CLI Reference¶

This document provides comprehensive reference for the FinOps Optimizer command-line interface.

📋 Overview¶

The FinOps Optimizer CLI provides a command-line interface for all major operations including cost analysis, optimization, reporting, and configuration management.

🚀 Quick Start¶

# Initialize configuration
python cli.py init

# Check provider status
python cli.py status

# Analyze costs
python cli.py analyze

# Run optimization
python cli.py optimize

# Generate report
python cli.py report

📚 Command Reference¶

Global Options¶

All commands support these global options:

python cli.py [OPTIONS] COMMAND [ARGS]...

Options: - --config, -c PATH: Path to configuration file - --verbose, -v: Enable verbose logging - --help, -h: Show help message

Example:

python cli.py --config custom_config.yml --verbose analyze

🔧 Configuration Commands¶

`init`¶

Initialize configuration file.

python cli.py init [OPTIONS]

Options: - --output, -o PATH: Output file path (default: finops_config.yml) - --interactive, -i: Interactive configuration setup - --template PATH: Use configuration template

Examples:

# Create default configuration
python cli.py init

# Create configuration with custom path
python cli.py init --output my_config.yml

# Interactive setup
python cli.py init --interactive

Output:

Configuration file created: finops_config.yml
Please edit the file with your cloud provider credentials.

`validate-config`¶

Validate configuration file.

python cli.py validate-config [OPTIONS]

Options: - --config, -c PATH: Configuration file path - --strict: Strict validation mode

Examples:

# Validate default configuration
python cli.py validate-config

# Validate specific configuration
python cli.py validate-config --config custom_config.yml

# Strict validation
python cli.py validate-config --strict

Output:

Configuration validation:
✅ AWS: Valid
✅ Azure: Valid
❌ GCP: Invalid credentials
✅ Oracle: Valid

Overall: 3/4 providers valid

☁️ Provider Commands¶

`status`¶

Check cloud provider status and connectivity.

python cli.py status [OPTIONS]

Options: - --providers LIST: Specific providers to check - --detailed: Show detailed status information - --timeout SECONDS: Connection timeout (default: 30)

Examples:

# Check all providers
python cli.py status

# Check specific providers
python cli.py status --providers aws,azure

# Detailed status
python cli.py status --detailed

Output:

Provider Status:
AWS: ✅ Connected (us-east-1)
Azure: ✅ Connected (subscription: abc123)
GCP: ❌ Disconnected (Invalid credentials)
Oracle: ⚠️ Warning (Limited permissions)

Summary: 2/4 providers connected

`test-credentials`¶

Test cloud provider credentials.

python cli.py test-credentials [OPTIONS]

Options: - --providers LIST: Specific providers to test - --permissions: Test specific permissions - --verbose: Show detailed test results

Examples:

# Test all providers
python cli.py test-credentials

# Test specific providers
python cli.py test-credentials --providers aws,gcp

# Test with permissions
python cli.py test-credentials --permissions

Output:

Credential Testing:
AWS:
  ✅ Access Key: Valid
  ✅ Secret Key: Valid
  ✅ Permissions: Cost Explorer, EC2, CloudWatch
  ✅ Region: us-east-1

Azure:
  ✅ Client ID: Valid
  ✅ Client Secret: Valid
  ✅ Permissions: Cost Management, Virtual Machines
  ✅ Subscription: abc123

GCP:
  ❌ Service Account: Invalid
  ❌ Permissions: Insufficient
  ❌ Project: Not found

💰 Cost Analysis Commands¶

`analyze`¶

Analyze costs across cloud providers.

python cli.py analyze [OPTIONS]

Options: - --days, -d INTEGER: Number of days to analyze (default: 30) - --start-date DATE: Start date (YYYY-MM-DD) - --end-date DATE: End date (YYYY-MM-DD) - --providers LIST: Specific providers to analyze - --output, -o PATH: Output file path - --format FORMAT: Output format (json, csv, yaml)

Examples:

# Analyze last 30 days
python cli.py analyze

# Analyze specific period
python cli.py analyze --start-date 2024-01-01 --end-date 2024-01-31

# Analyze specific providers
python cli.py analyze --providers aws,azure

# Save results to file
python cli.py analyze --output cost_analysis.json --format json

Output:

Cost Analysis Results:
Period: 2024-01-01 to 2024-01-31
Total Cost: $2,450.75

AWS (us-east-1):
  Total Cost: $1,250.50
  Top Services:
    EC2: $750.25
    S3: $350.00
    RDS: $150.25

Azure (subscription: abc123):
  Total Cost: $800.25
  Top Services:
    Virtual Machines: $500.00
    Storage: $200.00
    SQL Database: $100.25

GCP (project: my-project):
  Total Cost: $400.00
  Top Services:
    Compute Engine: $250.00
    Cloud Storage: $100.00
    Cloud SQL: $50.00

Cost Trends:
  Daily Average: $79.06
  Weekly Trend: +5.2%
  Monthly Trend: +12.8%

`cost-breakdown`¶

Get detailed cost breakdown.

python cli.py cost-breakdown [OPTIONS]

Options: - --days, -d INTEGER: Number of days (default: 30) - --group-by FIELD: Group by field (service, region, instance_type) - --filter FILTER: Filter results - --sort-by FIELD: Sort by field - --limit INTEGER: Limit number of results

Examples:

# Get service breakdown
python cli.py cost-breakdown --group-by service

# Get regional breakdown
python cli.py cost-breakdown --group-by region

# Get instance type breakdown
python cli.py cost-breakdown --group-by instance_type

# Filter by cost threshold
python cli.py cost-breakdown --filter "cost > 100"

Output:

Cost Breakdown by Service:
EC2 Instances: $750.25 (30.6%)
  - t3.large: $300.00
  - t3.xlarge: $450.25

S3 Storage: $350.00 (14.3%)
  - Standard: $200.00
  - IA: $150.00

RDS Databases: $150.25 (6.1%)
  - db.t3.micro: $50.00
  - db.t3.small: $100.25

Virtual Machines: $500.00 (20.4%)
  - Standard_D2s_v3: $300.00
  - Standard_D4s_v3: $200.00

⚙️ Optimization Commands¶

`optimize`¶

Run complete optimization pipeline.

python cli.py optimize [OPTIONS]

Options: - --providers LIST: Specific providers to optimize - --types LIST: Optimization types (rightsizing, autoscaling, allocation) - --output, -o PATH: Output file path - --generate-report: Generate optimization report - --save-results: Save results to file

Examples:

# Run complete optimization
python cli.py optimize

# Optimize specific providers
python cli.py optimize --providers aws,azure

# Specific optimization types
python cli.py optimize --types rightsizing,autoscaling

# Save results
python cli.py optimize --output optimization_results.json

Output:

Running Optimization Pipeline...
✅ Cost Analysis: Complete
✅ Rightsizing Analysis: Complete
✅ Autoscaling Analysis: Complete
✅ Cost Allocation: Complete
✅ Forecasting: Complete

Optimization Results:
Total Recommendations: 15
Total Potential Savings: $450.75

Rightsizing Recommendations: 8
  - Downsize t3.xlarge to t3.large: $200.00
  - Terminate unused instances: $150.00
  - Optimize storage classes: $100.75

Autoscaling Recommendations: 5
  - Optimize scaling policies: $50.00
  - Adjust thresholds: $25.00
  - Add predictive scaling: $25.00

Cost Allocation Recommendations: 2
  - Implement tagging strategy: $50.00
  - Set up cost centers: $25.00

Implementation Priority:
1. High Priority (5 recommendations): $300.00
2. Medium Priority (7 recommendations): $125.00
3. Low Priority (3 recommendations): $25.75

Report generated: optimization_report_20240101.html

`rightsizing`¶

Generate rightsizing recommendations.

python cli.py rightsizing [OPTIONS]

Options: - --providers LIST: Specific providers - --threshold FLOAT: Utilization threshold (default: 0.7) - --min-savings FLOAT: Minimum savings threshold (default: 0.1) - --output, -o PATH: Output file path - --detailed: Show detailed analysis

Examples:

# Generate rightsizing recommendations
python cli.py rightsizing

# Custom thresholds
python cli.py rightsizing --threshold 0.8 --min-savings 0.15

# Specific providers
python cli.py rightsizing --providers aws

# Detailed analysis
python cli.py rightsizing --detailed

Output:

Rightsizing Analysis:
Analyzed 25 instances across 2 providers

AWS Rightsizing Opportunities: 8
1. i-123456 (t3.xlarge → t3.large)
   Current: 25% CPU, 30% Memory
   Savings: $200.00/month
   Risk: Low

2. i-789012 (t3.large → t3.medium)
   Current: 35% CPU, 40% Memory
   Savings: $100.00/month
   Risk: Low

Azure Rightsizing Opportunities: 3
1. vm-123 (Standard_D4s_v3 → Standard_D2s_v3)
   Current: 30% CPU, 35% Memory
   Savings: $150.00/month
   Risk: Medium

Total Potential Savings: $450.00/month
Implementation Effort: Low
Risk Level: Low

`autoscaling`¶

Analyze and optimize autoscaling configurations.

python cli.py autoscaling [OPTIONS]

Options: - --providers LIST: Specific providers - --scale-up-threshold FLOAT: Scale up threshold (default: 0.8) - --scale-down-threshold FLOAT: Scale down threshold (default: 0.3) - --min-instances INTEGER: Minimum instances (default: 1) - --max-instances INTEGER: Maximum instances (default: 10) - --output, -o PATH: Output file path

Examples:

# Analyze autoscaling
python cli.py autoscaling

# Custom thresholds
python cli.py autoscaling --scale-up-threshold 0.7 --scale-down-threshold 0.4

# Specific providers
python cli.py autoscaling --providers aws

Output:

Autoscaling Analysis:
Analyzed 10 autoscaling groups

AWS Autoscaling Groups: 5
1. asg-web-app
   Current: 3-8 instances
   Recommended: 2-6 instances
   Savings: $150.00/month
   Reason: Over-provisioned

2. asg-api-service
   Current: 2-5 instances
   Recommended: 2-4 instances
   Savings: $75.00/month
   Reason: Conservative scaling

Azure Scale Sets: 3
1. vmss-frontend
   Current: 2-8 instances
   Recommended: 2-6 instances
   Savings: $100.00/month
   Reason: High idle time

Total Potential Savings: $325.00/month

📊 Forecasting Commands¶

`forecast`¶

Generate cost forecasts.

python cli.py forecast [OPTIONS]

Options: - --days, -d INTEGER: Days to forecast (default: 30) - --include-recommendations: Include optimization impact - --confidence-level FLOAT: Confidence level (default: 0.95) - --output, -o PATH: Output file path - --format FORMAT: Output format (json, csv, html)

Examples:

# Generate 30-day forecast
python cli.py forecast

# Generate 90-day forecast
python cli.py forecast --days 90

# Include optimization impact
python cli.py forecast --include-recommendations

# Custom confidence level
python cli.py forecast --confidence-level 0.9

Output:

Cost Forecast (30 days):
Base Forecast: $2,750.00
Confidence Interval: $2,500.00 - $3,000.00

Provider Breakdown:
AWS: $1,375.00 (+10.0%)
Azure: $880.00 (+10.0%)
GCP: $440.00 (+10.0%)

Optimization Impact:
Base Forecast: $2,750.00
Optimized Forecast: $2,300.00
Potential Savings: $450.00 (16.4%)

Trend Analysis:
- Daily Trend: +0.33%
- Weekly Trend: +2.3%
- Monthly Trend: +10.0%
- Seasonality: Detected

Forecast Factors:
- Historical patterns: Strong
- Seasonal trends: Moderate
- Growth rate: +10% monthly
- Optimization impact: -16.4%

📈 Reporting Commands¶

`report`¶

Generate comprehensive reports.

python cli.py report [OPTIONS]

Options: - --type, -t TYPE: Report type (comprehensive, summary, recommendations) - --format, -f FORMAT: Output format (html, pdf, json) - --output, -o PATH: Output file path - --template PATH: Custom template path - --include-charts: Include interactive charts - --include-recommendations: Include optimization recommendations

Examples:

# Generate comprehensive HTML report
python cli.py report --type comprehensive --format html

# Generate PDF summary
python cli.py report --type summary --format pdf

# Generate JSON recommendations
python cli.py report --type recommendations --format json

# Custom output path
python cli.py report --output my_report.html

Output:

Report Generation:
Type: Comprehensive
Format: HTML
Template: Default

Generating report...
✅ Cost Analysis: Complete
✅ Optimization Recommendations: Complete
✅ Cost Forecast: Complete
✅ Interactive Charts: Complete
✅ Executive Summary: Complete

Report generated: finops_report_20240101_143022.html
File size: 2.5 MB
Charts included: 8
Recommendations: 15

`dashboard`¶

Start web dashboard.

python cli.py dashboard [OPTIONS]

Options: - --host HOST: Host to bind to (default: 0.0.0.0) - --port PORT: Port to bind to (default: 5000) - --debug: Enable debug mode - --config PATH: Configuration file path - --ssl-cert PATH: SSL certificate path - --ssl-key PATH: SSL private key path

Examples:

# Start dashboard
python cli.py dashboard

# Custom host and port
python cli.py dashboard --host 127.0.0.1 --port 8080

# Enable debug mode
python cli.py dashboard --debug

# SSL enabled
python cli.py dashboard --ssl-cert cert.pem --ssl-key key.pem

Output:

Starting FinOps Dashboard...
Configuration loaded: finops_config.yml
Providers initialized: AWS, Azure, GCP
Web server starting...

Dashboard URL: http://0.0.0.0:5000
Default credentials: admin / admin123

Press Ctrl+C to stop the server

🔍 Monitoring Commands¶

`health`¶

Check system health and status.

python cli.py health [OPTIONS]

Options: - --detailed: Show detailed health information - --providers: Check cloud provider health - --system: Check system resources - --output, -o PATH: Output file path

Examples:

# Check overall health
python cli.py health

# Detailed health check
python cli.py health --detailed

# Check specific components
python cli.py health --providers --system

Output:

System Health Check:
Overall Status: ✅ Healthy

Cloud Providers:
AWS: ✅ Connected (us-east-1)
Azure: ✅ Connected (subscription: abc123)
GCP: ⚠️ Warning (High latency)
Oracle: ❌ Disconnected

System Resources:
CPU Usage: 15% ✅
Memory Usage: 45% ✅
Disk Usage: 60% ✅
Network: ✅ Connected

Performance Metrics:
Cache Hit Rate: 85% ✅
Average Response Time: 250ms ✅
Error Rate: 0.1% ✅

Alerts: 0 active

`metrics`¶

Show performance metrics.

python cli.py metrics [OPTIONS]

Options: - --period PERIOD: Time period (1h, 24h, 7d, 30d) - --format FORMAT: Output format (table, json, csv) - --output, -o PATH: Output file path

Examples:

# Show current metrics
python cli.py metrics

# Last 24 hours
python cli.py metrics --period 24h

# JSON format
python cli.py metrics --format json

Output:

Performance Metrics (Last 24 hours):
Requests: 1,250
Successful: 1,245 (99.6%)
Failed: 5 (0.4%)

Response Times:
Average: 250ms
Median: 200ms
95th percentile: 500ms
99th percentile: 800ms

Cache Performance:
Hit Rate: 85%
Miss Rate: 15%
Total Hits: 1,062
Total Misses: 188

Resource Usage:
CPU: 15% average
Memory: 45% average
Disk I/O: 2.5 MB/s average

Errors by Type:
Authentication: 2
Network: 2
Configuration: 1

🔧 Utility Commands¶

`version`¶

Show version information.

python cli.py version

Output:

FinOps Optimizer v2.0.0
Python: 3.9.7
Platform: Linux x86_64
Dependencies:
  - boto3: 1.26.0
  - azure-mgmt-compute: 29.0.0
  - google-cloud-compute: 1.0.0
  - oci: 2.100.0

`info`¶

Show system information.

python cli.py info [OPTIONS]

Options: - --detailed: Show detailed information - --providers: Show provider information - --config: Show configuration information

Examples:

# Basic information
python cli.py info

# Detailed information
python cli.py info --detailed

# Provider information
python cli.py info --providers

Output:

System Information:
Version: 1.0.0
Python: 3.9.7
Platform: Linux x86_64
Architecture: x86_64

Configuration:
Config File: finops_config.yml
Output Directory: ./finops_reports
Log Level: INFO

Cloud Providers:
AWS: Enabled (us-east-1)
Azure: Enabled (subscription: abc123)
GCP: Enabled (project: my-project)
Oracle: Disabled

Performance Settings:
Max Workers: 4
Cache TTL: 3600s
Batch Size: 100

Security Settings:
Encryption: Enabled
Authentication: Enabled
Rate Limiting: 100 req/hour

`cleanup`¶

Clean up temporary files and caches.

python cli.py cleanup [OPTIONS]

Options: - --cache: Clean cache files - --reports: Clean old reports - --logs: Clean log files - --all: Clean all temporary files - --dry-run: Show what would be cleaned

Examples:

# Clean all temporary files
python cli.py cleanup --all

# Clean only cache
python cli.py cleanup --cache

# Dry run
python cli.py cleanup --all --dry-run

Output:

Cleanup Operation:
Cache files: 15 files (2.5 MB)
Old reports: 8 files (15.2 MB)
Log files: 3 files (1.8 MB)

Cleaning up...
✅ Cache files removed: 15
✅ Old reports removed: 8
✅ Log files removed: 3

Total space freed: 19.5 MB

📝 Configuration Examples¶

Basic Configuration¶

# Initialize configuration
python cli.py init

# Edit configuration file
nano finops_config.yml

# Validate configuration
python cli.py validate-config

# Test providers
python cli.py status

Advanced Configuration¶

# Create custom configuration
python cli.py init --output custom_config.yml

# Use custom configuration
python cli.py --config custom_config.yml analyze

# Interactive setup
python cli.py init --interactive

Automation Examples¶

# Daily cost analysis
python cli.py analyze --days 1 --output daily_costs.json

# Weekly optimization
python cli.py optimize --output weekly_optimization.json

# Monthly report
python cli.py report --type comprehensive --format html --output monthly_report.html

# Health check
python cli.py health --output health_status.json

🔧 Troubleshooting¶

Common Issues¶

1. Configuration Errors¶

# Validate configuration
python cli.py validate-config

# Check configuration syntax
python -c "import yaml; yaml.safe_load(open('finops_config.yml'))"

2. Provider Connection Issues¶

# Test provider connections
python cli.py status --detailed

# Test credentials
python cli.py test-credentials

# Check environment variables
env | grep -E "(AWS|AZURE|GCP|ORACLE)"

3. Permission Issues¶

# Check file permissions
ls -la finops_config.yml

# Fix permissions
chmod 600 finops_config.yml

Debug Mode¶

# Enable verbose logging
python cli.py --verbose analyze

# Debug specific command
python cli.py --verbose --debug analyze

Getting Help¶

# Show help for specific command
python cli.py analyze --help

# Show all commands
python cli.py --help

# Show version
python cli.py version

📊 Output Formats¶

JSON Output¶

python cli.py analyze --format json --output results.json

CSV Output¶

python cli.py cost-breakdown --format csv --output breakdown.csv

YAML Output¶

python cli.py status --format yaml --output status.yml

Need more help? Check our Tutorial Guide or open an issue.

CLI Reference¶

📋 Overview¶

🚀 Quick Start¶

📚 Command Reference¶

Global Options¶

🔧 Configuration Commands¶

init¶

validate-config¶

☁️ Provider Commands¶

status¶

test-credentials¶

💰 Cost Analysis Commands¶

analyze¶

cost-breakdown¶

⚙️ Optimization Commands¶

optimize¶

rightsizing¶

autoscaling¶

📊 Forecasting Commands¶

forecast¶

📈 Reporting Commands¶

report¶

dashboard¶

🔍 Monitoring Commands¶

health¶

metrics¶

🔧 Utility Commands¶

version¶

info¶

cleanup¶

📝 Configuration Examples¶

Basic Configuration¶

Advanced Configuration¶

Automation Examples¶

🔧 Troubleshooting¶

Common Issues¶

1. Configuration Errors¶

2. Provider Connection Issues¶

3. Permission Issues¶

Debug Mode¶

Getting Help¶

📊 Output Formats¶

JSON Output¶

CSV Output¶

YAML Output¶

`init`¶

`validate-config`¶

`status`¶

`test-credentials`¶

`analyze`¶

`cost-breakdown`¶

`optimize`¶

`rightsizing`¶

`autoscaling`¶

`forecast`¶

`report`¶

`dashboard`¶

`health`¶

`metrics`¶

`version`¶

`info`¶

`cleanup`¶