This playbook provides a comprehensive, step-by-step technical guide for modernizing mainframe applications (IBM z/OS, Unisys ClearPath, Bull GCOS, NEC ACOS) using Azure AI Foundry integrated with GitHub and Azure DevOps. It follows a hybrid approach that preserves existing investments while enabling modern DevOps practices and AI capabilities.
This technical implementation guide serves as a complete resource for IT professionals undertaking mainframe modernization initiatives. Azure AI Foundry functions as the central intelligence layer in the modernization ecosystem, providing:
- 🔍 Deep analysis of complex COBOL, PL/I, Assembler, and Natural code bases
- 🧠 Knowledge extraction from legacy mainframe systems
- 🤖 Intelligent decision-making throughout the modernization process
- 📊 Predictive insights for risk assessment and optimization
- ⚙️ Automation of routine tasks to accelerate development and deployment
The playbook offers detailed implementation guidance for both GitHub and Azure DevOps integration paths, allowing teams to select the platform that best suits their requirements.
- 💻 Mainframe developers and administrators
- 🔄 DevOps engineers and practitioners
- ☁️ Cloud architects and infrastructure teams
- 🛠️ IT implementation teams
- 📈 Technical project managers
This technical playbook is organized as a sequential implementation guide. Each chapter provides detailed steps with:
| Component | Description |
|---|---|
| Objectives | Clear technical objectives |
| Prerequisites | Implementation prerequisites |
| Instructions | Step-by-step implementation instructions |
| Code Examples | Detailed code examples and configuration settings |
| Diagrams | Architecture and workflow diagrams |
| Troubleshooting | Guidance for common issues |
| Validation | Steps to verify successful implementation |
| Next Steps | Guidance to progress through the implementation |
Follow these chapters in sequence to implement your mainframe modernization:
- 🌟 Introduction to Mainframe Modernization with Azure AI Foundry
- 🔍 Discovery and Assessment Phase
- 🏗️ Foundation Setup
- 💻 Development Environment Configuration
- 🤖 AI-Powered Code Analysis
- 🐙 GitHub Integration
- 🔄 Azure DevOps Integration
- 🧠 AI-Powered Transformation
- 📦 CI/CD Implementation
⚠️ AI-Powered Risk Management- 🔄 Hybrid Operations Management
- 🤖 Agent-Based Mainframe Modernization
- 🔍 Understanding Agent-Based Modernization
- 🏗️ Agent Architecture and Roles
- ☁️ Implementing Agent-Based Modernization on Azure
- 🧠 Agent Personas and Prompt Engineering
- 🔄 Integration with GitHub and DevOps
- 📊 Measuring Success and Continuous Improvement
- 🔮 Advanced Topics and Future Directions
- 🌐 Comprehensive Mainframe Modernization with AI and GitHub
- 🖥️ Multi-Platform Mainframe Support (IBM z/OS, Unisys ClearPath, Bull GCOS, NEC ACOS)
- 💻 Programming Language Modernization (COBOL, PL/I, Assembler, Natural)
- ☁️ Cloud Integration Approaches (Azure, AWS, Google Cloud)
- 🧠 Benefits of AI-Driven Modernization
- 🛠️ Implementation Strategy
- 🔄 CI/CD Pipeline Implementations
- 🐙 GitHub Actions Workflows for Different Mainframe Platforms
- 🔄 Azure DevOps Pipeline Examples and Templates
- 🧪 Testing Automation Strategies
- 🚀 Deployment Strategies (Blue-Green, Canary)
- 🔧 Pipeline Templates and Matrix Testing Approaches
- 🔌 MCP-Enabled Agent Architecture
- 🎯 Introduction to Model Context Protocol
- 🖥️ MCP Server Implementation for Mainframe
- 🤝 Multi-Agent Orchestration
- 🚀 Production MCP Deployment
- ☁️ Integration with Azure AI Platform
- 📋 Best Practices and Patterns
- 🔧 Agentic DevOps for Mainframe
- 🏥 Self-Healing CI/CD Pipelines
- 🤖 Autonomous Pipeline Optimization
- 🎯 Intelligent Deployment Strategies
- 👷 SRE Agent Implementation
- 🐙 GitHub Actions Integration
- 📊 Monitoring and Continuous Learning
This repository contains working code examples and templates to accelerate your implementation:
| Resource Type | Description |
|---|---|
| GitHub Integration | Configuration files, workflows, templates, and scripts for GitHub integration |
| Azure DevOps Examples | Pipeline definitions, templates, extensions, and scripts for Azure DevOps |
| AI Foundry Examples | Implementation examples for Azure AI Foundry components |
| Mainframe Examples | Sample code with integration points for various mainframe platforms |
| Hybrid Examples | Examples of hybrid implementations and patterns |
| Agent Framework Examples | Implementation examples for agent-based modernization |
Reusable templates to streamline your implementation:
| Template Type | Description |
|---|---|
| Git Configuration | Templates for proper mainframe code handling |
| GitHub Workflow | GitHub Actions workflow templates |
| Azure Pipeline | Azure Pipelines templates |
| Deployment | Deployment automation templates |
This project is licensed under the MIT License - see the LICENSE file for details.
This Mainframe CI/CD Modernization Playbook was developed by @paulanunes85.