Agentic Observability: AI That Understands Your Entire System
Observe. Reason. Act.
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Virtana applies agentic AI to IT operations, giving autonomous agents the system-wide context to observe the entire environment, reason across dependencies, and act intelligently to prevent and resolve problems.
By connecting telemetry across applications, services, infrastructure, cloud, Kubernetes, storage, networks, and AI workloads, Virtana moves organizations from monitoring toward autonomous operations.
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Observe. Reason. Act.
From Legacy Monitoring to Autonomous Operations
Virtana transforms continuous system telemetry into operational intelligence through an agentic lifecycle designed for humans and AI agents, moving IT operations from legacy monitoring and investigation to autonomous operations.
OBSERVE
See the entire system.
REASON
Understand what matters.
ACT
Take intelligent action.
System Dependency Graph
Give AI a map of how your system actually works
Virtana continuously discovers and models relationships across applications, services, Kubernetes, compute, storage, networks, cloud, and AI infrastructure. The System Dependency Graph gives agents a real-time understanding of how those components depend on one another.
When something changes, agents can trace its impact across the system—connecting symptoms to the infrastructure, service, application, or dependency actually responsible.
Event Intelligence
Let AI agents find the signal behind the noise.
Virtana continuously correlates events against system topology and dependencies to determine which signals are symptoms, which represent true operational constraints, and how problems propagate across the environment.
Instead of sending teams another alert to investigate, Virtana helps diagnose what matters, what is affected, and where investigation should begin.
Diagnostic AI Agents
Automated Root Cause Analysis Across Every Layer
Virtana’s Diagnostic Agents function as SREs in a box, investigating across application, service, infrastructure, storage, network, Kubernetes, cloud, and AI workload data—using system relationships and operational evidence to determine where performance degradation actually originates.
Agents don’t simply summarize alerts. They build and test an evidence-backed explanation of what’s happening across the system.
Natural Language Investigation
Ask your environment. Get answers grounded in your environment.
Investigate complex operational questions without manually jumping between dashboards and tools.
Virtana lets teams use natural language to explore alerts, dependencies, performance, and root cause. Responses are grounded in Virtana’s system model and operational telemetry, giving teams answers backed by the same context used by the platform’s diagnostic agents.
- “Why is checkout latency increasing?”
- “What changed before this service degraded?”
- “Which applications are affected by this storage issue?”
- “Show me the evidence for the root cause.”
Remediation Agents
From AI Remediation to Autonomous Operations
Virtana Remediation Agents turn diagnosis into intelligent action, using system context and diagnostic evidence to recommend corrective actions and automate approved responses. Policies and human-in-the-loop controls determine when agents recommend, when they ask for approval, and when they can act autonomously.
That creates a controlled path from AI-assisted remediation to autonomous remediation and, ultimately, self-healing IT operations.
MCP Server
Bring trusted operational context to every Agent.
Virtana Remediation Agents turn diagnosis into intelligent action, using system context and diagnostic evidence to recommend corrective actions and automate approved responses. Policies and human-in-the-loop controls determine when agents recommend, when they ask for approval, and when they can act autonomously.
That creates a controlled path from AI-assisted remediation to autonomous remediation and, ultimately, self-healing IT operations.
The Virtana AI-Native Architecture
A layered AI architecture that transforms full-stack telemetry into system understanding and autonomous operations.
AI That Sees More Can Do More.
Full-stack context
Agents reason across applications, services, infrastructure, storage, networks, cloud, Kubernetes, and AI workloads—not isolated monitoring domains.
System-aware intelligence
A continuously evolving dependency graph gives AI an understanding of how the environment actually works.
Evidence before action
Diagnostics are grounded in telemetry, topology, dependencies, events, and operational evidence.
Built for autonomy
Diagnosis, natural-language operations, remediation, automation, and MCP create a path from insight to intelligent action.
FAQs
A: Agentic observability is an approach to IT operations in which AI agents continuously observe system behavior, reason across telemetry and dependencies, and take intelligent action to diagnose, prevent, and remediate operational issues.
Unlike traditional observability, which primarily gives humans data and tools for investigation, agentic observability gives AI agents the system context and operational intelligence neededto participate directly in IT operations.
At Virtana, agentic observability is built on Observe. Reason. Act.: observe the entire system, reason over relationships and evidence, and act through governed automation and remediation.