# ignite25-PREL15-ai-ready-apps-containerize-and-modernize-with-azure **Repository Path**: mirrors_microsoft/ignite25-PREL15-ai-ready-apps-containerize-and-modernize-with-azure ## Basic Information - **Project Name**: ignite25-PREL15-ai-ready-apps-containerize-and-modernize-with-azure - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-11-19 - **Last Updated**: 2026-05-02 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

# [Microsoft Ignite 2025](https://ignite.microsoft.com) ## 🔥 AI-Ready Apps: Containerize and Modernize with Azure Welcome to the Microsoft Ignite 2025 session **PREL15: AI-Ready Apps - Containerize and Modernize with Azure**! ## 🎯 Overview Modernize containerized apps with AI on Azure. This hands-on lab demonstrates how to quickly deploy powerful, flexible AI-powered applications to Azure Container Apps. You'll gain hands-on experience using Azure OpenAI and open-source models on serverless GPUs for cost-efficient AI inferencing, while securing enterprise-grade apps and ensuring compliance. ### What You'll Learn - **Azure Container Apps**: Deploy containerized AI applications with serverless GPUs - **Azure OpenAI Integration**: Build intelligent applications with GPT models using LangChain - **Open-Source AI Models**: Run Ollama and local LLMs on GPU-enabled containers - **Dynamic Sessions**: Execute untrusted code safely in isolated Python environments - **AI Agent Development**: Build autonomous agents with MCP and Goose - **Cost-Efficient AI**: Optimize AI inferencing with GPU-based compute - **Enterprise Security**: Implement secure, compliant AI applications - **Modern Development Practices**: Use Infrastructure as Code (IaC) and containerization ## 📚 Repository Structure ``` ├── docs/ # Comprehensive documentation and MkDocs site ├── lab/ # Hands-on lab materials and instructions │ ├── instructions/ # Step-by-step lab guides │ └── README.md # Lab overview and setup ├── src/ # Source code samples and templates ├── data/ # Sample data files └── img/ # Images and diagrams ``` ## 🚀 Getting Started ### Prerequisites - Azure subscription with appropriate permissions - Azure CLI installed and configured - WSL2 (Windows Subsystem for Linux) or Linux environment - Python 3.12+ - VS Code or preferred IDE ### Quick Start 1. **Clone this repository** ```bash git clone https://github.com/Azure-Samples/ignite25-PREL15-ai-ready-apps-containerize-and-modernize-with-azure.git cd ignite25-PREL15-ai-ready-apps-containerize-and-modernize-with-azure ``` 2. **Review the lab instructions** - See [`lab/README.md`](lab/README.md) for detailed setup and lab guide - Follow the step-by-step instructions in [`lab/instructions/`](lab/instructions/) 3. **Set up your Azure environment** - Ensure you have the required Azure resource providers registered - Configure your Azure CLI authentication ## 🧪 Lab Exercises This lab consists of multiple segments covering: 1. **AI & GPU Playbook**: Understanding AI workloads and GPU acceleration on Azure 2. **Environment Setup**: Configure Azure resources and development environment 3. **Azure OpenAI Deployment**: Create and configure Azure OpenAI resources with GPT models 4. **Ollama & Open-Source Models**: Deploy local LLMs on serverless GPUs 5. **Dynamic Sessions**: Set up Azure Container Apps session pools for code execution 6. **MCP Shell Integration**: Implement Model Context Protocol for AI agents 7. **Goose AI Agent**: Build autonomous coding agents with Goose 8. **LangChain Integration**: Build AI-powered applications combining multiple AI services 9. **Testing & Deployment**: Test and deploy your containerized AI applications See [`lab/README.md`](lab/README.md) for complete lab instructions. ## 📖 Documentation Comprehensive documentation is available in the `/docs` directory and can be viewed as a MkDocs site: ```bash pip install -r requirements.txt mkdocs serve ``` Then navigate to `http://localhost:8000` ## 🔑 Key Technologies - **Azure Container Apps**: Serverless container platform with GPU support and dynamic sessions - **Azure OpenAI Service**: Enterprise-grade AI models (GPT-3.5/GPT-4) - **Ollama**: Run open-source LLMs (Llama, Mistral, Phi) locally and on Azure - **GPU Acceleration**: Serverless GPU compute for cost-efficient AI inferencing - **LangChain**: Framework for building LLM-powered applications - **MCP (Model Context Protocol)**: Connect AI agents to external tools and data - **Goose AI Agent**: Autonomous coding agent for software development - **Python**: Primary programming language - **FastAPI**: Modern web framework for building APIs - **Docker**: Containerization platform ## 📚 Learning Resources | Topic | Link | |:------|:-----| | Azure Container Apps Overview | [https://learn.microsoft.com/azure/container-apps/overview](https://learn.microsoft.com/azure/container-apps/overview) | | Azure OpenAI Service Documentation | [https://learn.microsoft.com/azure/ai-services/openai/overview](https://learn.microsoft.com/azure/ai-services/openai/overview) | | Azure OpenAI Quickstart | [https://learn.microsoft.com/azure/ai-services/openai/quickstart](https://learn.microsoft.com/azure/ai-services/openai/quickstart) | | Ollama Documentation | [https://ollama.com/](https://ollama.com/) | | Azure Container Apps Dynamic Sessions | [https://learn.microsoft.com/azure/container-apps/sessions](https://learn.microsoft.com/azure/container-apps/sessions) | | Code Interpreter in Dynamic Sessions | [https://learn.microsoft.com/azure/container-apps/sessions-code-interpreter](https://learn.microsoft.com/azure/container-apps/sessions-code-interpreter) | | LangChain Python Documentation | [https://python.langchain.com/](https://python.langchain.com/) | | LangChain Azure Integration | [https://python.langchain.com/docs/integrations/platforms/microsoft](https://python.langchain.com/docs/integrations/platforms/microsoft) | | Model Context Protocol (MCP) | [https://modelcontextprotocol.io/](https://modelcontextprotocol.io/) | | Azure Container Apps Security | [https://learn.microsoft.com/azure/container-apps/security](https://learn.microsoft.com/azure/container-apps/security) | | Azure Well-Architected Framework | [https://learn.microsoft.com/azure/well-architected/](https://learn.microsoft.com/azure/well-architected/) | | Learn at Ignite 2025 | [https://aka.ms/LearnAtIgnite](https://aka.ms/LearnAtIgnite) | | Ignite 2025 Next Steps | [https://aka.ms/Ignite25-Next-Steps](https://aka.ms/Ignite25-Next-Steps?ocid=ignite25_nextsteps_cnl) | ## 📋 Additional Resources - [Azure Container Apps Documentation](https://learn.microsoft.com/azure/container-apps/) - [Azure Container Apps Dynamic Sessions](https://learn.microsoft.com/azure/container-apps/sessions) - [Azure OpenAI Service](https://learn.microsoft.com/azure/cognitive-services/openai/) - [LangChain Documentation](https://python.langchain.com/) - [Microsoft Ignite 2025](https://ignite.microsoft.com/) - [Microsoft Learn At Ignite](https://aka.ms/LearnAtIgnite) - [Ignite 2025 Next Steps](https://aka.ms/ignite25-next-steps) ## 🤝 Contributing This project welcomes contributions and suggestions. Please see [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) for details on our code of conduct. ## 📄 License - Code: [MIT License](LICENSE) - Documentation: [Creative Commons Attribution 4.0 License](LICENSE-DOCS) ## 🔒 Security See [SECURITY.md](SECURITY.md) for information about reporting security vulnerabilities. ## 💬 Support For support and questions, please see [SUPPORT.md](SUPPORT.md). --- **Microsoft Ignite 2025** | Session PREL15 *Building the future of AI-ready applications with Azure*