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46 repositories
- Kubernetes operator for managing the lifecycle of Apache Spark applications 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
- Kubernetes Operator for MPI-based applications (distributed training, HPC, etc.)
- Machine Learning Pipelines for Kubeflow
- Kubeflow’s superfood for Data Scientists
- Distributed AI Model Training and Fine-Tuning on Kubernetes
- A CLI for Kubeflow.
- Machine Learning Toolkit for Kubernetes
- Automated Machine Learning on Kubernetes
- MCP Server for Apache Spark History Server. The bridge between Agentic AI and Apache Spark.
- Kubeflow blog based on fastpages
- Kubeflow Pipelines on Tekton
- Experimental project plugging Tekton yaml behind KFP API and UI engine