Kubernetes ML optimizer, Kubeflow, improves data preprocessing with v1.6

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! More often than not, when organizations deploy applications across hybrid and multicloud environments, they use the open-source Kubernetes container orchestration system. Kubernetes itself helps to schedule and manage distributed virtual compute resources and isn't optimized by default for any one particular type of workload, that's where projects like Kubeflow come into play. For organizations looking to run machine learning (ML) in the cloud, a group of companies including Google, Red Hat and Cisco helped to found the Kubeflow open-source project in 2017.