New release, increased capabilities.
After 6 months since the release of 1.0, Kubeflow releases a new version with increased capabilities.
This new version has focused on improving ML Workflow Productivity, Isolation and Security, and GitOps. Here is a list of the enhanced features:
- Fairing and Kale (Kubeflow Automated pipeLines Engine) for end-to-end workflows.
- Katib hyperparameter tuning:
- New frameworks & algorithms (goptuna with CMA-ES, DARTS, chocolate, hyperopt, skopt).
- Flexible config & tuning options (new python SDK, experiments with undefined goal, new UI, new resume policy).
- Install and operations to support GitOps, using blueprints and kpt primitives.
- Isolation and security: multi-user Kubeflow pipelines, CVE scanning, and support for Google’s Private GKE and Anthos.
- MXNet and XGBoost distributed training operators, simplify training on multiple nodes, and speeds model creation.
- Seldon Core 1.1