Securing AI and Workload Identities with Entra Agent Identity

As AI agents and automated workloads increasingly access cloud resources, securing these non-human identities has become a critical security frontier. Traditional user-focused security measures are no longer enough to protect against automated identity-based threats. This text-based course guides you through the foundational concepts of Entra Agent Identity, helping you establish robust security boundaries for AI and machine workloads. You will learn to transition from basic identity concepts to advanced protection strategies, ensuring your automated systems operate securely and comply with modern security standards. What you'll learn: - Understand foundational identity concepts and the unique security challenges of non-human AI agents. - Map secure authentication flows specifically tailored for automated workloads and API-driven agents. - Configure Entra Conditional Access policies designed to restrict and monitor agent access. - Apply zero-trust architecture principles to machine-to-machine communications. - Manage lifecycle events and credentials safely to minimize identity-based risk. - Monitor and audit agent activities to detect anomalous behavior and potential compromises. The course starts with essential terminology and core identity concepts before walking you through practical configuration strategies and security policy design. Through written explanations and clear configuration examples, you will build a solid framework for managing secure machine identities. Designed for beginner security administrators, cloud engineers, and developers looking to secure automated workloads, this course requires no prior advanced security experience. Start reading today to build a secure foundation for your organization's AI and automated identities.