⚠️ Experimental Repository Notice
This repository contains experimental code and configurations provided by Microsoft for demonstration and learning purposes only. It is not intended for production use and should not be deployed in production environments. Use at your own risk and discretion. The content, APIs, and functionality may change or break without notice.
This Azure Developer CLI (azd) template provides a streamlined way to provision and deploy Azure AI Foundry resources for building and running AI agents. It includes infrastructure-as-code definitions and sample application code to help you quickly get started with Azure AI Foundry's agent capabilities, including model deployments, workspace configuration, and supporting services like storage and container hosting.
Features • Getting Started • Guidance
This template, the application code and configuration it contains, has been built to showcase Microsoft Azure specific services and tools. We strongly advise our customers not to make this code part of their production environments without implementing or enabling additional security features.
This project framework provides the following features:
- Azure AI Foundry Project: Complete setup of Azure AI Foundry workspace with project configuration
- Foundry Model Deployments: Automatic deployment of AI models for agent capabilities
- Container-Based Agent Hosting: Azure Container Apps environment for deploying and scaling AI agents
- Azure Container Registry: Secure container image storage and management for agent deployments
- Storage: Azure Storage Account with proper role-based access control for data and file management
- Managed Identity: Built-in Azure Managed Identity for secure, keyless authentication between services
- Infrastructure as Code: Complete Bicep templates for repeatable, version-controlled deployments
graph TB
User[👤 User] --> AIF[AI Agent Runtime]
subgraph "Azure Resource Group"
subgraph "AI Foundry Workspace"
AIF[Azure AI Foundry<br/>Project]
AIS[Azure AI Services Resource]
Models[Model Deployments]
end
subgraph "Container Infrastructure (Optional)"
ACR[Azure Container Registry<br/>Agent Images]
ACAE[Container Apps Environment]
ACA
end
subgraph "Storage & Search (Optional)"
Storage[Azure Storage Account<br/>Data & Files]
Search[Azure AI Search<br/>Knowledge Base]
Bing[Bing Search API<br/>Web Grounding]
end
subgraph "Security & Identity"
MI[Managed Identity<br/>Keyless Auth]
RBAC[Role-Based Access Control]
end
end
%% Connections
ACA --> AIF
ACA --> Models
AIF --> AIS
AIF --> Storage
AIF --> Search
AIF --> Bing
ACA --> ACR
ACA --> MI
MI --> RBAC
%% Styling
classDef primary fill:#0078d4,stroke:#005a9e,stroke-width:2px,color:#fff
classDef secondary fill:#00bcf2,stroke:#0099bc,stroke-width:2px,color:#fff
classDef optional fill:#f2f2f2,stroke:#666,stroke-width:1px,color:#333
classDef external fill:#ffd23f,stroke:#cc9900,stroke-width:2px,color:#333
class AIF,AIS,Models primary
class ACA,ACR,ACAE secondary
class Storage,Search,Bing optional
This architecture shows how the Azure AI Foundry starter template creates a complete environment for AI agent development and deployment, with optional components that can be enabled based on your needs.
🚧 Work in Progress - GitHub Codespaces setup is currently being developed and will be available soon.
🚧 Work in Progress - VS Code Dev Containers configuration is currently being developed and will be available soon.
Note: this repository is not meant to be cloned, but to be consumed as a template in your own project.
- Install azd
- Windows:
winget install microsoft.azd - Linux:
curl -fsSL https://aka.ms/install-azd.sh | bash - MacOS:
brew tap azure/azd && brew install azd
- Windows:
-
Bring down the template code:
azd init --template Azure-Samples/ai-foundry-starter-basic
This will perform a git clone
-
Sign into your Azure account:
azd auth login
-
Add an agent... 🚧 Work in Progress
This template does not use specific models. The model deployments are a parameter of the template. Each model may not be available in all Azure regions. Check for up-to-date region availability of Azure AI Foundry and in particular the Agent Service.
To prevent incurring unnecessary charges, it's important to clean up your Azure resources after completing your work with the application.
-
When to Clean Up:
- After you have finished testing or demonstrating the application.
- If the application is no longer needed or you have transitioned to a different project or environment.
- When you have completed development and are ready to decommission the application.
-
Deleting Resources: To delete all associated resources and shut down the application, execute the following command:
azd down
Please note that this process may take up to 20 minutes to complete.
Pricing varies per region and usage, so it isn't possible to predict exact costs for your usage. The majority of the Azure resources used in this infrastructure are on usage-based pricing tiers.
You can try the Azure pricing calculator for the resources deployed in this template.
azd down.
This template also uses Managed Identity for local development and deployment.
To ensure continued best practices in your own repository, we recommend that anyone creating solutions based on our templates ensure that the Github secret scanning setting is enabled.
You may want to consider additional security measures, such as:
- Enabling Microsoft Defender for Cloud to secure your Azure resources.
- Protecting the Azure Container Apps instance with a firewall and/or Virtual Network.
Important Security Notice
This template, the application code and configuration it contains, has been built to showcase Microsoft Azure specific services and tools. We strongly advise our customers not to make this code part of their production environments without implementing or enabling additional security features.
For a more comprehensive list of best practices and security recommendations for Intelligent Applications, visit our official documentation.
This template creates everything you need to get started with Azure AI Foundry:
| Resource | Description |
|---|---|
| Azure AI Foundry | Provides a collaborative workspace for AI development with access to models, data, and compute resources |
| Azure Container Apps | Hosts and scales the web application with serverless containers |
| Azure Container Registry | Stores and manages container images for secure deployment |
| Storage Account | Provides blob storage for application data and file uploads |
| AI Search Service | Optional - Enables hybrid search capabilities combining semantic and vector search |
| Application Insights | Optional - Provides application performance monitoring, logging, and telemetry for debugging and optimization |
| Log Analytics Workspace | Optional - Collects and analyzes telemetry data for monitoring and troubleshooting |
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