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Artificial Intelligence (AI) is transforming how modern enterprises are doing business and pressing organizations to increasingly integrate AI, along with its Machine Learning (ML) and Deep Learning (DL) capabilities, into cloud-native applications to deliver more insight and value for their customers and employees. In fact, the recent 2022 Red Hat Global Outlook report found that AI/ML was the top emerging technology workload most likely to be considered in the next 12 months, with 53% of the IT leaders surveyed ranking it the top priority. 

To help organizations more quickly and easily develop AI/ML-powered cloud-native applications and deploy them into production, Red Hat is supportingt OpenShift on several new infrastructure footprints. OpenShift offers a ubiquitous infrastructure to enable machine learning operations (MLOps) at scale, spanning NVIDIA DGX systems, to Arm-based instances in the public cloud to a new class of datacenter hardware called NVIDIA BlueField-2 data processing units (DPUs)

Enterprises can try Red Hat OpenShift for AI workloads at no cost in a new curated lab for NVIDIA AI Enterprise available on NVIDIA LaunchPad

Red Hat has worked with NVIDIA for many years, most recently as a strategic member of the new NVIDIA AI Accelerated program, which supports partners developing world-class AI solutions on the NVIDIA AI platform. 

This collaboration has produced many capabilities that benefit software developers, IT operators and data scientists in organizations across the globe. Red Hat OpenShift’s full-stack automated operations and self-service provisioning enable teams to work together more efficiently to quickly and securely move ideas from development to production, for both applications and IT infrastructure. 

From simplification of infrastructure planning to day-zero activities to advanced AI model deployments, OpenShift capabilities, like integration with NVIDIA GPUs via the GPU Operator, support of NVIDIA NGC containers, and managing Kubernetes containers with OpenShift over NVIDIA BlueField DPUs help accelerate data analytics, modeling, inferencing tasks, and help to secure networking.

Bringing OpenShift’s DevOps and GitOps automation capabilities to the entire AI life cycle enables MLOps and allows for better collaboration between data scientists, ML engineers, software developers and IT operations. MLOps enables organizations to automate and simplify the iterative process of integrating models into software development processes, production rollout, monitoring, retraining and redeployment for continued prediction accuracy.

Today, we are announcing a major advancement in enabling MLOps by bringing together Red Hat OpenShift with the NVIDIA AI Enterprise software suite to accelerate and streamline the development, deployment and management of new AI-powered intelligent applications.

Certification of Red Hat OpenShift with NVIDIA AI Enterprise

Red Hat OpenShift is now certified and supported with NVIDIA AI Enterprise 2.0, a comprehensive portfolio of AI tools and frameworks from NVIDIA. The combined power of Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform, and the NVIDIA AI Enterprise software suite running on NVIDIA-Certified Systems offers a scalable AI platform that helps accelerate a diverse range of AI use cases, including DL and ML, across industries -- from healthcare to financial services to manufacturing, and more. 

This solution includes key technologies and support from NVIDIA and Red Hat to more securely develop, deploy, manage and scale AI-powered cloud-native applications. Available on server systems certified by both Red Hat and NVIDIA and with virtualization platforms, such as VMware vSphere, running on those servers, this solution allows customers to deploy their AI workloads consistently across the hybrid cloud, on bare metal or virtualized environments. 

This comprehensive offering derisks deployments and enables seamless operational scaling. It provides self-service experiences for data scientists to rapidly build and share AI models before production rollout. Additionally, the integrated DevOps capabilities in Red Hat OpenShift enable MLOps to speed up continuous delivery of AI-powered applications.

NVIDIA AI Enterprise with Red Hat OpenShift offers organizations a comprehensive choice of AI tools and frameworks that accelerate the speed at which developers can build AI-powered cloud-native applications and high-performance data analytics. This solution helps enable organizations to scale modern cloud-native workloads on their existing infrastructure, while delivering enterprise-class manageability, security features, and availability. 

And for those companies that are evaluating the need for accelerated AI/ML infrastructure on a Kubernetes platform but would like to get hands-on lab experience configuring, optimizing, and orchestrating resources for AI and data science workloads, Red Hat and NVIDIA are making OpenShift available on NVIDIA LaunchPad

This private, GPU-accelerated compute infrastructure from NVIDIA allows customers to experience using OpenShift in a free lab for IT professionals, using the same hardware and software configuration that they can later access or acquire. Having Red Hat OpenShift available on the LaunchPad infrastructure allows our customers to evaluate and explore the Kubernetes and DevOps-powered accelerated AI/ML infrastructure domain without dipping into their budgets. It also provides a preview of what they can expect to see in production. 

We encourage you to experienceRed Hat OpenShift and NVIDIA AI Enterprise on NVIDIA LaunchPad while enjoying the ease of use, automation, and access to the latest GPU accelerators that this infrastructure offers.

Additional Resources

Learn more about running Red Hat OpenShift on NVIDIA BlueField-2 DPUs


About the authors

Yan Fisher is a Global evangelist at Red Hat where he extends his expertise in enterprise computing to emerging areas that Red Hat is exploring. 

Fisher has a deep background in systems design and architecture. He has spent the past 20 years of his career working in the computer and telecommunication industries where he tackled as diverse areas as sales and operations to systems performance and benchmarking. 

Having an eye for innovative approaches, Fisher is closely tracking partners' emerging technology strategies as well as customer perspectives on several nascent topics such as performance-sensitive workloads and accelerators, hardware innovation and alternative architectures, and, exascale and edge computing.  

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