Use Cases and Deployment Scope
We use Red Hat OpenShift as a flexible MLOps platform through OpenDataHub, enabling streamlined model training, tracking, and deployment workflows. It serves as the backbone for our AI Inference Server, allowing us to scale and manage containerized inference endpoints efficiently. Additionally, Red Hat OpenShift hosts our IBM Qiskit development environment via JupyterHub, supporting quantum computing research and prototyping. This setup addresses challenges in deploying reproducible ML pipelines, managing compute resources, and integrating emerging technologies like quantum computing. The scope includes AI/ML development, automated deployment, and hybrid cloud scalability across our research and enterprise infrastructure.
Alternatives Considered
HPE Ezmeral Data Fabric (MapR) and HPE Ezmeral Machine Learning Ops
Other Software Used
Proxmox VE, VMware vSphere, Docker, Azure AI Studio