polyaxon/mloperator

Machine learning operator & controller for Kubernetes

46
/ 100
Emerging

This project helps operations engineers and MLOps professionals manage and orchestrate machine learning workloads on Kubernetes. It takes your definitions for ML tasks like training, experiments, distributed training, or notebooks, and then sets up and monitors these processes within your Kubernetes clusters. This is for professionals who are responsible for deploying and managing the infrastructure and lifecycle of machine learning models.

Use this if you are an MLOps engineer or platform team building and managing an end-to-end machine learning platform on Kubernetes and need to standardize and automate your ML workflows.

Not ideal if you are an individual data scientist or researcher primarily focused on model development and experimentation, and not responsible for infrastructure orchestration.

MLOps Kubernetes-orchestration ML-workflow-management distributed-training ML-infrastructure
No Package No Dependents
Maintenance 10 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 11 / 25

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Stars

94

Forks

8

Language

Go

License

Apache-2.0

Last pushed

Jan 16, 2026

Commits (30d)

0

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