Kubeflow
Kubeflow is an open-source project dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable. It serves as a foundation for AI platforms, offering a composable, modular, portable, and scalable reference platform. Kubeflow comprises a suite of Kubernetes-native open-source projects that cover every stage of the AI/ML lifecycle, including data preparation, model training, hyperparameter tuning, and model serving. Key components include Kubeflow Pipelines for workflow orchestration, Kubeflow Notebooks for development environments, Kubeflow Trainer for LLM fine-tuning and distributed training, Katib for AutoML, KServe for model serving, and Kubeflow Model Registry for managing ML models. Kubeflow is a Cloud Native Computing Foundation (CNCF) project.
Kubeflow
Kubeflow is an open-source project dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable. It serves as a foundation for AI platforms, offering a composable, modular, portable, and scalable reference platform. Kubeflow comprises a suite of Kubernetes-native open-source projects that cover every stage of the AI/ML lifecycle, including data preparation, model training, hyperparameter tuning, and model serving. Key components include Kubeflow Pipelines for workflow orchestration, Kubeflow Notebooks for development environments, Kubeflow Trainer for LLM fine-tuning and distributed training, Katib for AutoML, KServe for model serving, and Kubeflow Model Registry for managing ML models. Kubeflow is a Cloud Native Computing Foundation (CNCF) project.