kubeflow

Machine Learning Pipelines for Kubeflow

Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.

Distributed AI Model Training and LLM Fine-Tuning on Kubernetes

Model Registry provides a single pane of glass for ML model developers to index and manage models, versions, and ML artifacts metadata. It fills a gap between model experimentation and production activities. It provides a central interface for all stakeholders in the MLOps lifecycle to collaborate on ML models.

Universal Python SDK to run AI workloads on Kubernetes