terracost 0.1.1

A tool for estimating Terraform infrastructure costs with uncertainty analysis

TerraCost

Multi-cloud Terraform cost estimation and AI-powered optimization tool

TerraCost is a comprehensive solution that scans your Terraform infrastructure files, estimates costs across AWS, Azure, and GCP, and provides AI-powered suggestions to optimize your cloud spending. Available as both a CLI tool and VS Code extension.

✨ Features

🌐 Multi-Cloud Support

• AWS: EC2, S3, Lambda, RDS, and more
• Azure: Virtual Machines, Storage Accounts, App Services
• GCP: Compute Engine, Cloud Storage, Cloud Functions
• Unified Cost Analysis: Compare costs across providers

🤖 AI-Powered Optimization

• Budget Optimization: Fit infrastructure within target budget
• Cost Savings: Conservative, moderate, and aggressive strategies
• Best Value: Optimal cost-performance balance
• Smart Suggestions: LLM-powered infrastructure recommendations

🚀 CI/CD Integration

• Budget Enforcement: Prevent pipeline execution if costs exceed limits
• Cost Monitoring: Track spending trends and growth rates
• Automated Checks: Integrate cost validation into your deployment pipeline

📊 Advanced Analytics

• Cost Uncertainty Analysis: Statistical confidence intervals
• Timeframe Flexibility: 1 month to 2 years projections
• Resource Breakdown: Detailed per-resource cost analysis
• Real-time Updates: Automatic refresh when files change

🛠️ Installation

CLI Tool

# Install from PyPI
pip install terracost

# Or install from source
git clone https://github.com/yourusername/terracost.git
cd terracost
pip install -e .

Requirements: Python 3.8+

VS Code Extension

1. Open VS Code
2. Go to Extensions (Ctrl+Shift+X)
3. Search for "TerraCost"
4. Click Install

🚀 Basic Usage

Cost Estimation

# Estimate costs for your Terraform infrastructure
terracost plan -f infrastructure/

# Specify timeframe (1m, 3m, 6m, 1y, 2y)
terracost plan -f . -t 6m

# Detailed breakdown
terracost plan -f . --verbose

AI-Powered Suggestions

# Get cost savings recommendations
terracost suggest --savings

# Fit infrastructure within budget
terracost suggest --budget 50.0

# Find best value configuration
terracost suggest --bestvalue

CI/CD Budget Enforcement

# Check if costs exceed $2000/month limit
terracost budget --limit 2000 -f infrastructure/

🔧 Configuration

Environment Variables

# Required for AI suggestions
export OPENAI_API_KEY="your-openai-api-key"

# AWS credentials (optional, for enhanced pricing)
export AWS_PROFILE="default"
export AWS_REGION="us-east-1"

# Azure credentials (optional)
export AZURE_CLIENT_ID="your-client-id"
export AZURE_TENANT_ID="your-tenant-id"
export AZURE_CLIENT_SECRET="your-client-secret"

# GCP credentials (optional)
export GOOGLE_APPLICATION_CREDENTIALS="path/to/service-account.json"

📁 Supported Infrastructure

AWS Resources

• Compute: EC2 instances, Lambda functions, ECS services
• Storage: S3 buckets, EBS volumes, RDS databases
• Networking: VPC, Load Balancers, API Gateway
• Security: IAM roles, Security Groups, KMS keys

Azure Resources

• Compute: Virtual Machines, App Services, Functions
• Storage: Storage Accounts, Blob Containers, SQL Databases
• Networking: Virtual Networks, Load Balancers, Application Gateway
• Security: Key Vault, Network Security Groups

GCP Resources

• Compute: Compute Engine, Cloud Functions, App Engine
• Storage: Cloud Storage, Cloud SQL, BigQuery
• Networking: VPC, Load Balancing, Cloud Armor
• Security: IAM, Cloud KMS, Security Command Center

🎯 AI Suggestion Types

Budget Optimization (--budget)

• Analyzes current infrastructure costs
• Suggests modifications to fit within target budget
• Provides risk assessment for each change
• Includes cost estimates for alternatives

Cost Savings (--savings)

• Conservative: Safe changes with minimal risk
• Moderate: Balanced optimization with some risk
• Aggressive: Maximum savings with higher risk
• Detailed explanations for each strategy

Best Value (--bestvalue)

• Optimizes cost-performance ratio
• Considers reliability and scalability
• Balances upfront vs. ongoing costs
• Recommends resource sizing optimizations

🔄 CI/CD Integration

Pipeline Budget Check

# In your CI/CD pipeline
terracost budget --limit 2000 -f infrastructure/
if [ $? -ne 0 ]; then
    echo "❌ Costs exceed budget limit!"
    exit 1
fi

Cost Growth Monitoring

The tool automatically:

• Tracks cost changes between pipeline runs
• Warns about excessive cost growth (>50% by default)
• Provides detailed cost breakdowns
• Saves cost reports for historical analysis

🎨 VS Code Extension Features

Sidebar Panel

• Costs Tab: View infrastructure costs with timeframe selection
• AI Tab: Get optimization suggestions directly in VS Code
• Real-time Updates: Automatic refresh when files change

Inline Cost Display

• Ghost Text: See monthly costs directly in .tf files
• Non-intrusive: Gray text that doesn't interfere with code
• Tooltips: Hover for detailed cost breakdowns

Seamless Integration

• File Watching: Automatically detects .tf file changes
• Context Menus: Right-click for quick cost calculations
• Terminal Integration: Dedicated terminal for TerraCost commands

📊 Example Output

Cost Estimation

📊 Infrastructure Analysis
   📁 Directory: ./infrastructure
   🔧 Total Resources: 15
   [AWS] AWS: 8 resources
   [AZURE] AZURE: 4 resources
   [GCP] GCP: 3 resources

💰 Total Cost: $247.83/month
📈 Cost Uncertainty Analysis:
   📊 68% Confidence: $235.12 - $260.54
   📊 95% Confidence: $222.41 - $273.25
   📊 Volatility: 8.2% monthly variation

AI Suggestions

🤖 AI-Powered Cost Optimization Suggestions

📋 Conservative Strategy (Low Risk):
   💰 Estimated Savings: 15-20%
   🔧 Changes: Instance type optimization, storage tier adjustments
   ⚠️ Risk: Minimal impact on performance

📋 Moderate Strategy (Balanced):
   💰 Estimated Savings: 25-35%
   🔧 Changes: Reserved instances, auto-scaling policies
   ⚠️ Risk: Some performance variability

📋 Aggressive Strategy (High Risk):
   💰 Estimated Savings: 40-50%
   🔧 Changes: Spot instances, aggressive scaling
   ⚠️ Risk: Potential downtime during scaling

🏗️ Architecture

Core Components

• Terraform Parser: Extracts resources from .tf files
• Cost Services: Provider-specific pricing calculations
• AI Service: OpenAI integration for suggestions
• Progress Tracking: Real-time operation monitoring
• CI/CD Service: Pipeline budget enforcement

Supported Providers

• AWS: Boto3 integration for pricing
• Azure: Azure SDK for cost estimation
• GCP: Google Cloud client libraries
• Multi-cloud: Unified cost analysis across providers

🚧 Requirements

CLI Tool

• Python 3.8+
• Terraform files (.tf) in your project
• OpenAI API key (for AI suggestions)
• Cloud provider credentials (optional, for enhanced pricing)

VS Code Extension

• VS Code 1.103.0+
• TerraCost Python package installed
• Python available in PATH
• Terraform files in workspace

🔍 Troubleshooting

Common Issues

No Cost Estimates Displayed

• Verify .tf files are in the specified directory
• Check if Terraform configuration is valid
• Ensure cloud provider credentials are configured

AI Suggestions Not Working

• Verify OPENAI_API_KEY is set
• Check internet connectivity
• Ensure Terraform files contain cloud resources

CI/CD Pipeline Fails

• Check budget limits are reasonable
• Verify cost estimation is working locally
• Review cost growth warnings

Debug Mode

# Enable verbose output
terracost plan -f . --verbose

# Check version
terracost --version

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

Development Setup

git clone https://github.com/yourusername/terracost.git
cd terracost
pip install -e .
npm install  # For VS Code extension

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

• Issues: Report bugs and feature requests on GitHub
• Documentation: Check the Wiki for detailed guides
• Community: Join discussions in the GitHub Discussions

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Made with ❤️ by the TerraCost team

Members:

• Daniël van Zyl
• Shailyn Ramsamy Moodley
• Tevlen Naidoo

TerraCost helps you build cost-effective cloud infrastructure without compromising on performance or reliability.