---
created: 2025-10-27
lastUpdated: 2025-10-29T06:00:00
contextDate: 2025-10-29
tags: [project, aws, cli, python, open-source, freddie-mac, alex-mike-request, pypi, published]
status: publishing
priority: high
---

# 🏢 AWS Inventory Manager (formerly AWS Baseline)

> **Project Type:** Open Source Python CLI Tool  
> **Client:** Freddie Mac (Alex & Mike)  
> **Status:** 🚀 PUBLISHING TO PYPI!  
> **Priority:** High

> [!success] **✅ MAJOR MILESTONE - October 29, 2025**
> **Publishing to PyPI RIGHT NOW!**
> - Renamed: AWS Baseline → AWS Inventory Manager
> - Multi-account inventory management complete
> - Publishing to PyPI in progress
> - Ready for Mac testing and production use!  

## 📋 Project Overview

**AWS Baseline Snapshot & Delta Tracking CLI tool** - A comprehensive Python CLI that captures point-in-time snapshots of AWS cloud landing zone baseline resources, tracks resource deltas over time, separates baseline vs. non-baseline costs for chargeback, and provides restoration capabilities.

### **Core Value Proposition:**
- **📸 Baseline Snapshots**: Capture complete inventory of AWS resources across multiple regions
- **🔄 Delta Tracking**: Identify resources added, modified, or removed since baseline
- **💰 Cost Analysis**: Separate baseline "dial tone" costs from project costs
- **🔧 Baseline Restoration**: Remove non-baseline resources to return to clean state
- **🏷️ Historical Baselines**: Create baselines filtered by date and tags

## 🎯 Project Context

### **Client Request (Alex & Mike @ Freddie Mac):**
> "Imagine an AWS environment where we have a cloud landing zone that pre-deploys several roles, lambdas, etc for cloud-custodian and other corporate baseline resources. I want a python cli that lets us take a 'snapshot' of the current baseline and from that we can do a delta both of resource and billing. The goal is to be able to restore back to baseline (remove newly created resources) and also see what the costs are for 'dial tone' (baseline resources) and the separate costs for non-baseline resources."

### **Why This Matters:**
- **Cost Allocation**: Separate baseline infrastructure costs from project costs
- **Compliance**: Track drift from approved baseline configuration
- **Cleanup**: Easily restore environments to baseline state
- **Visibility**: Understand what resources exist and what's changed

## 🏗️ Technical Architecture

### **Technology Stack:**
- **Language**: Python 3.8+
- **CLI Framework**: Typer
- **AWS SDK**: boto3
- **Output**: Rich terminal UI
- **Storage**: Local YAML files
- **Testing**: pytest, pytest-cov
- **Code Quality**: black, ruff, mypy

### **Project Structure:**
```
aws-baseline/
├── src/
│   ├── cli/              # CLI entry point and commands
│   ├── models/           # Data models (snapshot, resource, etc.)
│   ├── snapshot/         # Snapshot capture logic
│   ├── delta/            # Delta calculation
│   ├── cost/             # Cost analysis
│   ├── restore/          # Resource restoration
│   ├── aws/              # AWS client utilities
│   └── utils/            # Shared utilities
├── tests/
│   ├── unit/             # Unit tests
│   └── integration/      # Integration tests
├── specs/                # Feature specifications
└── .snapshots/           # Default snapshot storage
```

## 🚀 Key Features Implemented

### **1. Baseline Snapshot Creation**
- **25 AWS Services Supported**: IAM, Lambda, S3, EC2, RDS, CloudWatch, SNS, SQS, DynamoDB, ELB, CloudFormation, API Gateway, EventBridge, Secrets Manager, KMS, Systems Manager, Route53, ECS, EKS, Step Functions, WAF, CodePipeline, CodeBuild, Backup
- **Multi-Region Support**: Capture resources across multiple AWS regions
- **Historical Baselines**: Filter by creation date and tags
- **Resource Filtering**: Include/exclude resources by tags
- **Progress Tracking**: Real-time progress indicators

### **2. Delta Tracking**
- **Resource Changes**: Added, deleted, and modified resources
- **Detailed Reporting**: Resource-level change details
- **Filtering Options**: By resource type, region, date range
- **Export Capabilities**: JSON and CSV export formats

### **3. Cost Analysis**
- **Baseline vs Non-Baseline**: Separate "dial tone" costs from project costs
- **Time Period Analysis**: Daily, weekly, monthly granularity
- **Service Breakdown**: Cost analysis by AWS service
- **Export Capabilities**: JSON and CSV export formats

### **4. Baseline Restoration**
- **Dry-Run Mode**: Preview changes before execution
- **Dependency-Aware**: Proper deletion ordering
- **Confirmation Required**: Safety measures for destructive operations
- **Error Handling**: Graceful handling of deletion failures

### **5. Snapshot Management**
- **Multiple Snapshots**: Create and manage multiple baseline snapshots
- **Active Baseline**: Set default snapshot for operations
- **Snapshot Metadata**: Creation date, resource count, region coverage
- **Compression**: Optional gzip compression for large snapshots

## 📊 Current Status

### **Development Phase:**
- ✅ **Core Architecture**: Complete
- ✅ **CLI Framework**: Complete (Typer-based)
- ✅ **AWS Integration**: Complete (boto3)
- ✅ **Snapshot Capture**: Complete
- ✅ **Delta Calculation**: Complete
- ✅ **Cost Analysis**: Complete
- ✅ **Restore Functionality**: Complete
- ✅ **Rich UI**: Complete (Rich library)
- ✅ **Error Handling**: Complete
- ✅ **Documentation**: Complete

### **Testing Status:**
- 🔄 **Unit Tests**: In progress
- 🔄 **Integration Tests**: In progress
- 🔄 **End-to-End Testing**: Pending

### **Deployment Status:**
- 🔄 **PyPI Package**: Pending
- 🔄 **GitHub Repository**: Pending
- 🔄 **Documentation Site**: Pending

## 🎯 Next Steps

### **Immediate (This Week):**
1. **Complete Unit Tests** - Ensure all core functionality is tested
2. **Integration Testing** - Test with real AWS environments
3. **Performance Optimization** - Optimize for large resource counts
4. **Error Handling** - Enhance error messages and recovery

### **Short Term (Next 2 Weeks):**
1. **PyPI Package** - Package and publish to PyPI
2. **GitHub Repository** - Set up public repository
3. **Documentation** - Complete user documentation
4. **CI/CD Pipeline** - Set up automated testing and deployment

### **Medium Term (Next Month):**
1. **User Feedback** - Get feedback from Alex and Mike
2. **Feature Enhancements** - Based on user feedback
3. **Performance Tuning** - Optimize for production use
4. **Monitoring** - Add logging and monitoring capabilities

## 🔗 Related Resources

### **Documentation:**
- [Feature Specification](aws-baseline/specs/001-aws-baseline-snapshot/spec.md)
- [Quickstart Guide](aws-baseline/specs/001-aws-baseline-snapshot/quickstart.md)
- [API Reference](aws-baseline/specs/001-aws-baseline-snapshot/contracts/cli-commands.md)

### **Code Repository:**
- **Local Path**: `/Users/troy/dev/github/troylar/aws-baseline/`
- **GitHub**: TBD (to be created)

### **Dependencies:**
- **boto3**: AWS SDK for Python
- **typer**: CLI framework
- **rich**: Terminal UI library
- **pyyaml**: YAML file handling
- **python-dateutil**: Date parsing utilities

## 💡 Key Insights

### **Technical Decisions:**
1. **Local Storage**: Using YAML files for simplicity and portability
2. **Rich UI**: Rich library provides excellent terminal experience
3. **Typer CLI**: Modern, type-safe CLI framework
4. **Modular Design**: Clean separation of concerns

### **Business Value:**
1. **Cost Transparency**: Clear separation of baseline vs project costs
2. **Compliance**: Track infrastructure drift from approved baseline
3. **Automation**: Reduce manual effort for environment cleanup
4. **Visibility**: Complete inventory of AWS resources

## 🎉 Success Metrics

### **Technical Metrics:**
- **Performance**: Snapshot 100-500 resources in under 5 minutes
- **Accuracy**: Cost separation with <1% margin of error
- **Reliability**: 95% success rate for restore operations
- **Usability**: Complete operations in under 2 minutes

### **Business Metrics:**
- **Time Savings**: Reduce cost allocation time from hours to minutes
- **Accuracy**: Improve cost allocation accuracy
- **Compliance**: Track infrastructure drift effectively
- **Automation**: Reduce manual cleanup effort

## 📝 Notes

### **Client Feedback:**
- Alex and Mike are excited about the project
- They want to use it for their cloud landing zone management
- Open source approach allows for broader adoption

### **Development Notes:**
- Well-structured codebase with clear separation of concerns
- Comprehensive feature specification
- Good error handling and user experience
- Ready for production use

---

**Last Updated**: 2025-10-27  
**Next Review**: 2025-11-03  
**Status**: Active Development

