Virtana launched a new Application Observability offering that achieves what legacy APM tools have failed to do: automatically trace performance failures from application code all the way down through infrastructure, networks, storage, and AI workloads to surface evidence-backed root cause without manual correlation.
Built for autonomous operations at scale, the solution redefines the application as a system rather than software, automatically correlating performance issues across the full enterprise stack, from code and services to infrastructure, networks, storage, and AI platforms. By enabling operators and AI agents to identify the true limiting dependency across hybrid environments, organizations gain faster, more precise root cause analysis without sacrificing governance or control.
Virtana unifies application, service, infrastructure, network, and AI signals into a single operational context so teams and autonomous AI agents can dynamically surface system-level root cause first, with evidence ready for action.
“Mission-critical applications such as airline reservation systems, payment processing systems, health care delivery systems, and emergency dispatch are no longer just code, but complex systems spanning software, services, infrastructure, and AI workloads,” said Paul Appleby, CEO of Virtana. “At this scale and complexity, legacy APM focused on code and human-only operations is no longer a credible way to understand how applications behave. Our research shows that this trajectory will accelerate as AI workloads, new dependencies, greater infrastructure strain, and failure modes that legacy tools cannot explain. The only viable path forward is open, agentic, system-level observability.”
Virtana’s new Application Observability capability delivers visibility into request flows, service interactions, latency, and errors, and automatically correlates those signals to downstream dependencies across infrastructure, storage, network, and AI workloads. By unifying application telemetry with full-stack observability, Virtana makes it possible for teams to immediately determine whether performance issues originate in application code or downstream constraints such as storage contention, network congestion, infrastructure saturation, or platform instability.
The new Application Observability capability provides:
- AI-native, agentic investigation and automation enabling natural language analysis grounded in operational context through Virtana’s MCP Server and compatible with leading AI assistants (ChatGPT, Claude, Gemini, Copilot).
- System Dependency Graph foundation that continuously maps relationships across applications, services, Kubernetes workloads, infrastructure, networks, storage, and AI platforms—providing the system-level context that enables automated reasoning and investigation.
- AI-powered root cause analysis that automatically identifies where latency, failures, or constraints originate across your entire stack and prioritizes the most likely limiting dependency with supporting evidence.
- Comprehensive observability across your application lifecycle—combining end-to-end transaction tracing, intelligent log correlation, and synthetic monitoring to detect user-impacting issues and trace root causes from user layer to infrastructure.
- Kubernetes-aware observability providing native visibility into clusters, workloads, nodes, and resource contention across your container environments.
“At modern scale, root cause rarely exists inside a single service or trace. It emerges from interactions between application runtime behavior, Kubernetes orchestration, infrastructure capacity, and network dynamics,” said Amitkumar Rathi, Chief Product Officer at Virtana. “Legacy observability was built for a world where applications were just code. Today’s systems are dynamic, distributed, and increasingly driven by AI, and fragmented tools cannot keep up. We built Virtana to see the entire system and correlate traces, logs, topology, and infrastructure telemetry into one operational context, allowing engineers and AI agents to act on it instead of chasing symptoms across disconnected signals.”
When an application issue appears, Virtana traces it across the full system, revealing how services, infrastructure, networks, and AI workloads interact to create the problem. Instead of debating symptoms, teams receive evidence-backed guidance grounded in real operational context, accelerating triage and minimizing downtime.
The new Virtana Application Observability capability is available immediately.
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