Building Production-Ready AI Infrastructure: How Megaport and Vultr Are Solving the Enterprise Challenge
By Kevin Dresser, Solutions Architect
By bridging traditional enterprise environments with modern GPU resources, we're helping organizations build AI infrastructure that's truly ready for production workloads.
Co-authored by Duncan Ng, Vice President Solutions Engineering, Vultr
As enterprises move from AI experimentation to production deployment, most are realizing a fundamental truth: Successful AI adoption requires more than just access to GPU computing power. Production AI also needs a thoughtfully architected foundation – one that seamlessly combines secure, high-performance networking with flexible GPU computing capabilities.
That’s why Megaport and Vultr have joined forces to tackle this challenge head-on.
By bridging traditional enterprise environments with modern GPU resources, we’re helping organizations build AI infrastructure that’s truly ready for production workloads.
Why Megaport and Vultr?
The partnership between Megaport and Vultr aligns both providers’ strengths to support enterprises in making their AI goals a tangible reality.
- Vultr’s high-performance GPU cloud provides enterprises with flexible, cost-effective access to AI computing resources.
- Megaport’s global Network as a Service platform enables secure, reliable connectivity between existing enterprise infrastructure and these crucial GPU resources.
Together, we’re helping organizations bridge the gap between their current infrastructure investments and the specialized compute resources needed for AI workloads.
The evolution of enterprise AI infrastructure
At the beginning of the AI boom, adoption often followed a familiar pattern: Organizations would carve out isolated environments for their data science teams, typically relying on a single cloud provider’s GPU instances or building small on-premises GPU clusters.
While this approach worked for proof-of-concept projects, enterprises quickly discovered their limitations when scaling to production. Procuring additional hardware became incredibly difficult, and GPUs from just one hyperscale cloud provider were not often immediately available in the right location, at the right price.
Today’s mature AI implementations look markedly different. Now, organizations are embracing distributed and complex architectures that combine:
- on-premises data centers housing sensitive training data
- colocation facilities providing high-performance compute
- multiple cloud providers offering specialized GPU capabilities
- edge locations supporting real-time inference.
The story is not dissimilar to the enterprise cloud journey in the years prior to the AI boom, which we’ve written about previously. Not long after companies adopted cloud technology from a single vendor, they realized the cost and availability benefits of using multiple cloud providers.
With the subsequent rise of multicloud, enterprise IT infrastructure became increasingly distributed – and the underlying network became critical for overall performance and resilience.
A joint approach to production-ready AI
When used together, Megaport and Vultr simplify the complexity brought by modern, distributed AI networks. By combining Vultr’s GPU-as-a-Service platform with Megaport’s global network fabric, enterprises can:
- quickly establish private, high-performance connections to GPU resources
- maintain data sovereignty while leveraging cloud-based AI capabilities
- scale compute resources up and down based on demand
- optimize data transfer costs with predictable, usage-based pricing
- create multi-region AI architectures with consistent performance.
Real-world scenario
Healthcare: Distributed Medical Imaging Analysis
A leading healthcare provider needed to process medical imaging data from multiple clinics while maintaining HIPAA compliance. Clinicians and patients then needed to view their results via the provider’s healthcare portal. The joint solution from Megaport and Vultr included:
- local edge data aggregation from clinics
- secure transfer, via Megaport virtual and physical access services, onto Megaport’s private network
- direct access to secure data stores in public and private clouds
- private connections from data stores to Vultr’s GPU cloud for AI processing
- results distribution back to clinics through the same secure infrastructure.
As a result of deploying Megaport and Vultr, the healthcare provider now benefits from secure, scalable, low-latency connections to handle AI production workloads with efficiency and ease.
Build your production-ready AI infrastructure
Now, you can see for yourself how Megaport and Vultr are helping enterprises create the foundation for successful AI deployment. Join our upcoming webinar for a technical deep dive into how we’re working together to solve the challenges of production AI infrastructure.
Join us for a live demo of how you can:
- design hybrid architectures that optimize for both performance and cost
- implement secure, low-latency connectivity to GPU resources
- manage AI data pipelines across distributed environments
- leverage our combined solutions to simplify infrastructure complexity.
We’ll showcase how the integration of Megaport’s networking platform with Vultr’s GPU as a Service enables rapid deployment of production-ready AI infrastructure that scales with your needs.
Date: Thursday, March 6, 2025
Times:
- APAC - 10:00am AEST
- EMEA - 10:00am GMT | 11:00am CET
- AMER - 11:am PST | 2:00pm EST
Don’t miss this opportunity to learn from real-world examples and get practical how-tos for building resilient AI infrastructure for your production workloads.
Register now
