foundry-vnet-deploy

To deploy Azure AI Foundry inside a private VNet, you can use a guided Bicep parameter interview that provisions AI services, private endpoints, and private DNS zone links for agent connectivity. It generates a .bicepparam file to orchestrate the network-isolated environment.

Yes, you can reuse existing VNets and Azure services during private Azure AI Foundry deployment. The guided parameter interview collects your existing networking details to integrate current infrastructure rather than strictly provisioning new resources.

A private Azure AI Foundry agent setup provisions AI services, AI Search, Storage, CosmosDB, and private DNS zones. It also configures the Foundry project with an Agents capability host and optional hosted-agent developer RBAC.

To handle capability host timeouts during Azure AI Foundry VNet deployment, the process uses a fixed deployment timestamp for safe retries. It includes specific anti-duplication guidance to prevent conflicts when retrying timed-out deployments.

Yes, private Azure AI Foundry deployment supports APIM private DNS resolution through optional Citadel hub spoke network plumbing. This governance feature ensures proper DNS resolution across your network architecture.

The best way to validate a private Azure AI Foundry VNet deployment is using the built-in post-deployment validation checks. These checks run automatically after orchestrating the deterministic Bicep deployment to confirm resource connectivity.