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- Microsoft Foundry uses a top-level resource and child projects to centralize governance while providing isolated development environments for AI teams.
After completing this module, you will be able to:
- Plan a Microsoft Foundry resource and project structure for multiple AI workloads
- Assign Microsoft Foundry roles at appropriate resource and project scopes
- Connect a Foundry project to Azure AI Search
- Configure managed identity access to connected Azure services
- This module covers Azure Monitor fundamentals, including metrics collection, dashboards, alert and processing rules, and KQL-based log queries. Together, these capabilities enable faster root-cause analysis and improve operational reliability.
By the end of this module, you're able to:
- Explain how Azure Monitor and Log Analytics Workspace support infrastructure management
- Configure metrics collection and visualization for Azure resources
- Implement alert rules and processing rules to respond to infrastructure events.
- Query log data to diagnose infrastructure issues
- This module shows how to secure AI agents using Azure RBAC and Microsoft Entra ID managed identities, eliminating stored credentials while enforcing least‑privilege access. It then demonstrates deploying Azure Cosmos DB for NoSQL as a scalable, compliant conversation store optimized for agent workloads.
After completing this module, you'll be able to:
- 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.
- This module explains building resilient, multi-region AI infrastructure using Microsoft Foundry hubs, geo-redundant storage, and Azure Container Registry geo-replication. It shows how coordinated replication and failover protect data, model images, and AI services during regional outages.
By the end of this module, you're able to:
- Explain how Azure Monitor and Log Analytics Workspace support infrastructure management.
- Configure metrics collection and visualization for Azure resources.
- Implement alert rules and processing rules to respond to infrastructure events.
- Query log data to diagnose infrastructure issues.
