Kubeflow
Kubeflow is an open-source platform designed to simplify the deployment, orchestration, and management of machine learning (ML) workflows on Kubernetes. It provides a set of tools and components for building, training, and deploying ML models at scale, leveraging Kubernetes' container orchestration capabilities. Kubeflow aims to make ML workflows portable, scalable, and reproducible across different environments.
Developers should learn and use Kubeflow when building and deploying ML pipelines in production, especially in cloud-native or hybrid environments where Kubernetes is already in use. It is ideal for scenarios requiring scalable model training, automated ML workflows, and consistent deployment of ML applications, such as in large enterprises or research institutions handling complex data science projects. Kubeflow helps streamline MLOps by integrating with tools like Jupyter notebooks, TensorFlow, and PyTorch.