Multi-Agent AI Service Platform on Azure

A production-ready, enterprise-grade multi-agent AI system deployed on Microsoft Azure using Infrastructure as Code (Terraform). This platform provides a secure, scalable, and cost-optimized environment for running containerized AI agents with comprehensive networking, data storage, monitoring, and security features.

Architecture diagram showing the complete Azure infrastructure

🌟 Features

Core Infrastructure

• ✅ 5 Containerized AI Agents on Azure Container Instances with auto-scaling
• ✅ Azure Cosmos DB for conversation state storage (400-4000 RU/s autoscale)
• ✅ Azure Cache for Redis for session management (250MB - 4GB configurable)
• ✅ Application Gateway with Web Application Firewall (WAF)
• ✅ Container Registry with geo-replication support
• ✅ Key Vault for secrets management
• ✅ Application Insights + Log Analytics for observability

Security

• 🔒 Private Virtual Network with isolated subnets
• 🔒 Network Security Groups with least-privilege rules
• 🔒 Private endpoints for all backend services
• 🔒 Managed Identities (zero credential management)
• 🔒 TLS 1.3 enforcement
• 🔒 WAF with OWASP 3.2 ruleset
• 🔒 Customer-managed encryption keys

Scalability

• 📈 Independent agent scaling (2-10 instances per agent)
• 📈 Cosmos DB autoscaling (400-4000 RU/s)
• 📈 Redis capacity scaling (Basic to Premium tiers)
• 📈 Application Gateway autoscaling

Observability

• 📊 Application Insights for APM
• 📊 Centralized logging with Log Analytics
• 📊 Custom metrics and dashboards
• 📊 Pre-configured alerts (CPU, memory, errors, latency)
• 📊 Budget alerts at 80%, 95%, and 100% thresholds

🚀 Quick Start

Prerequisites

• Azure Subscription with appropriate permissions
• Terraform 1.5.0 or later (Install)
• Azure CLI 2.40 or later (Install)
• Docker Desktop (for building agent images) (Install)
• Git for version control

One-Command Deployment

# Clone the repository
git clone https://github.com/Remaker-Digital/multi-agent-service-platform.git
cd multi-agent-service-platform/terraform

# Authenticate with Azure
az login
az account set --subscription "YOUR_SUBSCRIPTION_ID"

# Make scripts executable (Unix/Mac/Git Bash)
chmod +x scripts/*.sh

# Deploy to development environment
./scripts/init.sh dev
./scripts/plan.sh dev
./scripts/apply.sh dev

For detailed deployment instructions, see the Deployment Guide.

📁 Project Structure

multi-agent-service-platform/
├── README.md                       # This file
├── LICENSE                         # MIT License
├── CONTRIBUTING.md                 # Contribution guidelines
├── claude.md                       # Project context for AI assistants
│
├── terraform/                      # Infrastructure as Code
│   ├── main.tf                    # Root module
│   ├── variables.tf               # Variable definitions
│   ├── outputs.tf                 # Output values
│   ├── modules/                   # 7 Terraform modules
│   ├── environments/              # Environment configs (dev/staging/prod)
│   ├── scripts/                   # Deployment automation
│   └── docs/                      # Detailed documentation
│
├── agents/                         # Agent applications
│   ├── conversation-agent/        # Conversational AI agent
│   ├── analysis-agent/            # Data analysis agent
│   ├── recommendation-agent/      # Recommendation engine
│   ├── knowledge-agent/           # Knowledge base manager
│   └── orchestration-agent/       # Multi-agent orchestrator
│
├── docker/                         # Docker configurations
│   ├── docker-compose.yml         # Local development setup
│   └── base/                      # Base Docker images
│
├── .github/                        # GitHub configurations
│   └── workflows/                 # CI/CD pipelines
│
└── docs/                          # Additional documentation
    ├── architecture.md            # Architecture details
    ├── setup/                     # Setup guides
    └── images/                    # Diagrams and screenshots

💰 Cost Estimates

Environment	Monthly Cost	Use Case
Development	~$500	Development and testing
Staging	~$2,000	Pre-production validation
Production	~$5,000	Live production workloads

Cost optimization features:

• Environment-specific SKUs (Basic for dev, Premium for prod)
• Autoscaling to match demand
• Budget alerts and monitoring
• Optional geo-replication (production only)

🏗️ Architecture

The platform consists of 7 modular Terraform components:

1. Networking - VNet, subnets, NSGs, private DNS zones
2. Security - Key Vault, managed identities, RBAC
3. Container Registry - ACR with geo-replication
4. Data Layer - Cosmos DB and Redis
5. Observability - Application Insights and Log Analytics
6. Agent Infrastructure - Container instances with autoscaling
7. Gateway - Application Gateway with WAF

For detailed architecture documentation, see Architecture Guide.

🔧 Configuration

Environment Variables

Create a terraform/environments/<env>/terraform.tfvars file:

# Core Configuration
project_name = "multiagent-ai"
environment  = "dev"
location     = "eastus"

# Alert Configuration
alert_email_addresses = ["info@remakerdigital.com"]

# Budget
monthly_budget_amount = 500

# Agent Configuration
agents = {
  agent1 = {
    name        = "conversation-agent"
    description = "Handles conversational interactions"
    port        = 8080
  }
  # Add more agents...
}

See terraform.tfvars.example for all available options.

🐳 Docker Setup

Build and push agent images:

# Build agent image
cd agents/conversation-agent
docker build -t conversation-agent:latest .

# Login to Azure Container Registry
az acr login --name <your-registry-name>

# Tag and push
docker tag conversation-agent:latest <registry>.azurecr.io/conversation-agent:latest
docker push <registry>.azurecr.io/conversation-agent:latest

For local development:

cd docker
docker-compose up

📊 Monitoring

Application Insights

Access Application Insights for real-time monitoring:

APP_INSIGHTS_URL=$(terraform output -raw app_insights_id)
echo "https://portal.azure.com/#resource/$APP_INSIGHTS_URL"

Log Analytics

Query logs using KQL:

az monitor log-analytics query \
  --workspace $(terraform output -raw log_analytics_workspace_id) \
  --analytics-query "ContainerInstanceLog_CL | take 100"

🛡️ Security

• Zero Trust Architecture - No public access to backend services
• Managed Identities - Eliminates credential management
• Private Endpoints - All data services isolated from internet
• WAF Protection - OWASP 3.2 + Bot detection + Rate limiting
• Encryption - TLS 1.3 in transit, customer-managed keys at rest

For security best practices, see Security Guide.

🔄 CI/CD

GitHub Actions workflows are included for:

• Terraform validation and formatting
• Infrastructure deployment (with approvals)
• Container image building and pushing
• Security scanning

See .github/workflows/ for workflow definitions.

📚 Documentation

• Deployment Guide - Step-by-step deployment instructions
• Quick Reference - Common commands
• Files Summary - Complete file inventory
• Architecture Guide - Detailed architecture documentation
• Security Guide - Security best practices

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for details on:

• Code of conduct
• Development setup
• Pull request process
• Coding standards

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with Terraform
• Deployed on Microsoft Azure
• Documentation generated with assistance from Claude AI

📧 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: info@remakerdigital.com

🗺️ Roadmap

• Terraform infrastructure modules
• Environment configurations (dev/staging/production)
• Security hardening with private endpoints
• Comprehensive monitoring and alerting
• Sample AI agent implementations
• Kubernetes alternative (AKS)
• Multi-region deployment support
• Advanced autoscaling policies
• Terraform Cloud integration

⭐ Show Your Support

If you find this project helpful, please consider giving it a star on GitHub!

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