Implementing best practices: Controlled network environment for Ray clusters in Red Hat OpenShift AI 3.0
The adoption of Ray for scalable AI and ML workloads has skyrocketed. The Ray framework is powerful, but as the official documentation emphasizes, developers or platform providers are responsible for their own security.With Red Hat OpenShift AI, we are committed to providing a production-ready environment for complex AI workloads, and we recognize that robust security is important. That's why we're enhancing the existing controlled network environment (CNE) for Ray Clusters in OpenShift AI 3.0 and delivering that natively with KubeRay. CNE is an opinionated, platform-enforced policy that strea