Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
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README.md

Azure MLOps (v2) solution accelerator

Header

Welcome to the MLOps (v2) solution accelerator repository! This project is intended to serve as the starting point for MLOps implementation in Azure.

MLOps is a set of repeatable, automated, and collaborative workflows with best practices that empower teams of ML professionals to quickly and easily get their machine learning models deployed into production. You can learn more about MLOps here:

Prerequisites

  1. An Azure subscription. If you don't have an Azure subscription, create a free account before you begin.
  2. The Terraform extension for Azure DevOps if you are using Terraform to spin up infrastructure
  3. Git bash, WSL or another shell script editor on your local machine

Project overview

The solution accelerator provides a modular end-to-end approach for MLOps in Azure based on pattern architectures. As each organization is unique, solutions will often need to be customized to fit the organization's needs.

The solution accelerator goals are:

  • Simplicity
  • Modularity
  • Repeatability & Security
  • Collaboration
  • Enterprise readiness

It accomplishes these goals with a template-based approach for end-to-end data science, driving operational efficiency at each stage. You should be able to get up and running with the solution accelerator in a few hours.

👤 Getting started: Azure Machine Learning Pattern Demo

The demo follows the classical machine learning or computer vision pattern with Azure Machine Learning.

Azure Machine Learning - Classical Machine Learning Architecture: AzureML CML

Azure Machine Learning - Computer Vision Architecture: AzureML CV

‼️ Please follow the instructions to execute the demo accordingly: Quickstart ‼️

‼️ Please submit any issues here: Issues ‼️

📐 Pattern Architectures: Key concepts

Link AI Pattern
Pattern AzureML CML Azure Machine Learning - Classical Machine Learning
Pattern AzureML CV Azure Machine Learning - Computer Vision
Pattern AzureML NLP Azure Machine Learning - Natural Language Processing
[TBD] Azure Machine Learning / Azure Databricks - Classical Machine Learning
[TBD] Azure Machine Learning / Azure Databricks - Computer Vision
[TBD] Azure Machine Learning / Azure Databricks - Natural Language Processing
[TBD] Azure Machine Learning - Edge AI

📯 (Coming Soon) One-click deployments

📯 MLOps infrastructure deployment

Name Description Try it out
Outer Loop Default Azure Machine Learning outer infrastructure setup [DEPLOY BUTTON]
[TBD] Default Responsible AI for Classical Machine Learning [DEPLOY BUTTON]
Feature Store FEAST Default Feature Store using FEAST [DEPLOY BUTTON]
Feature Store Feathr Feature Store Pattern using Feathr [DEPLOY BUTTON]

📯 MLOps use case deployment

Name AI Workload Type Services Try it out
classical-ml Classical machine learning Azure Machine Learning [DEPLOY BUTTON]
CV Computer Vision Azure Machine Learning [DEPLOY BUTTON]
[TBD] Natural Language Processing Azure Machine Learning [DEPLOY BUTTON]
[TBD] Classical machine learning Azure Machine Learning, Azure Databricks [DEPLOY BUTTON]
[TBD] Computer Vision Azure Machine Learning, Azure Databricks [DEPLOY BUTTON]
[TBD] Natural Language Processing Azure Machine Learning, Azure Databricks [DEPLOY BUTTON]
[TBD] Edge AI Azure Machine Learning [DEPLOY BUTTON]

Contributing

This project welcomes contributions and suggestions. To learn more visit the contributing section, see CONTRIBUTING.md for details.

Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.