Skip to content

Commit 8628b9d

Browse files
repo created
Add a new module for running governed AI workloads with Microsoft Foundry, including prerequisites and learning objectives.
1 parent 87322e2 commit 8628b9d

1 file changed

Lines changed: 42 additions & 0 deletions

File tree

  • learn-pr/wwl-azure/run-governed-ai-workloads-microsoft-foundry
Lines changed: 42 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,42 @@
1+
### YamlMime:Module
2+
uid: learn.wwl.run-governed-ai-workloads-microsoft-foundry
3+
metadata:
4+
title: "Run Governed AI Workloads with Microsoft Foundry"
5+
description: "Implement enterprise AI governance with Microsoft Foundry by understanding the governance framework, configuring policy‑driven controls, enforcing quotas and safeguards, and applying hands‑on exercises to balance compliance, security, cost management, and innovation."
6+
ms.date: 02/02/2026
7+
author: wwlpublish
8+
ms.author: bradj
9+
ms.topic: module
10+
ms.service: azure
11+
title: "Run governed AI workloads with Microsoft Foundry"
12+
summary: Implement enterprise AI governance with Microsoft Foundry by understanding the governance framework, configuring policy‑driven controls, enforcing quotas and safeguards, and applying hands‑on exercises to balance compliance, security, cost management, and innovation.
13+
abstract: |
14+
After completing this module, you’ll be able to:
15+
- **Configure secure AI infrastructure access** by assigning least‑privilege RBAC roles and enabling managed identities. 
16+
- **Deploy and optimize Cosmos DB for AI conversations** using scalable partition keys and time‑to‑live (TTL) policies. 
17+
- **Implement production‑ready AI infrastructure** that meets security audit requirements and supports global‑scale deployments.
18+
prerequisites: |
19+
- Familiarity with Azure fundamentals, including subscriptions, resource groups, and Azure Policy.
20+
- Basic knowledge of AI workloads and services used in Microsoft Foundry or Azure AI.
21+
- Understanding of governance concepts such as compliance, data residency, and cost controls.
22+
- Experience navigating the Azure portal and reviewing resource configurations.
23+
iconUrl: /learn/achievements/generic-badge.svg
24+
levels:
25+
- intermediate
26+
roles:
27+
- administrator
28+
- ai-engineer
29+
products:
30+
- azure
31+
- azure-ai-foundry
32+
subjects:
33+
- infrastructure
34+
units:
35+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.introduction
36+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.understand-microsoft-foundry-governance-framework
37+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.configure-governance-policies-controls
38+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.exercise-implement-governance-policies
39+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.knowledge-check
40+
- learn.wwl.run-governed-ai-workloads-microsoft-foundry.summary
41+
badge:
42+
uid: learn.wwl.run-governed-ai-workloads-microsoft-foundry.badge

0 commit comments

Comments
 (0)