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An accelerator to help organizations build Trusted Research Environments on Azure.

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Azure Trusted Research Environment

Azure TRE documentation site: https://microsoft.github.io/AzureTRE/

Background

Across the health industry, be it a pharmaceutical company interrogating clinical trial results, or a public health provider analyzing electronic health records, there is the need to enable researchers, analysts, and developers to work with sensitive data sets.

Trusted Research Environments (TREs) enable organisations to provide research teams secure access to these data sets alongside appropriate tooling to ensure researchers can remain efficient and productive despite the security controls in place.

Further information on TREs in general can be found in many places, one good resource is HDR UK's website.

The Azure Trusted Research Environment project is an accelerator to assist Microsoft customers and partners who want to build out Trusted Research environments on Azure. This project enables authorized users to deploy and configure secure workspaces and researcher tooling without a dependency on IT teams.

This project is typically implemented alongside a data platform that provides research ready datasets to TRE workspaces.

TREs are not “one size fits all”, hence although the Azure TRE has a number of out of the box features, the project has been built be extensible, and hence tooling and data platform agnostic.

Core features include:

  • Self-service workspace management for TRE administrators
  • Self-service provisioning of research tooling for research teams
  • Package and repository mirroring - PyPi, R-CRAN, Apt and more.
  • Extensible architecture - build your own service templates as required
  • Microsoft Entra ID integration
  • Airlock - import and export
  • Cost reporting
  • Ready to workspace templates including:
    • Restricted with data exfiltration control
    • Unrestricted for open data
  • Ready to go workspace service templates including:
    • Virtual Desktops: Windows, Linux
    • AzureML (Jupyter, R Studio, VS Code)
    • ML Flow
    • Gitea

Project Status and Support

This project's code base is still under development and breaking changes will happen. Whilst the maintainers will do our best to minimise disruption to existing deployments, this may not always be possible. Stable releases will be published when the project is more mature.

The aim is to bring together learnings from past customer engagements where TREs have been built into a single reference solution. This is a solution accelerator aiming to be a great starting point for a customized TRE solution. You're encouraged to download and customize the solution to meet your requirements

This project does not have a dedicated team of maintainers but relies on you and the community to maintain and enhance the solution. Microsoft will on project-to-project basis continue to extend the solution in collaboration with customers and partners. No guarantees can be offered as to response times on issues, feature requests, or to the long term road map for the project.

It is important before deployment of the solution that the Support Policy is read and understood.

Contributing

This project welcomes contributions and suggestions. 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 [email protected] with any additional questions or comments.

Note: maintainers should refer to the maintainers guide

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.

Repository structure

├── .github
│   ├── ISSUE_TEMPLATE     - Templates for GitHub issues
│   ├── linters            - Linter definitions for workflows
│   └── workflows          - GitHub Actions workflows (CI/CD)
│
├── devops
│   ├── scripts            - DevOps scripts
│   └── terraform          - Terraform specific DevOps files/scripts for bootstrapping
│
├── docs                   - Documentation
│
├── e2e_tests              - pytest-based end-to-end tests
│
├── api_app                - API source code and docs
│
├── resource_processor     - VMSS Porter Runner
│
├── scripts                - Utility scripts
│
└── templates
    ├── core/terraform     - Terraform definitions of Azure TRE core resources
    ├── shared_services    - Terraform definitions of shared services
    ├── workspace_services - Workspace services
    └── workspaces         - Workspace templates

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