and alert volumes are rising, AI expectations are growing, and automation is hard to trust when it can affect production systems.

Adding an AI assistant to existing dashboards does not solve the underlying problem. Without relationships between services, infrastructure, applications, and business impact, AI can summarize alerts, but it cannot reliably explain what matters or recommend the right action.

Autonomous IT requires a platform built from the bottom up: complete, AI-ready data, signals that connects to operational context, and AI that helps teams take action within the controls they define.

Autonomous IT is built bottom-up

Think of a good investigator. Evidence is collected first, completely and admissibly. It’s organized into a case file that shows how the pieces relate. Only then does anyone decide what to do, and that decision is reviewed before it’s acted on. Skip a step and you get a confident conclusion that’s wrong.

The LogicMonitor platform is built on the same three layers, and the dependency runs upward. You cannot build unified context without governed, AI-ready telemetry. You cannot deliver AI actions teams can review and approve without unified context. That is why we are announcing innovations across all three at once—a platform announcement, not a feature announcement.

Complete, AI-ready data

The Enterprise Data Foundation collects, enriches, governs, and scales the telemetry that everything above it depends on. Across the LogicMonitor customer base, that means more than 5 million devices and over 2 trillion metrics a day. What’s new is how that data arrives and what it carries:

  • OpenTelemetry metrics ingestion: Push metrics into LogicMonitor in a standardized, vendor-neutral way using either upstream open-source or LogicMonitor OpenTelemetry collectors. It removes pull-based requirements, reaches restricted environments where SNMP access is limited, and handles high-scale streaming telemetry from network devices.
  • IIS application log collection through the OpenTelemetry Windows collector: Application-layer evidence from Windows web tiers, collected through the same open path.
  • Infrastructure cost inside observability workflows: Spend appears alongside performance and reliability, so the team optimizing an environment sees the cost of what it’s running while it’s running it.

Read the deep-dive: The Foundation Under Autonomous IT: Why AI-Ready Data Comes First

Connected context

The Unified Context Layer connects infrastructure, applications, services, users, and business context into one understanding of how your environment fits together. This is the layer that turns “three alerts fired” into a much more insightful “one dependency failed, and here’s who it affects.”

  • The ITOps context graph: A connected model of your environment spanning infrastructure, applications, services, and user context, built so Edwin AI reasons over relationships rather than isolated data points.
  • Topology-aware correlation: Correlation that uses dependency relationships, not just time and text proximity, to decide which events belong together.
  • Service Insights with Synthetics: LogicMonitor service constructs are integrated with synthetic tests, so service health and measured user experience live in the same view.
  • Unified context across LM Envision, Edwin AI, Digital Experience, and third-party sources: One context set across the portfolio, extended with external sources such as CMDB and ITSM.

Read the deep-dive: Why Context, Not More Data, is What Makes AI Useful in IT

Governed action

The AI Layer is where understanding becomes action. Edwin AI uses telemetry from across your environment and the context graph to investigate incidents, prioritize by business impact, and recommend or execute actions within the controls you define.

  • Deep AI Investigations 2.0: Richer context and governed remediation inside the investigation flow, grounded in diagnostic evidence collected at the time of the incident.
  • Multi-agent orchestration: Edwin AI coordinates domain-specific agents that investigate close to their own data and return contextual findings, so domain expertise works closer to the data and delivers faster root cause identification and next-best actions. 
  • Edwin AI where your team already works: In Slack, Microsoft Teams, ServiceNow, and LM Envision, so investigations happen in the incident channel, not in another tab.
  • A unified MCP offering: One offering across the portfolio supports custom integrations, IDE and terminal workflows, and advanced automation, using the same open protocol their own agents use.
  • AI automation workflows: Teams build automation without code and run it within approval boundaries, with auditability and policy checks in the execution path. 
  • AI-based auto-clustering: Related events are grouped automatically before triage, so teams can begin with a contextualized incident rather than a queue of raw events. 

Edwin AI is becoming the front door to IT operations, by helping teams understand what’s happening, why it matters, and what action to take next. LogicMonitor is bringing together telemetry, context, specialized AI agents, and automation. Edwin AI helps teams cut through noise, find root cause, and resolve issues faster while people stay in control.

Read the deep-dive: AI Where the Work Happens: How Edwin AI Turns Understanding Into Governed Action

What it looks like when the layers work together

Back to 2:14 a.m. with the layers in place. Here’s how the system is designed to work.

The online checkout service’s Kubernetes pods push metrics over OpenTelemetry. A synthetic test measuring the real checkout journey degrades at the same time. The context graph already knows the service depends on those pods, a payment API, and a CDN, and topology-aware correlation groups the pod latency, the synthetic failure, and an Internet signal into one incident instead of three.

Edwin AI opens an investigation in the on-call Slack channel. It delegates to a Kubernetes agent and an Internet agent, each working close to its own data, and returns a finding: the CDN edge in one region is degraded, and the retry storm is what’s pressuring the pods. It recommends an existing playbook to fail traffic over to a healthy edge, shows the diagnostic evidence, and waits for the engineer to approve. The action runs. The synthetic test recovers. The whole thing is logged.

The engineer never opened nine dashboards. She also never gave up control. That combination is the point.

Where to start

Customers progress from observability to agentic AIOps and toward Autonomous IT at a pace they govern with people staying in control.

So the practical question is, which layer is your biggest gap today? If your team still finds out about outages from customers, start with the data foundation and add Digital Experience. If your alerts are complete but nobody can tell which ones matter, start with context. If you already trust your context and want to give hours back to your engineers, start with Edwin AI, integrated into where your teams already work. Whichever solution you pick, it pulls the other two solutions forward.

Conclusion

Autonomous IT is not a single feature or a destination you reach overnight. It is an operating model built on trustworthy data, connected context, and governed AI action.

The innovations announced at Elevate 2026 strengthen each layer so organizations can adopt autonomy at their own pace with people remaining in control.

This is how IT teams move beyond managing incidents toward protecting growth.

We don’t just observe complexity. We operate it.

See what a system of action does with your hardest incident

See how Edwin AI can help your team move faster. Get a personalized demo today, and we’ll show you what’s possible.

FAQs

What is Autonomous IT?

Autonomous IT is an operating model in which IT systems detect and interpret operational conditions, predict outcomes, and take governed action, with humans in control but no longer stuck in every loop. It is closed-loop, connecting unified telemetry, business-aware context, AI-driven reasoning, and governed execution.

Does this announcement change the LogicMonitor products I use today?

No. You keep using LM Envision, Digital Experience, and Edwin AI as you do now. What changes is that the AI experience becomes progressively more consistent across them, with shared context and shared governance underneath.

Does Edwin AI take action without approval?

Edwin AI recommends and executes actions within the controls, policies, and approval gates you define. Role-based access, inline policy checks, human-in-the-loop approvals, and an audit trail apply to automated actions.

What is the difference between agentic AIOps and Autonomous IT?

Agentic AIOps connects signals in context, prioritizes, and recommends action. Autonomous IT is the destination it builds toward: systems that sense, decide, and act under governance, so teams progress from guided response to governed automation to scaled autonomy.

Garth Fort profile image
By Garth Fort

Chief Product Officer

Garth Fort is LogicMonitor’s Chief Product Officer, where he leads global product strategy and execution for the company’s AI-powered observability platform, LM Envision. A seasoned technology executive, Garth brings more than 20 years of experience driving product innovation, business growth, and cloud transformation across some of the world’s most respected enterprise software companies.

Disclaimer: The views expressed on this blog are those of the author and do not necessarily reflect the views of LogicMonitor or its affiliates.

© LogicMonitor 2026 | All rights reserved. | All trademarks, trade names, service marks, and logos referenced herein belong to their respective companies.

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