AI-powered Azure infrastructure auditing tool built using Python, Azure CLI, and Ollama.
This project scans Azure resources, collects infrastructure data, and uses a local AI model to generate security, architecture, and cost optimization recommendations.
- Resource Groups
- Virtual Machines
- Storage Accounts
- Network Security Groups (NSGs)
- Virtual Networks (VNets)
- Security observations
- Cost optimization suggestions
- Architecture review
- Best-practice recommendations
- Risk assessment
- Markdown audit reports
- Infrastructure summary
- AI-generated recommendations
Azure Subscription
↓
Azure CLI
↓
Python Automation
↓
Ollama Local AI (Qwen2.5)
↓
Azure Audit Report
- Python
- Azure CLI
- Ollama
- Qwen2.5 Local LLM
- Git
- GitHub
- Linux (Ubuntu)
azure-ai-auditor/
├── main.py
├── requirements.txt
├── README.md
├── .gitignore
├── reports/
│ ├── sample-report.md
│ └── azure-audit-report.md
└── venv/
- Reviews Azure resource configuration
- Highlights missing tags
- Identifies potential security gaps
- Reviews NSG configuration
- Detects underutilized infrastructure
- Highlights unnecessary resources
- Recommends cost-saving opportunities
- Reviews resource organization
- Examines Azure deployment structure
- Suggests best practices
az login --use-device-codepython3 -m venv venv
source venv/bin/activatepip install -r requirements.txtollama run qwen2.5:1.5bpython main.py- Azure infrastructure inventory
- Security observations
- Cost optimization suggestions
- Architecture recommendations
- Markdown audit report
Generated report:
reports/azure-audit-report.md
- Microsoft Azure
- Cloud Security
- Cloud Governance
- Cost Optimization
- Python Automation
- Infrastructure Auditing
- AI Integration
- Linux Administration
- Git & GitHub
Syed Arif Ali - Cloud Engineer
Email: Syedarif1907@gmail.com
LinkedIn: www.linkedin.com/in/syed-arif-a-a13782407
GitHub: github.com/Syed-2050