About This Webinar

Building modern AI infrastructure requires more than just powerful GPUs. It also demands integrated orchestration, high-performance networking, and robust multi-tenancy.

To address these requirements, OpenNebula has been validated as an orchestration platform compatible with NVIDIA Spectrum-X Ethernet Networking (learn more).

In this webinar, we’ll demonstrate how this validation works in practice within the NVIDIA Air environment—a cloud-native platform designed to model and simulate data center networking and AI infrastructure. You’ll see how OpenNebula leverages NVIDIA Spectrum-X Ethernet networking inside NVIDIA Air to orchestrate GPU-accelerated workloads efficiently, securely, and at scale.

What You’ll Learn:

– Introduction to the Solution: How OpenNebula orchestration, NVIDIA Spectrum-X Ethernet networking, and NVIDIA Air work together to simplify AI infrastructure and enable efficient AI Factories.
– AI Factory Challenges: How to tackle the key cloud management and orchestration complexities in production AI workloads.
– Integration Overview: A technical deep dive into OpenNebula’s compute and orchestration capabilities, NVIDIA Spectrum-X Ethernet networking performance, and the benefits of this integration within the NVIDIA Air ecosystem.
– Live Demo: A practical demonstration of deploying and operating AI workloads using OpenNebula orchestration with NVIDIA networking and simulation capabilities.
– Q&A: Get your questions answered by OpenNebula and NVIDIA experts on orchestrating AI Factories, GPU workloads, and using Spectrum-X Ethernet networking and NVIDIA Air.

This session will be hosted by Alberto Picón, Principal Technologist for Cloud-Edge Engineering at OpenNebula Systems, and Avi Alkobi, Senior Director Business Development at NVIDIA. 

With AI transforming every industry, organizations need a scalable, secure AI infrastructure. Don’t miss this webinar to see how to build production-ready AI Factories with OpenNebula and NVIDIA technologies to power the most demanding enterprise workloads.