udpate azure ai to microsoft foundry

Author: riswinto

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/includes/azure-security-governance-ai-workloads.md

@@ -5,11 +5,11 @@ AI workloads rely on more than one service for security, governance, and access
 AI workloads in Azure benefit from a connected ecosystem of security and governance tools:
 
 - **Microsoft Defender for Cloud** provides posture management and workload protection. It identifies configuration gaps, applies policies, and detects threats across the services that support AI applications.
-- **Azure AI Foundry** introduces model-level guardrails and observability. It lets you apply controls like **Prompt Shields** and **Content Safety**, then track usage, prompt activity, and system behavior to maintain safe model operations.
+- **Microsoft Foundry** introduces model-level guardrails and observability. It lets you apply controls like **Prompt Shields** and **Content Safety**, then track usage, prompt activity, and system behavior to maintain safe model operations.
 - **Microsoft Purview** supports data protection and governance. It discovers and classifies sensitive data used for training, retrieval, or evaluation. This process ensures that regulated or confidential content is properly managed throughout the AI lifecycle.
 - **Microsoft Entra ID** secures identity and access. It provides role-based access control (RBAC), conditional access, and identity protection for users, apps, and services that interact with AI workloads.
 
-Together, these tools not only secure infrastructure and data but also reinforce **responsible AI principles** like transparency and accountability. **Microsoft Purview** provides lineage, classification, and access controls that document how sensitive data is used, while **Azure AI Foundry** adds guardrails and observability that make model operations traceable and reviewable. This combination helps teams demonstrate that model behavior is both governed and auditable.
+Together, these tools not only secure infrastructure and data but also reinforce **responsible AI principles** like transparency and accountability. **Microsoft Purview** provides lineage, classification, and access controls that document how sensitive data is used, while **Microsoft Foundry** adds guardrails and observability that make model operations traceable and reviewable. This combination helps teams demonstrate that model behavior is both governed and auditable.
 
 Each tool serves a distinct purpose, and together they form a comprehensive security framework for AI solutions.
 
@@ -20,11 +20,11 @@ These tools align naturally across the layers of an AI workload:
 - **Microsoft Defender for Cloud** monitors and protects the cloud infrastructure where AI services run.
 - **Microsoft Purview** safeguards the data those services use.
 - **Microsoft Entra ID** controls who and what can access them.
-- **Azure AI Foundry** enforces model-specific protections at the application level.
+- **Microsoft Foundry** enforces model-specific protections at the application level.
 
 When used together, they create a defense-in-depth approach where posture, data, identity, and model behavior are all protected under a unified strategy.
 
-For example, an AI application that uses **Azure OpenAI** for generation and **Azure AI Search** for retrieval might rely on **Microsoft Purview** to govern sensitive content, **Microsoft Entra ID** to enforce role-based access, **Azure AI Foundry** to apply guardrails, and **Microsoft Defender for Cloud** to detect infrastructure threats. This combination ensures that protections remain consistent across every layer, from data to model output.
+For example, an AI application that uses **Azure OpenAI** for generation and **Azure AI Search** for retrieval might rely on **Microsoft Purview** to govern sensitive content, **Microsoft Entra ID** to enforce role-based access, **Microsoft Foundry** to apply guardrails, and **Microsoft Defender for Cloud** to detect infrastructure threats. This combination ensures that protections remain consistent across every layer, from data to model output.
 
 ## Implications for security practice
 

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/includes/introduction.md

@@ -8,7 +8,7 @@ In this module, you learn to:
 
 - Identify the layers that make up AI workloads in Azure
 - Recognize security risks unique to AI, including prompt injection, data leakage, and model misuse
-- Explain how Azure AI Foundry provides guardrails and observability for AI models
+- Explain how Microsoft Foundry provides guardrails and observability for AI models
 - Describe how Microsoft Defender for Cloud, Microsoft Purview, and Microsoft Entra ID support AI security and governance
 
 ## Prerequisites

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/includes/summary.md

@@ -5,15 +5,15 @@ You learned to:
 - Identify the five layers of an AI workload and how data moves through them
 - Recognize three categories of AI-specific security risks
 - Explain how Prompt Shields and Content Safety act as guardrails for model behavior
-- Describe how Microsoft Defender for Cloud, Microsoft Purview, Microsoft Entra ID, and Azure AI Foundry form a connected security and governance framework
+- Describe how Microsoft Defender for Cloud, Microsoft Purview, Microsoft Entra ID, and Microsoft Foundry form a connected security and governance framework
 
 The challenge of applying established cloud security practices to AI workloads required a broader approach to protection. By combining posture management, data governance, model guardrails, and identity protection, Azure delivers a defense-in-depth strategy that secures AI systems across the entire lifecycle.
 
 ## Resources
 
-- [What is Azure AI Foundry?](/azure/ai-foundry/what-is-azure-ai-foundry?azure-portal=true)
+- [What is Microsoft Foundry?](/azure/ai-foundry/what-is-azure-ai-foundry?azure-portal=true)
 - [Enable threat protection for AI services](/azure/defender-for-cloud/ai-threat-protection?azure-portal=true)
-- [Prompt Shields in Azure AI Content Safety](/azure/ai-services/content-safety/concepts/jailbreak-detection?azure-portal=true)
+- [Prompt Shields](/azure/ai-services/content-safety/concepts/jailbreak-detection?azure-portal=true)
 - [Azure AI Content Safety documentation](/azure/ai-services/content-safety?azure-portal=true)
 - [Microsoft Purview documentation](/purview?azure-portal=true)
 - [Microsoft Entra ID documentation](/entra/identity?azure-portal=true)

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/includes/understand-ai-services-azure.md

@@ -8,7 +8,7 @@ AI applications in Azure typically combine five layers of services:
 - **Retrieval services**: Azure AI Search or vector indexes are used to supply context and keep responses grounded in organizational data.
 - **Application layer**: Web apps, APIs, or copilots connect user input to models and return results.
 - **Data layer**: Storage accounts and databases hold prompts, cached responses, logs, and training or evaluation datasets.
-- **Orchestration and management**: Azure AI Foundry provides tools for building, testing, and operationalizing AI solutions.
+- **Orchestration and management**: Microsoft Foundry provides tools for building, testing, and operationalizing AI solutions.
 
 These components resemble other workloads in Azure. What changes is how sensitive data flows through them and how users interact with the system.
 

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/index.yml

@@ -12,13 +12,13 @@ metadata:
 title: Understand how Microsoft Defender for Cloud supports AI security and governance in Azure
 
 summary: |
-  Microsoft Defender for Cloud plays a central role in securing AI workloads across Azure. Learn how Microsoft Defender for Cloud supports AI security across Azure. Explore the layers of an AI workload, the unique risks AI systems introduce, and the guardrails that protect model inputs and outputs. See how Microsoft Purview, Microsoft Entra ID, and Azure AI Foundry work together to support a unified security and governance strategy.
+  Microsoft Defender for Cloud plays a central role in securing AI workloads across Azure. Learn how Microsoft Defender for Cloud supports AI security across Azure. Explore the layers of an AI workload, the unique risks AI systems introduce, and the guardrails that protect model inputs and outputs. See how Microsoft Purview, Microsoft Entra ID, and Microsoft Foundry work together to support a unified security and governance strategy.
 
 abstract: |
   In this module, you learn to:
   - Identify the layers that make up AI workloads in Azure
   - Recognize security risks unique to AI, including prompt injection, data leakage, and model misuse
-  - Explain how Azure AI Foundry provides guardrails and observability for AI models
+  - Explain how Microsoft Foundry provides guardrails and observability for AI models
   - Describe how Microsoft Defender for Cloud, Microsoft Purview, and Microsoft Entra ID work together to secure and govern AI workloads
   - Summarize how these services align to create a unified, defense-in-depth strategy for AI security in Azure
 

learn-pr/wwl-sci/defender-for-cloud-ai-understand-protections/knowledge-check.yml

@@ -70,24 +70,24 @@ quiz:
     - content: "Microsoft Defender for Cloud"
       isCorrect: true
       explanation: "Correct: Microsoft Defender for Cloud provides cloud security posture management (CSPM) and workload protection. It helps engineers assess AI infrastructure, detect threats, and align configurations with best practices."
-    - content: "Azure AI Foundry"
+    - content: "Microsoft Foundry"
       isCorrect: false
-      explanation: "Incorrect: Azure AI Foundry provides guardrails and observability for model operations, not infrastructure posture management."
+      explanation: "Incorrect: Microsoft Foundry provides guardrails and observability for model operations, not infrastructure posture management."
     - content: "Microsoft Purview"
       isCorrect: false
       explanation: "Incorrect: Microsoft Purview focuses on data discovery and classification, not workload posture or threat detection."
 
   - content: "To achieve a complete protection strategy for Contoso's AI assistant, which combination of tools should the engineer use?"
     choices:
-    - content: "Azure AI Foundry and Microsoft Defender for Cloud"
+    - content: "Microsoft Foundry and Microsoft Defender for Cloud"
       isCorrect: false
       explanation: "Incorrect: These tools protect model behavior and infrastructure but not data governance or access."
     - content: "Microsoft Purview and Microsoft Entra ID"
       isCorrect: false
       explanation: "Incorrect: These services address data governance and access control but not workload or model protection."
-    - content: "Azure AI Foundry and Azure AI Search"
+    - content: "Microsoft Foundry and Azure AI Search"
       isCorrect: false
       explanation: "Incorrect: Azure AI Search provides retrieval for contextual responses but not security or governance controls."
-    - content: "Microsoft Purview, Azure AI Foundry, Microsoft Defender for Cloud, and Microsoft Entra ID"
+    - content: "Microsoft Purview, Microsoft Foundry, Microsoft Defender for Cloud, and Microsoft Entra ID"
       isCorrect: true
       explanation: "Correct: Together, these tools provide unified coverage across data governance, model guardrails, workload posture, and identity protection. Microsoft Entra ID enforces access through RBAC and conditional access, while Defender for Cloud extends CSPM to AI workloads."