To strengthen its AI workload management capabilities, NVIDIA has entered into a definitive agreement to acquire Run:ai, a prominent provider of Kubernetes-based workload management and orchestration software. As AI deployments become increasingly complex and distributed across multiple infrastructures, efficient resource utilization has become a priority for businesses.
Run:ai provides an open platform built on Kubernetes, a popular orchestration layer for modern AI and cloud infrastructure. The platform supports multiple Kubernetes variants and integrates seamlessly with third-party AI tools and frameworks. Run:ai’s technology allows enterprise customers to efficiently manage and optimize their computing infrastructure across on-premises, cloud, or hybrid environments.
This acquisition allows NVIDIA to provide customers with a centralized interface to manage shared computing infrastructure and simplify access to complex AI workloads. It also provides features such as user management, resource allocation control, and resource utilization monitoring. Run:ai’s platform enables GPU pooling and computing power sharing, enabling efficient GPU cluster resource utilization.
As part of the acquisition, NVIDIA plans to continue offering Run:ai’s products under the same business model. The company also plans to invest in developing Run:ai’s product roadmap to align with NVIDIA’s DGX Cloud AI platform. NVIDIA DGX server and workstation customers and DGX Cloud users will gain access to the capabilities of Run:ai, specifically deploying generative AI across multiple data center locations.
Run:ai has had a close collaboration with NVIDIA since 2020, and this acquisition further strengthens the partnership. Omri Geller, CEO of Run:ai, expressed his excitement to join NVIDIA and continue our journey together.
The acquisition of Run:ai is consistent with NVIDIA’s commitment to providing comprehensive solutions for AI infrastructure management. By combining their expertise, NVIDIA and Run:ai aim to provide customers with increased GPU utilization, improved GPU infrastructure management, and increased flexibility in AI deployment. This acquisition reflects NVIDIA’s commitment to advancing AI technology and supporting enterprise AI initiatives.
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