Virtana announced support for HPE AI Factory, including HPE AI-ready server infrastructure, through validation in the HPE Server Partner Program.
Delivered as part of the Virtana AI Platform, AI Factory Observability (AIFO) provides customers with a proven, production-ready agentic observability solution that interoperates seamlessly with HPE AI infrastructure. The validation gives organizations confidence that Virtana's AI observability platform interoperates cleanly with HPE servers and is supported in production AI environments. This announcement marks Virtana’s fourth major AIFO integration in 2026, further expanding Virtana's position as the system-aware agentic observability platform spanning the industry's leading AI infrastructure ecosystem.
“AI is becoming foundational infrastructure for every industry, and the organizations that lead will be the ones that operate it with the same discipline they apply to every other mission-critical system,” said Paul Appleby, CEO of Virtana. “The HPE AI Factory provides the foundation for enterprise AI. Virtana extends that foundation with end-to-end agentic observability, giving customers the visibility, governance, and operational control they need to optimize performance, improve efficiency, and scale AI with confidence.”
The Virtana AI Observability Platform extends AIFO across HPE AI-ready server infrastructure, correlating GPU performance with the memory, power, thermal, and reliability signals that determine whether AI workloads run efficiently. Instead of operating AI infrastructure as a black box, customers can measure, optimize, and maximize the business value of their HPE-based AI investments from day one.
The Virtana AI Observability Platform delivers the following AIFO capabilities for validated HPE AI-ready server infrastructure:
- GPU and compute performance tracking measures utilization, memory consumption, and throughput across HPE AI-ready servers, identifying idle and underutilized capacity and connecting infrastructure consumption to workload output
- Power and thermal intelligence monitors power draw and thermal conditions in real time, surfacing risk before it disrupts production AI workloads
- Reliability monitoring identifies hardware degradation and reliability signals early, helping teams distinguish infrastructure issues from workload or orchestration problems
- Data movement visibility tracks how data flows across the AI factory, correlating pipeline performance with training and inference throughput
- AI capacity planning connects infrastructure consumption trends to scaling decisions, giving teams the evidence needed to plan capacity with confidence
- Cost and business outcome correlation maps infrastructure consumption to AI workload costs, enabling teams to evaluate the return on their HPE AI investment
As enterprises run agentic AI workloads across distributed infrastructure, validation through the HPE Server Partner Program gives customers confidence that Virtana’s observability platform is built to perform in production. That production-grade reliability is what separates a proof of concept from a system organizations can govern and optimize with confidence at scale.
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