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AWS GenAI for Operations Demos

This repository contains deployable code samples demonstrating how generative AI drives operational excellence across security, cost optimization, resilience, and automation. Each demo provides working implementations that solve real operational challenges - deploy as-is with one click, or adapt to your specific environment and business needs with minimal customization effort.

Available Demos

Demo Name Pillar Description Repository
AI-Powered Security Posture with Prowler + DevOps Agent Security Continuous Prowler scans with Nova-generated remediation playbooks and AWS DevOps Agent incident dispatch, surfaced in a React dashboard security/prowler-security-findings-agent/
AI-Powered Graviton Migration Assessment Cost Optimization Get comprehensive migration assessment with cost analysis and ready-to-use migration artifacts for any codebase cost-optimization/ai-graviton-migration-assessment/
AI-Powered Technical Documentation Generation Operations Automation Generate comprehensive technical documentation with architecture analysis, API docs, and operational guides from any codebase operations-automation/ai-documentation-generation/
AI-Powered Legacy System Automation Operations Automation Automate complex web workflows on legacy systems using cloud-based browser automation with session recording and live monitoring operations-automation/ai-legacy-system-browser-automation/
AI Password Reset Chatbot Operations Automation Conversational password reset with streaming responses, session persistence, and secure Cognito integration for anonymous access operations-automation/ai-password-reset-chatbot/
AWS Services Lifecycle Tracker Operations Automation Automated monitoring and intelligent categorization of AWS service deprecations with real-time dashboard and admin interface operations-automation/aws-services-lifecycle-tracker/
AWS GenAI Cost Optimization Kiro Power Cost Optimization MCP server for static code analysis of AWS GenAI service usage patterns with cost optimization recommendations and Kiro IDE integration cost-optimization/aws-genai-cost-optimization-mcp-server/
AI Lambda Runtime Migration Assistant Operations Automation Discover, assess, and transform Lambda functions running deprecated runtimes using Amazon Bedrock AgentCore and Nova 2 Lite with a React dashboard operations-automation/ai-lambda-runtime-migration/
Natural Language Chaos Engineering with AWS FIS Resilience Transform natural language descriptions into validated AWS FIS experiment templates with current capabilities and intelligent caching resilience/ai-chaos-engineering-with-fis/
Intelligent EKS Incident Investigation with AWS DevOps Agent Observability Automatically detect, investigate, and diagnose EKS infrastructure incidents using AWS DevOps Agent — reducing mean time to resolution from hours to minutes observability/eks-investigation-devops-agent/
Intelligent AWS Site-to-Site VPN Tunnel Investigation with AWS DevOps Agent Observability Automatically detect, investigate, and diagnose Site-to-Site VPN tunnel failures with BGP routing using AWS DevOps Agent — reducing mean time to resolution from hours to minutes observability/aws-site-to-site-vpn-tunnel-investigation-devops-agent/
AI Incident Response Playbook Builder Security Analyze AWS architecture and generate tailored IR playbooks with MITRE ATT&CK mapping, SSM Automation documents, and step-by-step response procedures security/ai-incident-response-playbook-builder/

Roadmap (Coming Soon)

Demo Name Pillar Description Status
AWS Health and Support Case Analyzer Resilience AI-powered analysis of AWS Health events and Support Cases with intelligent categorization and actionable recommendations Planned

Repository Structure

cost-optimization/
├── ai-graviton-migration-assessment/
└── aws-genai-cost-optimization-mcp-server/
operations-automation/
├── ai-documentation-generation/
├── ai-lambda-runtime-migration/
├── ai-legacy-system-browser-automation/
├── ai-password-reset-chatbot/
├── anycompany-it-demo-portal/
└── aws-services-lifecycle-tracker/
observability/
├── eks-investigation-devops-agent/
└── aws-site-to-site-vpn-tunnel-investigation-devops-agent/
resilience/
└── ai-chaos-engineering-with-fis/
security/
└── ai-incident-response-playbook-builder/
└── prowler-security-findings-agent/
shared/
├── scripts/                # Common prerequisite checks
└── utils/                  # Shared region/account utilities

Each demo folder typically contains:

[demo-name]/
├── README.md              # Deployment guide
├── ARCHITECTURE.md        # Technical design
├── deploy-*.ps1           # PowerShell deployment script
├── deploy-*.sh            # Bash deployment script
└── [additional files]     # Demo-specific resources

Getting Started

  1. Browse the available demos in the table above
  2. Click on the repository link for your chosen demo
  3. Follow the demo's README.md for detailed deployment instructions
  4. Deploy using the provided Infrastructure as Code scripts

Prerequisites

  • AWS CLI configured with appropriate permissions
  • AWS CDK (TypeScript or Python) for infrastructure deployment
  • Node.js 20+ (for CDK-based demos)
  • Python 3.10+ (for Python-based demos)

Technology Stack

Core AI Services

  • Amazon Bedrock - Foundation model access and management
  • Amazon Nova Models - Latest generation AI models
  • Amazon Bedrock AgentCore - Multi-step AI workflow orchestration
  • AWS Transform - AI-powered code transformation and documentation generation

Integration Frameworks

  • Model Context Protocol (MCP) Servers - Standardized tool integration
  • Kiro - AI-assisted development workflows

Supporting Services

  • AWS Lambda - Serverless compute
  • Amazon CloudWatch - Monitoring and logging
  • AWS Systems Manager - Configuration management
  • Amazon S3 - Object storage
  • Amazon DynamoDB - NoSQL database

Cost Considerations

Each demo includes detailed cost estimates and optimization recommendations. Typical costs range from $10-50/month depending on usage patterns. See individual demo READMEs for specific cost breakdowns.

For Contributors

This repository includes AI-assisted development guidance via steering files in .kiro/steering/. These files provide project standards, patterns, and anti-patterns to any AI coding assistant.

AI IDE How to use the steering files
Kiro Loads automatically from .kiro/steering/
Cursor Reference .kiro/steering/contributor-guide.md in project context or .cursorrules
GitHub Copilot Reference via .github/copilot-instructions.md
Cline Reference via .clinerules
Claude Code Reference via CLAUDE.md
Other Point your AI assistant to .kiro/steering/contributor-guide.md

Start with the Contributor Guide for all project standards.

Contributing

We welcome community contributions! Please see CONTRIBUTING.md for guidelines.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

👏 Contributors

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Deployable code samples demonstrating how generative AI transforms cloud operations. Deploy as-is with one click, or adapt to your specific environment with minimal customization effort.

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