Virtana, a global leader in AI Factory observability, announced a strategic partnership with NVIDIA to deliver enhanced visibility and performance management for enterprise AI Factories. The collaboration integrates Virtana’s observability platform with NVIDIA’s AI and accelerated computing technologies, empowering IT teams to better manage complex, distributed AI infrastructures with speed, reliability, and intelligence.
As enterprises shift from AI experimentation to full-scale industrialization, the complexity of monitoring and optimizing performance across heterogeneous infrastructure layers continues to rise. Virtana, an NVIDIA Connect program member, brings unified observability across on-premises, cloud, and containerized environments. This integration extends deeper observability into NVIDIA GPU-powered infrastructure, enabling faster insights, improved automation, and optimized resource utilization.
The urgency for AI infrastructure readiness has never been greater. According to Gartner, “By 2029, 70% of large enterprises failing to effectively utilize AI factories will cease to exist.” The takeaway is clear: success with AI requires intelligent observability to ensure infrastructure keeps pace with enterprise demands.
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During his GTC 2025 keynote, Jensen Huang, NVIDIA founder and CEO, emphasized this balance:
“AI infrastructure must account for more than just raw performance, it must also consider energy consumption, physical space, and operational costs. Optimizing workloads to use only the compute resources truly necessary will be critical for scaling AI responsibly. Businesses will increasingly need to strike a balance between performance requirements and sustainability constraints if ‘AI everywhere’ is to become a reality.”
“To accelerate Virtana’s mission to deliver AI Factory Observability, powered by AI, at industrial scale, our collaboration with NVIDIA is critical,” said Paul Appleby, CEO and President of Virtana. “By combining Virtana’s deep expertise in hybrid cloud performance with NVIDIA’s market-leading computing and AI capabilities, we’re empowering enterprises to improve application performance, accelerate root cause analysis, and reduce infrastructure costs. Our collaboration gives IT teams the intelligence they need to support AI-native workloads with confidence and efficiency.”
Driving AI-Optimized IT Operations
The joint effort focuses on delivering real-time, intelligent insights that enable enterprises to align infrastructure performance with business objectives while reducing mean-time-to-resolution (MTTR). With enhanced observability for NVIDIA GPU environments, IT leaders can accelerate troubleshooting, maximize resource efficiency, and prepare for large-scale AI-native deployments.
Key Capabilities of the Virtana Platform
- Automated Topology Discovery: Machine learning maps interdependencies between AI applications, GPUs, storage, and networking components, offering real-time visibility into system behavior and potential bottlenecks.
- AI-Powered Root Cause Analysis: Leveraging NVIDIA AI Enterprise, Virtana enables rapid identification of root causes by processing massive datasets in seconds, minimizing downtime.
- Predictive Performance Management: Combines historical and live telemetry data to anticipate potential issues before they affect mission-critical workloads.
- Cost & Capacity Optimization: AI-driven analytics improve resource forecasting and cost efficiency, particularly for GPU utilization.
- Natural Language Query with Virtana Copilot: A generative AI assistant that allows users to query infrastructure data in plain language, making observability insights accessible to non-technical stakeholders.
Observability for NVIDIA NIM with OpenTelemetry
Virtana also delivers comprehensive observability for NVIDIA NIM, using OpenTelemetry standards to provide deep visibility into application performance, health, and availability. With this integration, enterprises can monitor, trace, and optimize AI workloads on NIM in real time.
Enabling Enterprise AI Success
With Virtana’s observability platform, organizations can:
- Detect anomalies in AI workload performance instantly.
- Assess infrastructure impact across hybrid environments.
- Forecast resource requirements for upcoming AI initiatives.
- Prevent costly downtime with proactive monitoring.
Together, Virtana and NVIDIA are redefining what enterprise IT teams can achieve with AI Factory observability, ensuring that organizations not only scale AI but also operate it responsibly, efficiently, and with resilience.