GoogleCloudPlatform/automlops

Build MLOps Pipelines in Minutes

56
/ 100
Established

This tool helps data science teams and MLOps engineers quickly set up and manage continuous integration/continuous delivery (CI/CD) pipelines for machine learning models. You provide your machine learning model code, and it generates the complete infrastructure and automation needed to deploy, monitor, and retrain your models. This means you can get your experimental models into production faster and with less manual effort.

258 stars.

Use this if you are a data scientist or MLOps engineer looking to automate the entire lifecycle of your machine learning models on Google Cloud, from development to deployment and monitoring.

Not ideal if you are working with on-premise infrastructure or require a highly customized, non-standard MLOps setup that isn't compatible with the supported Google Cloud services.

Machine Learning Operations Model Deployment CI/CD for ML Data Science Workflow Cloud Infrastructure Automation
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 20 / 25

How are scores calculated?

Stars

258

Forks

44

Language

Python

License

Apache-2.0

Last pushed

Jan 22, 2026

Commits (30d)

0

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