Azure Policy Regulatory Compliance controls for Azure Machine Learning
Regulatory Compliance in Azure Policy provides Azure created and managed initiative definitions, known as built-ins, for the compliance domains and security controls related to different compliance standards. This page lists the compliance domains and security controls for Azure Machine Learning. You can assign the built-ins for a security control individually to help make your Azure resources compliant with the specific standard.
The title of each built-in policy definition links to the policy definition in the Azure portal. Use the link in the Policy Version column to view the source on the Azure Policy GitHub repo.
Important
Each control is associated with one or more Azure Policy definitions. These policies might help you assess compliance with the control. However, there often isn't a one-to-one or complete match between a control and one or more policies. As such, Compliant in Azure Policy refers only to the policies themselves. This doesn't ensure that you're fully compliant with all requirements of a control. In addition, the compliance standard includes controls that aren't addressed by any Azure Policy definitions at this time. Therefore, compliance in Azure Policy is only a partial view of your overall compliance status. The associations between controls and Azure Policy Regulatory Compliance definitions for these compliance standards can change over time.
Azure Security Benchmark
The Azure Security Benchmark provides recommendations on how you can secure your cloud solutions on Azure. To see how this service completely maps to the Azure Security Benchmark, see the Azure Security Benchmark mapping files.
To review how the available Azure Policy built-ins for all Azure services map to this compliance standard, see Azure Policy Regulatory Compliance - Azure Security Benchmark.
| Domain | Control ID | Control title | Policy (Azure portal) |
Policy version (GitHub) |
|---|---|---|---|---|
| Network Security | NS-2 | Secure cloud services with network controls | Azure Machine Learning workspaces should use private link | 1.1.0 |
| Data Protection | DP-5 | Use customer-managed key option in data at rest encryption when required | Azure Machine Learning workspaces should be encrypted with a customer-managed key | 1.0.3 |
Next steps
- See the built-ins on the Azure Policy GitHub repo.