Secure AI identity infrastructure with Microsoft Entra

  • Learning Path
  • 4 Modules

At a glance

Learn how to secure identities used by AI workloads in Azure. Understand workload identity architecture, configure access to Azure resources, apply Conditional Access policies, and investigate identity risk by using Microsoft Entra.

Prerequisites

  • Experience with Microsoft Entra ID fundamentals
  • Familiarity with Azure role-based access control (RBAC)
  • Basic understanding of Azure subscriptions, resource groups, and resources
  • General understanding of identity and access management concepts

Modules in this learning path

Understand identity architecture for AI workloads

Identity architecture defines who can deploy, invoke, and manage AI workloads in Azure. Microsoft Entra ID governs access across management and data planes, authentication flows establish trust boundaries for AI endpoints, and role scope decisions determine blast radius. Identity types, role assignments, and scope boundaries shape AI security outcomes long before enforcement controls are applied.

Implement access management for Azure resources

Explore how to use built-in Azure roles, managed identities, and RBAC-policy to control access to Azure resources. Identity is the key to secure solutions.

Plan, implement, and administer Conditional Access

Conditional Access gives a fine granularity of control over which users and identities can do specific activities, access which resources, and how to ensure data and systems are safe—including AI agent identities managed through Microsoft Entra Agent ID.

Manage Microsoft Entra Identity Protection

Protecting a user's identity by monitoring their usage and sign-in patterns ensure a secure cloud solution. Explore how to design and implement Microsoft Entra Identity protection.

Start