👻 OCI Load Balancer Ghost Hunter

Professional Python script that hunts down forgotten and unused OCI Load Balancers consuming resources but not serving traffic. Intelligent ghost scoring with comprehensive reporting for Oracle Cloud Infrastructure optimization.

🚀 Quick Start Examples

Complete Tenancy Scan
python oci-loadbalancer-ghosthunter.py
Specific Compartments
python oci-loadbalancer-ghosthunter.py --compartments comp-123,comp-456
Custom Output Path
python oci-loadbalancer-ghosthunter.py --output ./reports/
Specific Profile
python oci-loadbalancer-ghosthunter.py --profile PRODUCTION

🎯 Advanced Ghost Detection Features

Sophisticated multi-factor analysis engine that identifies unused OCI Load Balancers with precision scoring and comprehensive reporting capabilities.

🎯

Intelligent Ghost Scoring

Multi-factor analysis with 0-100 scale scoring system evaluating backend sets, listeners, certificates, and lifecycle state for accurate ghost detection.

🏗️

Compartment Intelligence

Smart compartment discovery with automatic tenancy scanning or targeted compartment analysis with proper OCI SDK integration.

⚡

Comprehensive Analysis

Analyzes backend sets, listeners, SSL certificates, health probes, and lifecycle states for both Classic and Network Load Balancers.

📊

Dual Format Reporting

Generates structured CSV for analysis and rich JSON reports with detailed ghost scoring breakdown and actionable recommendations.

🔍

Status Classification

5-tier classification system: Definite Ghost (≥80), Likely Ghost (≥60), Suspicious (≥40), Review Needed (≥20), Active (<20).

🛡️

Backend Health Analysis

Evaluates backend set configurations, health status, and connectivity to identify load balancers with no healthy backends or empty pools.

🔧

OCI SDK Integration

Native OCI Python SDK integration with proper authentication, error handling, and support for multiple OCI profiles and configurations.

📈

Age-Based Scoring

Intelligent age analysis that adds scoring weight to older load balancers (>30 days) with existing ghost characteristics for enhanced accuracy.

🍳 Chef's Usage Examples

Real-world scenarios for hunting down ghost load balancers in your OCI environment like a professional sous chef organizing the kitchen.

1

Complete Tenancy Ghost Hunt

python oci-loadbalancer-ghosthunter.py
--output ./ghost-reports/
--profile DEFAULT

Comprehensive scan across all compartments in your OCI tenancy to identify forgotten load balancers consuming resources but not serving traffic.

2

Targeted Compartment Analysis

python oci-loadbalancer-ghosthunter.py
--compartments ocid1.compartment.oc1..prod,ocid1.compartment.oc1..dev
--output ./targeted-analysis/

Focus your ghost hunting on specific compartments like production and development environments for targeted cost optimization efforts.

3

Multi-Profile Environment Scan

python oci-loadbalancer-ghosthunter.py
--profile PRODUCTION
--output ./prod-ghost-analysis/

Use different OCI profiles to scan multiple tenancies or environments with proper authentication and configuration management.

4

Custom Configuration Analysis

python oci-loadbalancer-ghosthunter.py
--config ~/.oci/custom_config
--compartments ocid1.compartment.oc1..networking

Use custom OCI configuration files and target specific networking compartments for specialized ghost hunting operations.

🔧 Technical Specifications

Professional-grade Python implementation with comprehensive OCI SDK integration and intelligent ghost detection algorithms.

📋Requirements

  • Python 3.6+ with OCI Python SDK installed
  • OCI Authentication configured (config file, instance principal, or resource principal)
  • IAM Permissions for Load Balancer and Identity services (read access)
  • Network Connectivity to OCI management endpoints
  • Required Packages: oci, argparse, csv, json, logging, datetime

⚙️Parameters

--compartments
Comma-separated list of compartment OCIDs to scan (optional)
--output
Output directory path for CSV and JSON reports (default: current directory)
--profile
OCI configuration profile name (default: DEFAULT)
--config
Path to OCI configuration file (optional)

🎯Core Analysis Features

Ghost Scoring Engine

  • • Multi-factor analysis with 0-100 scale scoring
  • • Backend set evaluation (empty pools, offline backends)
  • • Listener configuration analysis
  • • SSL certificate validation for Classic LBs
  • • Lifecycle state assessment
  • • Age-based scoring adjustments

Reporting & Output

  • • Structured CSV for data analysis and BI tools
  • • Rich JSON reports with detailed breakdowns
  • • Ghost status classification (5-tier system)
  • • Backend and listener detail extraction
  • • Shape and bandwidth information
  • • Compartment and tenancy metadata

👻 Ghost Scoring Breakdown

Sophisticated multi-factor algorithm that evaluates load balancer configurations to identify unused resources with precision scoring.

50

Backend Sets Analysis

  • • 50 points: No backend sets configured
  • • 45 points: All backend sets are empty or offline
  • • 25 points: Some backend sets are empty
40

Listener Configuration

  • • 40 points: No listeners configured
  • • 35 points: All listeners lack valid backend sets
  • • 20 points: Some listeners lack backend sets
30

Lifecycle State

  • • 30 points: Non-ACTIVE/CREATING state
  • • 0 points: ACTIVE or CREATING state
15

SSL Certificates

  • • 15 points: HTTPS listeners without SSL certificates (Classic LB only)
  • • 0 points: Proper SSL configuration
10

Age Analysis

  • • 10 points: Created >30 days ago with existing ghost score >40
  • • 0 points: Recently created or low ghost score
5★

Status Classification

  • • ≥80: DEFINITE GHOST
  • • ≥60: LIKELY GHOST
  • • ≥40: SUSPICIOUS
  • • ≥20: REVIEW NEEDED
  • • <20: ACTIVE

📊 Professional Reporting

Comprehensive dual-format reporting designed for both technical analysis and executive presentation with detailed ghost scoring insights.

📈CSV Data Export

Structured data format perfect for analysis, BI tool integration, and automated processing workflows.

Key Data Fields:

  • • Load balancer name, OCID, and type
  • • Ghost score and status classification
  • • Compartment and tenancy information
  • • Backend set and listener counts
  • • Lifecycle state and creation date
  • • Shape and bandwidth details
  • • Detailed ghost scoring reasons

📋JSON Detailed Reports

Rich structured format with comprehensive details, perfect for API integration and detailed analysis workflows.

Enhanced Features:

  • • Complete ghost scoring breakdown
  • • Backend set health analysis
  • • Listener configuration details
  • • SSL certificate information
  • • Nested compartment hierarchy
  • • Timestamp and metadata
  • • Actionable recommendations

👨‍🍳 Chef's Best Practices

Professional tips for effective ghost hunting and OCI load balancer optimization from the CloudCostChefs kitchen.

OCI Authentication Setup

  • Configure OCI CLI with proper authentication (API key, instance principal, or resource principal)
  • Ensure IAM policies grant read access to Load Balancer and Identity services
  • Test connectivity with oci iam compartment list before running the script

Performance Optimization

  • Use specific compartment targeting for faster scans in large tenancies
  • Run during off-peak hours to minimize impact on OCI API rate limits
  • Monitor script output for any authentication or permission issues

Ghost Analysis Strategy

  • Focus on "DEFINITE GHOST" and "LIKELY GHOST" classifications for immediate action
  • Review "SUSPICIOUS" load balancers with application teams before cleanup
  • Use ghost scoring reasons to understand why resources were flagged

Report Integration

  • Import CSV reports into BI tools for trend analysis and executive dashboards
  • Use JSON reports for automated workflows and API integrations
  • Schedule regular scans to track ghost load balancer trends over time

🚀 Start Your Ghost Hunt Today

Download the OCI Load Balancer Ghost Hunter and start identifying unused resources in your Oracle Cloud Infrastructure environment.

Download ScriptView Repository

Part of the CloudCostChefs toolkit • Open source