Kubeflow 1.10 delivers significant enhancements to the machine learning platform, with improved MLOps capabilities, better model serving, enhanced training workflows, and production-ready features for enterprise ML deployments.
Kuberay 1.1 delivers improved Ray cluster management, enhanced autoscaling, better performance, and expanded integration capabilities for distributed computing on Kubernetes.
Kubeflow 1.9 delivers improved ML workflow capabilities, enhanced model serving, better integration, and expanded features for machine learning on Kubernetes.
KAITO streamlines the deployment of large language models on Kubernetes, reducing setup time from days to minutes with automated GPU provisioning and containerized model management.
KubeRay 1.0 provides Kubernetes operator for Ray distributed computing framework, enabling scalable ML workloads and distributed computing on Kubernetes.
Kubeflow 1.8 delivers pipeline improvements, model serving enhancements, and better MLOps integration for machine learning workloads.
Kubeflow 1.7 enhances machine learning capabilities with improved pipelines, better model serving, and enhanced integration for MLOps on Kubernetes.
Kubeflow 1.4 enhances machine learning capabilities with improved pipelines, better model serving, and enhanced integration for MLOps on Kubernetes.
Kubeflow 1.0 marks the first major production-ready release of the machine learning platform for Kubernetes, providing stable APIs and comprehensive tools for ML workflows.