Streamlining AI/ML model delivery with FlexPod AI and Red Hat OpenShift AI

Artificial intelligence (AI) and machine learning (ML) are integral to modern enterprise data centers, driving innovation and investment. However, deploying ML applications in production can be challenging due to unique requirements, complex data pipelines, and the need for collaboration across teams. To overcome these challenges and ensure successful outcomes, adopting machine learning operations (MLOps) is crucial.

ML model delivery involves multiple stages, from data pipeline preparation to model training, validation, and automation. Each stage requires careful orchestration and collaboration among data engineers, ML engineers, and application teams. Furthermore, scaling the environment to accommodate numerous models and applications adds complexity. Gartner estimates that only 54% of AI projects make it from pilot to production, emphasizing the need for a strategic approach to overcome these challenges. 

MLOps, inspired by DevOps principles, offers a holistic approach to streamlining and accelerating ML model delivery. By integrating ML development and operations, MLOps ensures consistency, efficiency, and scalability. It enables continuous retraining, integration, and delivery of models while minimizing technical debt. With MLOps, enterprises can effectively put AI/ML initiatives into operation, delivering sustainable value to the business.

To address the complex demands of AI/ML model delivery, we published FlexPod Datacenter with Red Hat OpenShift AI for MLOps. The solution presented in this design guide brings together Red Hat OpenShift AI and FlexPod® AI, revolutionizing the world of AI/ML and MLOps. Red Hat OpenShift AI, built on the foundation of Red Hat OpenShift, is a flexible and scalable platform for AI/ML and MLOps. It offers a trusted, operationally consistent environment where teams can collaborate, experiment, and deliver ML-enabled applications at scale. 

FlexPod AI leverages FlexPod Datacenter on bare metal, providing a robust infrastructure architecture for AI initiatives. With compute, networking, storage, and GPU options, FlexPod AI enables enterprises to start their AI journey and scale incrementally as their needs evolve. This integration of Red Hat OpenShift AI and FlexPod AI unlocks a world of possibilities for organizations seeking to excel in the realm of MLOps. By combining the strengths of these two remarkable technologies, organizations can achieve unparalleled efficiency, scalability, and agility in their AI and ML initiatives.  

Key features and benefits of the solution include the following.   

• Streamlined model delivery. With Red Hat OpenShift AI at its core, the FlexPod AI reference architecture simplifies the entire ML model delivery process, from development to production deployment. It offers efficient lifecycle management, pipeline automation, and a comprehensive suite of integrated tools and frameworks. Say goodbye to complexities and embrace a streamlined model delivery experience. 

• Model serving at scale. In the FlexPod AI reference architecture, OpenShift AI supports serving multiple models for seamless integration into AI-enabled applications. Leveraging inferencing servers, it enables easy rebuilding, redeployment, and monitoring of models, which means optimal performance even at scale. Embrace the power of scalable model serving with confidence. 

• Compatibility and integration. OpenShift AI seamlessly integrates with leading AI tools and frameworks, including TensorFlow and PyTorch, in the FlexPod AI reference architecture. It also supports the cutting-edge NVIDIA GPUs, accelerating AI workloads and unlocking unparalleled performance for your ML initiatives. 

• Automation and efficiency. The FlexPod AI reference architecture, powered by OpenShift AI, brings advanced MLOps capabilities to the forefront. Automation and continuous retraining mean that models adapt to changing data and maintain accuracy over time. Embrace the power of automation to minimize technical debt and improve overall efficiency, enabling your organization to stay ahead in the AI revolution. 

Unlock the true potential of your AI and ML endeavors with the FlexPod AI reference architecture, seamlessly integrating NetApp storage, Cisco compute, and the NVIDIA GPU with Red Hat OpenShift AI. Embrace streamlined model delivery, collaborative workspaces, scalable model serving, compatibility with leading tools, and automation-driven efficiency. Experience the future of MLOps with FlexPod AI.