# microsoft/MLOps

MLOps examples

Repository: https://github.com/microsoft/MLOps
Canonical: https://ross.abutalabs.com/products/mlops
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: mlops, azureml
Last push: 2024-08-02T16:21:40+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2679, "days_push": 761, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2116, forks 606 (observed 2026-08-28T04:06:16.189660+00:00)

## What it is
A collection of end-to-end MLOps examples and solutions from Microsoft showing how to operationalize ML workflows with Azure Machine Learning, GitHub, and Azure services like Data Factory and DevOps. It serves as sample code and guidance for bringing ML models to production on Azure.

## Use cases
- learn mlops on azure with examples
- set up a ci/cd pipeline for machine learning models
- operationalize ml model training and deployment workflows
- integrate azure machine learning with azure devops and github
- find end-to-end mlops architecture examples
- version and track ml lifecycle assets in production

## When to choose
- you use Azure Machine Learning and want concrete end-to-end MLOps examples
- you want sample pipelines integrating Azure ML with Azure DevOps, GitHub, or Data Factory
- you are learning MLOps concepts with working Jupyter Notebook examples

## When to avoid
- you need MLOps tooling for AWS, GCP, or on-premises environments
- you want the latest Microsoft MLOps guidance - the repo points to the newer Azure MLOps (v2) accelerator
- you need a production-ready library rather than example code

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, ci-cd, deployment, workflow-automation
- domain: machine-learning, cloud-computing, tutorials
- platform: python, cloud
- tags: mlops, azure-machine-learning, azure-devops, examples, jupyter-notebooks, sample-code, devops, docker

## Member repositories
- microsoft/MLOps (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:16.189660+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:53:20.426664+00:00, confidence not recorded.
  - readme: https://github.com/microsoft/MLOps (fetched 2026-08-28T04:06:16.189660+00:00, sha 613bb90e44f1)
- Data as of 2026-08-30T08:39:29.467469+00:00.