caraml-dev/merlin

Kubernetes-friendly ML model management, deployment, and serving.

58
/ 100
Established

Merlin helps machine learning engineers deploy and manage their trained models quickly and efficiently in production. It takes a machine learning model artifact (e.g., a saved scikit-learn model, a TensorFlow model) and makes it available as a scalable, high-performance web service. This allows practitioners to easily move models from development to live use without extensive infrastructure knowledge.

183 stars.

Use this if you are an ML engineer struggling with the complexity and time involved in getting your machine learning models from a trained state into a live, scalable web service for inference.

Not ideal if you are a data scientist primarily focused on model training and experimentation rather than deployment and serving infrastructure.

MLOps model deployment model serving machine learning engineering production ML
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 22 / 25

How are scores calculated?

Stars

183

Forks

49

Language

Go

License

Apache-2.0

Last pushed

Mar 05, 2026

Commits (30d)

0

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