DEVOPSdigest

Oracle has expanded its collaboration with NVIDIA to help customers streamline the development and deployment of production-ready AI, develop and run next-generation reasoning models and AI agents, and access the computing resources needed to further accelerate AI innovation.

As part of the initiative, NVIDIA AI Enterprise, an end-to-end, cloud-native software platform, is now available natively through the Oracle Cloud Infrastructure (OCI) Console. In addition, NVIDIA GB200 NVL72 systems on OCI Supercluster are now generally available with up to 131,072 NVIDIA Blackwell GPUs. Oracle has also become one of the first hyperscalers to integrate with NVIDIA DGX Cloud Lepton, an AI platform with a compute marketplace that connects developers with a global network of GPU compute.

“Oracle has become the platform of choice for AI training and inferencing, and our work with NVIDIA boosts our ability to support customers running some of the world’s most demanding AI workloads,” said Karan Batta, senior vice president, Oracle Cloud Infrastructure. “Combining NVIDIA’s full-stack AI computing platform with OCI’s performance, security, and deployment flexibility enables us to deliver AI capabilities at scale to help advance AI efforts globally.”

“Developers need the latest AI infrastructure and software to rapidly build and launch innovative solutions,” said Ian Buck, vice president of hyperscale and HPC, NVIDIA. “With OCI and NVIDIA, they get the performance and tools to bring ideas to life, wherever their work happens.”

Unlike other NVIDIA AI Enterprise offerings that are available through a marketplace, OCI is making it natively available through the OCI Console and enabling customers to purchase it with their existing Oracle Universal Credits. This reduces the time it takes to deploy the service and allows customers to benefit from direct billing and support. In addition, with NVIDIA AI Enterprise on OCI, customers can quickly and easily access 160+ AI tools for training and inference, including NVIDIA NIM microservices, a set of optimized, cloud-native inference microservices designed to simplify the deployment of generative AI models. With an end-to-end set of training and inference capabilities on OCI, customers can combine them with OCI services for building applications and managing data across a range of distributed cloud deployment options.

By making NVIDIA AI Enterprise available through the OCI Console, Oracle is helping customers to deploy it across OCI’s distributed cloud, which includes OCI’s public regions, Government Clouds, OCI sovereign cloud solutions, OCI Dedicated Region, Oracle Alloy, OCI Compute Cloud@Customer, and OCI Roving Edge Devices. This helps customers address security, regulatory, and compliance requirements when developing, deploying, and operating their enterprise AI stack.

To help meet the increasing need for AI training and inference, Oracle and NVIDIA continue to evolve AI infrastructure with new NVIDIA GPU types across Oracle’s distributed cloud. For example, OCI now offers liquid-cooled NVIDIA GB200 NVL72 systems on OCI Supercluster that can scale to up to 131,072 NVIDIA GPUs. In addition, customers can now use thousands of NVIDIA Blackwell GPUs on NVIDIA DGX Cloud and OCI to develop and run next-generation reasoning models and AI agents.

Oracle’s distributed cloud, AI infrastructure, and generative AI services, combined with NVIDIA accelerated computing and generative AI software, are enabling governments and enterprises to deploy AI factories. These new AI factories leverage the NVIDIA GB200 NVL72 platform, a rack-scale system that combines 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell GPUs, to help deliver exceptional performance and energy efficiency for agentic AI accelerated by advanced AI reasoning models.

To help developers easily access the advanced GPU resources they need to further accelerate AI development and deployment, Oracle is one of the first hyperscalers to integrate with NVIDIA DGX Cloud Lepton. This integration enables developers to access OCI’s high-performance GPU clusters and the scalable compute needed for AI training and inference, digital twins, and massively parallel HPC applications. It also helps developers support strategic and sovereign AI goals by allowing them to tap into GPU compute capacity in specific regions for both on-demand and long-term computing.