September 2025 Summaries

The AI era is fundamentally transforming enterprise technology, rendering traditional cloud architectures inadequate for modern AI workloads that require real-time decision-making and autonomous operations. Organizations relying on legacy cloud strategies face challenges such as inflated costs, compromised compliance, and operational inefficiencies due to static performance models and rigid network architectures. Forrester's 2025 report emphasizes the necessity of adopting an AI-native cloud strategy, which involves building infrastructure intentionally designed for AI's dynamic requirements, including modular and composable architectures, deployment flexibility, ecosystem integration, and robust operations and governance. By aligning infrastructure with AI demands, businesses can avoid the pitfalls of retrofitting outdated systems and instead leverage AI as a competitive advantage. The report outlines five paths to AI-native infrastructure, stressing the importance of strategic planning and skill development to enable sustainable scaling and governance of AI initiatives.

AI adoption among platform engineering teams is significantly high, with nearly 89% of platform engineers using AI daily and 75% hosting or planning to host AI workloads, but most uses are for quick productivity boosts like code generation and documentation rather than strategic impact. Despite the enthusiasm, challenges such as skill gaps, unclear AI ownership, infrastructure readiness, and collaboration issues with data science teams hinder progress. Platform engineers are becoming crucial in the enterprise AI landscape, tasked with building and operating the infrastructure necessary to make AI scalable and secure. Success in moving AI beyond experimentation requires clear pathways and AI-ready infrastructure, with tools like Vultr's GPU-ready infrastructure providing templates for provisioning and configuring resources efficiently. These developments allow platform engineers to focus more on model development while ensuring security and compliance, ultimately driving AI's enterprise-wide impact.

Vultr has successfully developed an AI-native cloud platform by partnering with Supermicro and AMD to meet the demands of modern deployment, scalability, and security. In a recent webinar, Vultr's Senior Vice President of Engineering, Nathan Goulding, emphasized the importance of these partnerships in enabling the company to rapidly and reliably bring composable AI infrastructure to market. Supermicro provides critical support with their reliable hardware and expertise, while AMD's Instinct GPUs and EPYC CPUs form the backbone of Vultr's AI solutions. The collaboration has allowed Vultr to be a leader in integrating and deploying cutting-edge technology, ensuring their customers receive the latest advancements for evolving AI and HPC workloads.

In a recent webinar, Vultr's CMO Kevin Cochrane and AMD AI Business Development Manager Aleks Shargorodskiy discussed the capabilities of the AMD Instinct™ MI355X GPU and the advantages of using AMD's ROCm™ open-source software on Vultr's platform for AI applications. They highlighted a shift in the AI marketplace from prioritizing rapid time-to-market for startups to focusing on cost-efficient, scalable AI solutions for enterprises. The discussion emphasized the importance of price-to-performance benefits, urging users to conduct their own benchmarks to experience the advantages of AMD GPUs. The AMD Instinct series, compatible with the flexible ROCm architecture, supports diverse industry needs and facilitates open-ecosystem innovation. Cochrane and Shargorodskiy underscored the significance of continuous development in AI infrastructure and the need for developers to adapt their skillsets to emerging AI technologies, positioning AMD and Vultr as key players in this evolving landscape.

FluidCloud has partnered with Vultr to offer a streamlined cloud migration solution that allows businesses to move their workloads to Vultr's infrastructure rapidly and without the need for rearchitecting or experiencing downtime. Utilizing FluidCloud's Cloud Cloning™ technology, organizations can reverse engineer, replicate, and migrate their infrastructure across various cloud providers like AWS, Azure, and Google Cloud Platform directly into Vultr. This collaboration provides instant workload portability, real-time governance, and a scalable platform, addressing common migration challenges such as vendor lock-in, compliance risks, and cost overruns. Vultr offers a developer-friendly ecosystem with high performance and cost-effective infrastructure, built-in compliance, transparent pricing, and AI-ready capabilities. The partnership aims to simplify multi-cloud operations by ensuring resilience, compliance, and cost optimization, ultimately providing a seamless path for organizations to adopt Vultr's cloud solutions.

Vultr has introduced AMD Instinct™ MI355X GPUs to its offerings, available as both Vultr Bare Metal servers and Cloud GPU virtual machines, designed for enhanced AI training, inference, scientific simulation, and high-performance computing (HPC) workloads. These GPUs, built on AMD's CDNA™ 4 architecture, promise improved energy efficiency and computational performance, featuring 288GB of HBM3E memory suitable for large datasets and complex models, and supporting FP6 and FP4 precision formats for efficient processing. Users have the option of deploying these GPUs with maximum control on Bare Metal servers or with near-bare metal performance as part of Vultr's Cloud GPU virtual machines, benefiting from fast provisioning and seamless integration with Vultr's extensive cloud services, storage, networking solutions, and support for advanced virtualization features. The addition of these GPUs aims to enable high-density, high-throughput deployments with ultra-low latency, making them an appealing choice for those looking to advance complex AI and machine learning workloads, all with transparent pricing and ease of deployment through Vultr's control panel or API.

Baseten's collaboration with Vultr Cloud GPU marks an enhancement in the Vultr Cloud Alliance, offering an efficient solution for deploying and scaling AI inference by integrating Baseten's developer-centric inference platform with Vultr's infrastructure. This partnership enables developers and enterprises to manage AI models, including LLMs and diffusion models, without the complications of traditional hyperscale cloud providers, by providing low-latency, high-throughput infrastructure suitable for real-time applications like transcription and image generation. Baseten’s platform supports various AI tasks, from real-time transcription with Whisper to complex AI orchestration via Baseten Chains, and offers features like autoscaling and advanced observability. Vultr provides a robust infrastructure with global availability of NVIDIA and AMD GPUs, ensuring compliance with standards like GDPR and HIPAA, and offering flexible deployment options with tools such as Kubernetes and Terraform, all while maintaining cost transparency and avoiding vendor lock-in.