Kubeflow
Kubeflow is an open, community driven project to make it easy to deploy and manage an ML stack on Kubernetes
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- model-registry Public
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.
kubeflow/model-registry’s past year of commit activity - mcp-apache-spark-history-server Public
MCP Server for Apache Spark History Server. The bridge between Agentic AI and Apache Spark.
kubeflow/mcp-apache-spark-history-server’s past year of commit activity - spark-operator Public
Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.
kubeflow/spark-operator’s past year of commit activity - mpi-operator Public
Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
kubeflow/mpi-operator’s past year of commit activity
