A lightweight, local Python CLI tool designed to detect orphaned AWS resources and identify hidden infrastructure waste before it compounds into financial debt.
This repository contains the free core-logic preview (Lite Version).
Need full automation? The Enterprise AWS FinOps Auditor includes:
👉 Download the Enterprise Engine Here
The Lite engine runs a local pandas pipeline against exported AWS billing or usage CSVs. It executes multi-vector financial cost-waste calculations to flag:
git clone https://github.com/Ace7-coder/aws-finops-auditor.git
cd aws-finops-auditor
pip install -r requirements.txt
python infrastructure_auditor.py --file my_aws_usage.csv
The engine outputs two files to your local directory:
audit_report.json: Granular JSON output of all flagged resources.executive_summary.md: A high-level markdown summary of total waste identified (in USD) and critical security flags.def calculate_waste(self, df: pd.DataFrame) -> float:
"""Multi-vector financial cost-waste calculations."""
# Identifying idle instances (CPU < 5%) and unattached volumes
waste_mask = (df['cpu_utilization'] < 5.0) | ((df['amount'] > 0) & (df['cpu_utilization'].isna()))
return df.loc[waste_mask, 'amount'].sum() if not df.loc[waste_mask].empty else 0.0
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Python
100.0%
A lightweight, local Python CLI tool designed to detect orphaned AWS resources and identify hidden infrastructure waste before it compounds into financial debt.
This repository contains the free core-logic preview (Lite Version).
Need full automation? The Enterprise AWS FinOps Auditor includes:
👉 Download the Enterprise Engine Here
The Lite engine runs a local pandas pipeline against exported AWS billing or usage CSVs. It executes multi-vector financial cost-waste calculations to flag:
git clone https://github.com/Ace7-coder/aws-finops-auditor.git
cd aws-finops-auditor
pip install -r requirements.txt
python infrastructure_auditor.py --file my_aws_usage.csv
The engine outputs two files to your local directory:
audit_report.json: Granular JSON output of all flagged resources.executive_summary.md: A high-level markdown summary of total waste identified (in USD) and critical security flags.def calculate_waste(self, df: pd.DataFrame) -> float:
"""Multi-vector financial cost-waste calculations."""
# Identifying idle instances (CPU < 5%) and unattached volumes
waste_mask = (df['cpu_utilization'] < 5.0) | ((df['amount'] > 0) & (df['cpu_utilization'].isna()))
return df.loc[waste_mask, 'amount'].sum() if not df.loc[waste_mask].empty else 0.0
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Python
100.0%