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README.md

Three Horizons AI Platform Demo Templates

This directory contains comprehensive demo templates for each horizon of the Three Horizons AI Platform, designed to showcase the capabilities and implementation patterns for each stage of the transformation journey.

Overview

The templates are organized by horizon and follow best practices for Azure, GitHub, and MCP integration. Each template is a complete, executable demo that demonstrates specific capabilities and can be used as a foundation for real-world implementations.

Template Organization

πŸ—οΈ Horizon 1: Foundation Templates

Foundation templates establish the core infrastructure and basic capabilities needed to begin your AI transformation journey.

Purpose: Complete e-commerce application demonstrating microservices architecture
Technologies: React, Node.js, Azure Container Apps, Cosmos DB
Features: Product catalog, shopping cart, order processing, payment integration
Demo Scenario: End-to-end e-commerce platform with modern architecture

Purpose: Starter template for microservices-based applications
Technologies: Configurable (Node.js/Python/C#), Docker, Kubernetes
Features: Service mesh, API gateway, distributed tracing
Demo Scenario: Scalable microservices foundation with observability

Purpose: Deploy foundational Azure infrastructure
Technologies: Bicep, AKS, Azure Monitor, Key Vault
Features: Secure networking, RBAC, monitoring foundation
Demo Scenario: Production-ready infrastructure setup

Purpose: Establish basic continuous integration and deployment
Technologies: GitHub Actions, Azure DevOps, Azure App Service
Features: Automated testing, security scanning, deployment
Demo Scenario: Reliable software delivery pipeline

⚑ Horizon 2: Optimization Templates

Optimization templates introduce advanced capabilities that enhance performance, security, and developer experience.

Purpose: Implement advanced GitOps workflows with ArgoCD
Technologies: ArgoCD, Helm, Kubernetes, Multi-environment management
Features: App-of-apps pattern, canary deployments, promotion workflows
Demo Scenario: Sophisticated deployment automation and management

Purpose: Comprehensive monitoring and observability
Technologies: Prometheus, Grafana, Jaeger, Azure Monitor, Application Insights
Features: Distributed tracing, SLO monitoring, intelligent alerting
Demo Scenario: Full-stack observability with AI-powered insights

Purpose: Advanced security scanning and policy enforcement
Technologies: SAST/DAST tools, OPA Gatekeeper, Falco, Azure Security Center
Features: Vulnerability scanning, policy enforcement, compliance monitoring
Demo Scenario: Zero-trust security with automated compliance

Purpose: Comprehensive performance testing and optimization
Technologies: K6, JMeter, Azure Load Testing, Application Insights
Features: Load testing, stress testing, performance analytics
Demo Scenario: Performance optimization with AI-driven insights

πŸ€– Horizon 3: Innovation Templates

Innovation templates implement cutting-edge AI capabilities and autonomous operations.

Purpose: AI-native application with advanced ML capabilities
Technologies: Azure OpenAI, Semantic Kernel, Vector Search, RAG
Features: Intelligent chatbots, document analysis, multi-modal AI
Demo Scenario: Intelligent application with conversational AI

Purpose: Custom Copilot agent with MCP integration
Technologies: GitHub Copilot, MCP, Azure AI, Custom AI models
Features: Code generation, review automation, intelligent assistance
Demo Scenario: AI-powered development assistant

Purpose: Self-healing, intelligent operations system
Technologies: AI decision engines, Predictive analytics, Azure Automation
Features: Self-healing, predictive maintenance, autonomous scaling
Demo Scenario: Fully autonomous platform operations

Purpose: Comprehensive Model Context Protocol integration
Technologies: MCP servers, AI orchestration, Multi-model support
Features: Tool discovery, context sharing, intelligent routing
Demo Scenario: Seamless AI tool orchestration and connectivity

Getting Started

Prerequisites

Before using these templates, ensure you have:

  1. Azure Subscription with appropriate permissions
  2. GitHub Account with access to three-horizon-ai organization
  3. Red Hat Developer Hub deployed and configured
  4. Required CLI Tools: az, kubectl, oc, git

Template Execution Process

  1. Select Template: Choose a template based on your horizon and use case
  2. Fill Parameters: Provide required configuration parameters
  3. Deploy Infrastructure: Use the generated Bicep/Terraform files
  4. Configure Services: Set up integrations and connections
  5. Run Demo: Execute the demo scenario
  6. Monitor Results: Use monitoring dashboards to observe behavior

Demo Execution Guidelines

Each template includes:

  • Parameter Configuration: Required and optional parameters
  • Infrastructure Files: Bicep/Terraform for Azure resources
  • Application Code: Sample applications and services
  • Documentation: Setup instructions and demo scenarios
  • Monitoring: Dashboards and alerts for observability

Template Features

πŸ” Security

  • Azure Key Vault integration for secrets management
  • RBAC and identity management
  • Security scanning and vulnerability assessment
  • Compliance framework implementation

πŸš€ Performance

  • Auto-scaling capabilities
  • Performance monitoring and optimization
  • Load testing and stress testing
  • Resource optimization recommendations

πŸ”„ DevOps

  • CI/CD pipeline automation
  • GitOps deployment patterns
  • Infrastructure as Code (IaC)
  • Automated testing and quality gates

πŸ€– AI Integration

  • Azure OpenAI and AI Foundry integration
  • Model Context Protocol (MCP) support
  • Intelligent automation and decision making
  • Multi-modal AI capabilities

Configuration Management

Environment Variables

Templates use environment-specific configuration:

  • AZURE_SUBSCRIPTION_ID: Azure subscription
  • AZURE_LOCATION: Deployment region
  • GITHUB_TOKEN: GitHub access token
  • OPENAI_API_KEY: Azure OpenAI key

Secret Management

All sensitive data is managed through:

  • Azure Key Vault for cloud secrets
  • GitHub Secrets for CI/CD
  • Kubernetes Secrets for runtime configuration

Parameter Files

Each template includes parameter files for different environments:

  • parameters-dev.json: Development environment
  • parameters-staging.json: Staging environment
  • parameters-prod.json: Production environment

Best Practices Implementation

Infrastructure as Code

  • Modular Bicep templates with reusable components
  • Parameterized configurations for environment flexibility
  • Secure default configurations with least privilege access
  • Comprehensive resource tagging and organization

Application Development

  • Container-first architecture with Docker
  • Microservices patterns with service mesh
  • API-first design with OpenAPI specifications
  • Event-driven architecture with Azure Service Bus

Monitoring and Observability

  • Structured logging with correlation IDs
  • Distributed tracing across all services
  • Custom metrics and dashboards
  • Intelligent alerting with noise reduction

Security and Compliance

  • Zero-trust network architecture
  • Continuous security scanning
  • Policy-as-code with OPA
  • Audit trails and compliance reporting

Demo Scenarios

Each template includes specific demo scenarios:

H1 Foundation Demos

  • E-commerce Platform: Complete shopping experience
  • Microservices Setup: Service communication and resilience
  • Infrastructure Deployment: Azure resource provisioning
  • CI/CD Pipeline: Code to production automation

H2 Optimization Demos

  • GitOps Workflow: Multi-environment deployment
  • Monitoring Dashboard: Full-stack observability
  • Security Scanning: Vulnerability detection and remediation
  • Performance Testing: Load testing and optimization

H3 Innovation Demos

  • AI Application: Intelligent chatbot with RAG
  • Copilot Agent: AI-powered development assistance
  • Autonomous Operations: Self-healing system demonstration
  • MCP Integration: Multi-tool AI orchestration

Troubleshooting

Common Issues

  1. Authentication Failures: Verify Azure and GitHub credentials
  2. Resource Conflicts: Check for existing resource names
  3. Permission Errors: Ensure proper RBAC assignments
  4. Network Issues: Verify connectivity and firewall rules

Debug Tools

  • Azure CLI for resource inspection
  • kubectl for Kubernetes debugging
  • Application Insights for application issues
  • GitHub Actions logs for CI/CD troubleshooting

Support Resources

Contributing

Template Development

  1. Fork the repository
  2. Create a new template in the appropriate horizon directory
  3. Follow the template structure and naming conventions
  4. Include comprehensive documentation and demo scenarios
  5. Test the template in multiple environments
  6. Submit a pull request with detailed description

Quality Standards

  • All templates must be fully functional
  • Include proper error handling and logging
  • Implement security best practices
  • Provide clear documentation and examples
  • Support multiple deployment environments

Next Steps

  1. Choose Your Horizon: Start with H1 if you're beginning your journey
  2. Select Demo Template: Pick the template that best matches your use case
  3. Follow Setup Guide: Use the detailed setup instructions
  4. Execute Demo: Run the complete demo scenario
  5. Customize: Adapt the template for your specific needs
  6. Scale Up: Move to the next horizon when ready

For detailed instructions on each template, navigate to the specific template directory and follow the README.md file.


The Three Horizons AI Platform demonstrates the evolution from foundational capabilities (H1) through optimization (H2) to innovation (H3), providing a clear path for AI transformation at enterprise scale.