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:
- Automated Multi-Region Scanning: Scans all active AWS regions simultaneously.
- Zero-Setup Credential Handling: Automatically assumes cross-account roles.
- Slack & Teams Integrations: Pushes daily/weekly waste reports directly to your engineering channels.
- 1-Click Remediation: Generates execution scripts to instantly delete orphaned resources.
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:
- Unattached EBS Volumes
- Idle EC2 Instances (CPU < 5%)
- Unassociated Elastic IPs
- Public-facing security anomalies
- Clone the repository:
git clone https://github.com/Ace7-coder/aws-finops-auditor.git cd aws-finops-auditor
- Install dependencies:
pip install -r requirements.txt
- Run the auditor against your usage CSV:
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 0.0Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.