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| 1 | +## Microsoft Foundry's role in AI infrastructure governance |
| 2 | + |
| 3 | +When you deploy AI workloads across Azure OpenAI, Azure Machine Learning, and Cognitive Services, you create a distributed infrastructure that spans multiple subscriptions, regions, and resource groups. Without centralized governance, each team manages policies independently, leading to inconsistent security controls, fragmented cost tracking, and compliance gaps that auditors discover only during reviews. Microsoft Foundry addresses this by offering a single governance layer that works with Azure Policy, Microsoft Purview, and Azure Monitor to apply controls automatically across all AI resources. |
| 4 | + |
| 5 | +Microsoft Foundry lets you define governance boundaries at the management group or subscription level and automatically enforce policies across your entire resource hierarchy. Centralized controls for tagging, regional restrictions, and responsible AI ensure every AI deployment is compliant before provisioning, while providing real-time visibility into cost, metadata, and compliance. |
| 6 | + |
| 7 | +With Microsoft Foundry, you can: |
| 8 | +- Define governance policies once and apply them consistently through inheritance across all subscriptions and resources |
| 9 | +- Enforce tagging, regional limits, and responsible AI controls automatically for all AI deployments, regardless of how they’re created |
| 10 | +- Gain continuous, real-time insight into resource usage, costs, and compliance without manual inventory tracking |
| 11 | + |
| 12 | + |
| 13 | +## Policy enforcement for AI workloads |
| 14 | + |
| 15 | + |
| 16 | +Microsoft Foundry extends Azure Policy by providing prebuilt templates designed specifically for governing AI infrastructure. These templates help ensure governance and compliance requirements are enforced automatically before any AI resource is deployed. |
| 17 | +- Common scenarios include mandatory tags for cost center tracking, restricting AI service deployments to approved regions for data residency compliance, and limiting SKU selections to control costs. |
| 18 | +- Foundry also enforces responsible AI configurations, such as content filtering and abuse monitoring, and evaluates all applicable policies whenever an AI engineer attempts a deployment. |
| 19 | + |
| 20 | +Microsoft Foundry also streamlines policy enforcement by preventing noncompliant resources from ever reaching production. This proactive approach reduces manual effort and eliminates the need for later remediation. |
| 21 | +- For example, instead of manually defining a **CostCenter** tagging rule per subscription, you select a prebuilt tagging policy template, specify the required tags, and assign it at the management group level. |
| 22 | +- Any Azure OpenAI deployment missing the **CostCenter** tag fails immediately with a clear error message, avoiding downstream fixes during monthly governance audits. |
| 23 | + |
| 24 | + |
| 25 | +## Resource organization and cost management |
| 26 | + |
| 27 | +Foundry uses Azure's resource hierarchy—management groups, subscriptions, resource groups—to organize AI workloads by business domain, project, or compliance boundary. This hierarchical structure becomes powerful when combined with budget controls and spending limits. You can assign a monthly budget to a resource group containing a specific AI project, configure alerts when spending reaches 80% and 100% of the threshold, and optionally block new deployments once the budget is exhausted. This prevents the scenario described in the introduction, where unmonitored AI experimentation leads to unexpected charges. |
| 28 | + |
| 29 | +At the same time, Foundry integrates cost data with resource tagging, enabling you to generate chargeback reports that show exactly which department, project, or cost center consumed AI resources during a billing period. Organizations using this capability report 25-30% reduction in unplanned AI infrastructure spending because teams gain visibility into their consumption patterns and adjust usage proactively. Your finance team receives automated reports showing AI costs by business unit, while project managers see real-time spending trends in the Foundry dashboard, creating accountability without manual cost tracking. |
| 30 | + |
| 31 | +:::image type="content" source="../media/resource-hierarchy-management-group.png" alt-text="Diagram showing how Microsoft Foundry integrates cost data with resource tagging."::: |
| 32 | + |
| 33 | +## Compliance tracking and audit readiness |
| 34 | + |
| 35 | +Microsoft Foundry maintains detailed audit logs for every governance decision: policy evaluations, resource deployments, configuration changes, and access requests. These logs integrate with Microsoft Purview to provide compliance dashboards aligned with regulatory frameworks like ISO 27001, and SOC 2. When auditors request evidence that your organization enforces data residency requirements, you export a Foundry compliance report showing all AI deployments, their regions, the policies that governed their placement, and any exceptions granted through documented approval workflows. |
| 36 | + |
| 37 | +This automated evidence collection transforms compliance from a quarterly burden into a continuous process. Instead of spending weeks reconstructing resource inventories and policy enforcement records, your compliance officer generates current reports on demand. Organizations using Foundry's compliance features complete regulatory reviews 60% faster because the audit trail exists automatically, validated through policy enforcement rather than self-reported by engineering teams. Building on this foundation, you're ready to explore how to configure specific governance policies that balance innovation velocity with the control requirements your organization demands. |
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| 39 | + |
| 40 | +:::image type="content" source="../media/microsoft-foundry-governance-flow.png" alt-text="Diagram with Microsoft Foundry at the center connecting to four governance pillars."::: |
| 41 | + |
| 42 | +*Microsoft Foundry governance architecture showing integration with Azure Policy, resource hierarchy, cost controls, and Microsoft Purview* |
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| 44 | + |
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