AI adoption is accelerating across industries, but moving from proof-of-concept to production introduces new challenges. Enterprise AI isn’t just about getting access to GPUs – it requires resilient, high-performance infrastructure that can handle massive data transfers, support hybrid environments, and ensure low-latency connectivity.
That’s why Megaport and Vultr are joining forces to help enterprises build production-ready AI infrastructure that scales. In our upcoming webinar, we’ll explore the key network and infrastructure considerations for supporting AI at scale, providing practical insights and real-world examples.
Why network infrastructure is critical for AI
In the early days of AI adoption, many enterprises relied on a single cloud provider or built small-scale GPU clusters on-premises. But as AI projects scale, so do the demands on infrastructure. Enterprises now require a distributed, hybrid approach that includes:
- On-premises data centers for data security and compliance
- Colocation facilities for high-performance computing
- Cloud-based GPUs to scale AI training and inference workloads
- Processing for real-time AI applications
The challenge? Ensuring that all these environments are connected seamlessly, securely, and with minimal latency.
How Megaport and Vultr solve AI infrastructure challenges
Megaport’s Network as a Service (NaaS) and Vultr’s GPU Cloud enable enterprises to build scalable, high-performance AI architectures that connect on-prem, cloud, and edge environments without the complexity of traditional networking.
With Megaport and Vultr, enterprises can:
- Establish private, high-speed connections to GPU resources
- Optimize data transfer costs with usage-based pricing
- Maintain data sovereignty while leveraging cloud-based AI
- Deploy multi-region AI architectures with low-latency connectivity
Register for the webinar: Architecting high-performance AI infrastructure
Want to see how it works? Join our webinar for a technical deep dive into networking best practices for AI infrastructure and a live demo showcasing how Megaport and Vultr simplify AI deployment.
What you’ll learn:
- How to design hybrid AI architectures for performance and cost efficiency
- Best practices for low-latency, high-speed networking to GPU resources
- How to securely manage AI data pipelines across distributed environments
- Real-world examples of enterprises scaling AI with Megaport and Vultr
Webinar details
Date: Thursday, March 6, 2025
Time:
- APAC - 10:00 am AEST
- EMEA - 10:00 am GMT | 11:00am CET
- AMER - 11:00 am PST | 2:00pm EST
Meet the experts
Duncan Ng: Duncan Ng is VP of Solutions Engineering at Vultr, leading Global Technical Go-To-Market across Presales, Technical Account Management, and Partner Engineering. With a background in Engineering, he helps users and partners navigate the cloud with a platform that delivers hyperscaler performance without complexity or cost surprises. Duncan’s experience spans startups, SaaS, and Fortune 500 enterprises, supporting internet-scale clients. He has built a Top 500 Supercomputer and served on the Technical Advisory Committees for CalREN & CENIC, shaping next-gen networking and cloud infrastructure.
Kevin Dresser: Kevin Dresser is a Solutions Architect, Network and Security Infrastructure, at Megaport. Kevin provides network and security expertise to alliance partners, including NFV integration and innovative CSP architectures on Megaport’s global NaaS platform. He brings a unique perspective from over 20 years designing, implementing, and supporting network and security infrastructure solutions across financial services, healthcare, and media.
Seize this chance to gain hands-on insights and master the art of building resilient, production-ready AI infrastructure that grows with your business. Secure your spot today!