microsoft/MLOpsPython resource

Health v2 · maintenance only

Adoption not part of the score

1318 stars · 1159 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Microsoft sample/template repository demonstrating how to build CI/CD pipelines for machine learning projects using Azure Machine Learning and Azure DevOps. It includes pipeline definitions for data sanity tests, model training, evaluation, versioning, and staged deployment as a realtime web service.

Use cases

• set up mlops pipelines for a python ml project on azure
• automate model training and deployment with azure devops
• learn how to operationalize machine learning workflows
• template for ci/cd for scikit-learn models
• build a model retraining pipeline in azure ml
• deploy ml models as realtime web services with staged qa/prod releases

When to choose

• you use Azure Machine Learning and Azure DevOps and want a reference implementation
• you need a starting template for end-to-end ML lifecycle automation on Azure
• you want to learn MLOps practices like model evaluation, versioning, and staged deployment

When to avoid

• you don't use Azure (the pipelines and services are Azure-specific)
• you need a production-grade maintained tool rather than a sample/template
• you use other ML platforms like SageMaker, Vertex AI, or Kubeflow

Facets

learning-resource · maturity maintenance

ci-cd machine-learning deployment testing workflow-automation machine-learning cloud-computing python cloud mlops azure-machine-learning azure-devops reference-architecture sample-template model-deployment retraining-pipeline devops azure docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="microsoft/MLOpsPython")