Kubernetes Launches New ML Optimizer Kubeflow to Improve Data Pre-processing 

Kubernetes has announced the latest iteration of their open-source technology and made it generally available with the release of Kubeflow 1.6.

The updated version has security improvements, improved cluster serving runtime management capabilities, and new ways to more simply describe which AI models to deploy and use. Kubeflow is an open-source machine learning platform, according to the business, designed for data scientists who wish to create and test machine learning pipelines as well as machine learning developers who deploy systems across various development environments.

Specific actions are being taken as part of the Kubeflow 1.6 version to assist solve some of the problems that the user survey uncovered. According to the manufacturer, population-based training (PBT) is supported in Kubeflow 1.6, which expedites model iteration and increases the possibility that models will be ready for production.

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