Infoblox Universal DDI Resource Counter

⚠️ Early Preview: This tool is currently in early preview and provided without guarantees. Resource counts should be verified independently before making licensing decisions.

A Python tool that discovers and counts DDI Objects and Active IPs across AWS, Azure, and Google Cloud Platform (GCP) for Infoblox Universal DDI licensing assessment.

Features

• Multi-Cloud Support: Discover resources across AWS, Azure, and GCP
• DDI Object Counting: Count VPCs, subnets, DNS zones, and other network infrastructure
• Active IP Tracking: Identify IP addresses assigned to running instances and services
• Flexible Output: Support for JSON, CSV, and TXT output formats
• Parallel Processing: Configurable worker threads for improved performance
• Checkpointing & Resume: Save progress and resume interrupted discoveries (Azure)
• Retry Logic: Automatic retries for failed API calls to ensure consistency
• Modular Design: Clean separation between cloud providers and shared utilities

Quick Start

Prerequisites: Python 3.11+, network access to cloud provider APIs

Installation:

git clone https://github.com/stefanriegel/Infoblox-Universal-DDI-cloud-usage.git
cd Infoblox-Universal-DDI-cloud-usage

# macOS/Linux
./setup_venv.sh

# Windows
.\setup_venv.ps1

# Activate virtual environment
source venv/bin/activate  # macOS/Linux
& venv\Scripts\Activate.ps1  # Windows

Usage:

python main.py aws
python main.py azure --subscription-workers 8
python main.py gcp

Installation

Automated Setup (Recommended)

The setup scripts handle everything automatically:

macOS/Linux:

./setup_venv.sh

Windows:

.\setup_venv.ps1

Windows (Batch file fallback - use if PowerShell execution is restricted):

setup_venv.bat

Note: The PowerShell script is signed but may be blocked on systems with strict execution policies that don't trust self-signed certificates. Use the batch file alternative in such cases.

Manual Setup

Use manual setup when automated scripts cannot execute due to system restrictions or permissions issues.

macOS/Linux:

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

Windows (required when PowerShell/Batch scripts cannot execute):

# Create virtual environment
python -m venv venv
venv\Scripts\activate.bat

# Upgrade pip
python -m pip install --upgrade pip

# Install common dependencies
pip install tqdm pandas

# Install provider-specific dependencies (choose one):
# For AWS only:
pip install -r aws_discovery/requirements.txt

# For Azure only:
pip install -r azure_discovery/requirements.txt

# For GCP only:
pip install -r gcp_discovery/requirements.txt

# For all providers:
pip install -r aws_discovery/requirements.txt
pip install -r azure_discovery/requirements.txt
pip install -r gcp_discovery/requirements.txt

Note: On Windows, you may need to install the Microsoft Visual C++ Redistributable if Azure dependencies fail to install due to cryptography compilation errors.

Configuration

AWS Setup

Environment Variables:

export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"

AWS Profile/SSO:

export AWS_PROFILE="your_profile"
aws sso login --profile your_profile

Required Permissions: EC2ReadOnlyAccess, Route53ReadOnlyAccess

Azure Setup

Azure CLI:

az login --tenant "your-tenant-id"  # Use --tenant for specific tenant
az account set --subscription "your-subscription-id"  # Optional
az account show  # Verify login

Service Principal:

export AZURE_CLIENT_ID="your_client_id"
export AZURE_CLIENT_SECRET="your_client_secret"
export AZURE_TENANT_ID="your_tenant_id"
export AZURE_SUBSCRIPTION_ID="your_subscription_id"

Required Permissions: Reader role for subscription-level read access

Required Permissions (Read-Only):

• Reader - Built-in role for subscription-level read access across all subscriptions
• Network Reader - For network resource discovery across all resource groups (read-only)
• Management Group Reader - For multi-subscription discovery (if using Management Groups)

GCP Setup

gcloud CLI:

gcloud auth login
gcloud auth application-default login
export GOOGLE_CLOUD_PROJECT="your-project-id"

Service Account:

export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account-key.json"
export GOOGLE_CLOUD_PROJECT="your-project-id"

Required Permissions: Compute Instance Viewer, Network Viewer, DNS Reader

Usage

Command Line Interface

python main.py {provider} [options]

Providers:

• aws - Amazon Web Services
• azure - Microsoft Azure
• gcp - Google Cloud Platform

Options:

• --format {json,csv,txt} - Output format (default: txt)
• --workers <number> - Number of parallel workers (default: 8)
• --subscription-workers <number> - Parallel subscriptions for Azure (default: 4)
• --retry-attempts <number> - Retry attempts for failed API calls (default: 3)
• --no-checkpoint - Disable checkpointing and resume
• --resume - Auto-resume from checkpoint without prompt
• --checkpoint-file <path> - Custom checkpoint file path
• --checkpoint-interval <number> - Save checkpoint every N subscriptions (default: 50)
• --full - Save detailed resource data (default: summary only)

Examples

python main.py aws
python main.py azure --subscription-workers 8
python main.py gcp --format json
python main.py azure --resume

Output

Output Files

Generated in the output/ directory:

• {provider}_universal_ddi_estimator_{timestamp}.csv - Minimal columns for sizing sheets
• {provider}_universal_ddi_licensing_{timestamp}.txt - Human-readable summary
• {provider}_universal_ddi_proof_{timestamp}.json - Audit manifest (scope, regions, hashes)
• {provider}_unknown_resources_{timestamp}.json - Only when unknown types exist

Output Structure

The tool generates detailed reports showing breakdowns first, with the key sizing numbers prominently displayed at the end:

Resource Breakdowns:

• DDI Objects breakdown (vpc, subnet, route53-zone, etc.)
• Active IPs breakdown (ec2-instance, load-balancer, etc.)

Key Sizing Numbers (at the end):

• DDI Objects Count - Total DDI objects for licensing
• Active IPs Count - Total active IP addresses

Resource Counting

⚠️ Important: Resource counts are estimates and should be verified independently.

DDI Objects: VPCs, subnets, DNS zones/records, load balancers, network interfaces, etc.

Active IPs: IP addresses assigned to running instances, load balancers, and network services.

Project Structure

├── aws_discovery/          # AWS discovery module
├── azure_discovery/        # Azure discovery module
├── gcp_discovery/          # GCP discovery module
├── licensing/              # Licensing calculation data
├── shared/                 # Shared utilities
├── tests/                  # Unit tests
├── main.py                 # Main CLI entry point
├── setup_venv.sh          # Linux/macOS setup script
├── setup_venv.ps1         # Windows PowerShell setup script
├── setup_venv.bat         # Windows batch file setup script
└── requirements.txt        # Dependencies