Unlock Deeper Insights with Virtana: Full-Stack Root Cause Analysis Beyond Traditional APM

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Virtana Introduces Full-Stack Root Cause Analysis for Modern Applications

Virtana has launched a new Application Observability offering that enables organizations to identify the root cause of performance issues across their entire technology stack, from application code to infrastructure, networks, storage, and AI workloads. This capability is designed to provide evidence-based root cause analysis without manual correlation, redefining the application as a system rather than just software.

Research Highlights the Need for Comprehensive Visibility and Automation

According to Virtana’s research, “AI Is Breaking Human-Managed Operations,” 52% of IT practitioners report persistent visibility gaps and fragmented observability, despite significant investments in observability tools. The study found that median annual observability spending exceeds $800,000 per enterprise, with some organizations spending over $10 million annually on a single vendor. These findings highlight the need for a new architecture that can provide comprehensive visibility and automation.

“Mission-critical applications are no longer just code, but complex systems spanning software, services, infrastructure, and AI workloads,” said Paul Appleby, CEO of Virtana. “Legacy APM is no longer sufficient to understand how these applications behave. Our research shows that this trajectory will accelerate as AI workloads, new dependencies, and infrastructure strain continue to multiply.”

Legacy APM Limitations and the Need for a New Approach

Legacy Application Performance Monitoring (APM) platforms have limitations in identifying the root cause of performance issues, as they focus primarily on code-level analysis and rarely account for storage behavior, network paths, Kubernetes resource pressure, and other external factors. Virtana’s new offering addresses this limitation by unifying application, service, infrastructure, network, and AI signals into a single operational context, enabling teams and autonomous AI agents to dynamically surface system-level root cause analysis.

“Modern applications are distributed systems, and performance constraints frequently originate in infrastructure, network, or platform layers that traditional APM was never designed to see,” said Doug Syer, Chief Engineer for AI Monitoring and Observability at NWN. “Virtana Application Observability offers true system-level visibility, correlating signals across the full stack, enabling the immediate transition from symptoms to evidence-backed root cause.”

Key Features and Benefits of Virtana Application Observability

Virtana’s Application Observability capability provides visibility into request flows, service interactions, latency, and errors, and automatically correlates those signals to downstream dependencies across infrastructure, storage, network, and AI workloads. This capability enables teams to immediately determine whether performance issues originate in application code or downstream constraints such as storage contention, network congestion, or platform instability.

The new offering includes AI-native investigation and automation, system dependency graph foundation, AI-powered root cause analysis, comprehensive observability, and Kubernetes-aware observability. These features enable organizations to detect user-impacting issues, trace root causes, and prioritize the most likely limiting dependency with supporting evidence.

When an application issue appears, Virtana traces it across the 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.