azure-microsoft-foundry

You can deploy and manage Microsoft Foundry resources by creating, deleting, and configuring projects efficiently. This streamlines cloud operations for AI and data workloads, enabling scalable AI deployment across your Azure subscription.

Configure RBAC and permissions by managing roles and role assignments within your Azure subscription. This ensures secure access control and operations for your Microsoft Foundry projects and underlying cloud resources.

The best way to monitor quotas is by viewing utilization and requesting capacity increases. This optimizes your deployment capacity and ensures your AI models have sufficient resources to scale effectively.

Troubleshoot network issues by accessing logs, session data, and observability connections to identify failures. You can configure VNet, private endpoints, and network isolation for secure, private deployments.

Yes, you need azd, az, and jq installed to execute deployment scripts and process JSON data. These dependencies are required to run the commands for project setup, permissions configuration, and quota management.

Yes, you can set up auto-evaluation, scoring, and ongoing performance tracking for AI models and agents. This provides continuous monitoring to ensure your AI deployments maintain optimal performance.