Curated List of MLOps Libraries
20.5k 2026-04-26
EthicalML/awesome-production-machine-learning
A comprehensive curated list of open-source libraries for deploying, monitoring, versioning, and scaling machine learning models in production.
Core Features
Curated collection of MLOps tools
Covers deployment, monitoring, versioning, and scaling
Categorized by MLOps stages (AutoML, Data Pipeline, Feature Store, etc.)
Provides a search toolkit for navigation
Regular updates via GitHub releases and newsletter
Detailed Introduction
This project serves as an essential resource for machine learning engineers and data scientists looking to operationalize their ML models. It meticulously curates a wide array of open-source libraries, categorizing them by critical MLOps stages such as deployment, monitoring, data management, and model orchestration. By centralizing these tools, it simplifies the complex process of bringing ML models from experimentation to robust, scalable production environments, fostering best practices in the MLOps domain.