Introduction
Learning objectives
- Configure Azure RBAC role assignments to enforce least-privilege access for AI infrastructure components
- Implement system-assigned managed identities to enable keyless authentication between Azure services
- Deploy and configure Azure Cosmos DB for NoSQL as a conversation and metadata store for AI agents
- Evaluate security and governance considerations for production AI workloads on Azure
In this module, you configure the secure infrastructure that Contoso's AI agents require. You assign RBAC roles to grant specific permissions without over-provisioning access, enable managed identities to eliminate connection string management, and deploy Cosmos DB as a scalable conversation store with optimized partition keys and time-to-live policies. By the end of this module, you have hands-on experience building production-ready AI infrastructure that satisfies security auditors and supports global-scale deployments.
More resources
- What is Azure Role-Based Access Control (Azure RBAC)? - Comprehensive overview of RBAC concepts, scope hierarchy, and built-in roles
- What are managed identities for Azure resources? - Introduction to system-assigned and user-assigned managed identities with use case examples
- Welcome to Azure Cosmos DB - Overview of Cosmos DB capabilities, consistency levels, and global distribution features