FSx to S3 Intelligent-Tiering Cost Estimation Tool

This tool helps AWS users analyze their FSx for NetApp ONTAP (FSxN) volume usage patterns to estimate potential cost savings when migrating to Amazon S3 Intelligent-Tiering. It collects and analyzes metrics such as storage usage, access patterns, and operations to provide insights for data migration planning.

Features

• 📊 Detailed storage metrics analysis
• 📈 Access pattern analysis for intelligent tiering estimation
• 🔄 Throughput and operations monitoring
• 💰 Cost optimization insights
• 📋 Comprehensive reporting of volume statistics

Prerequisites

• Python 3.6 or higher
• AWS credentials configured with appropriate permissions
• Access to FSx for NetApp ONTAP volumes
• Required permissions for CloudWatch metrics

Installation

1. Clone the repository:

git clone https://github.com/yourusername/fsx-to-s3-int.git
cd fsx-to-s3-int

2. Create and activate a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # On Windows, use: venv\Scripts\activate

3. Install required dependencies:

pip install -r requirements.txt

Configuration

Ensure your AWS credentials are properly configured. You can do this by:

• Using AWS CLI: aws configure --profile your-profile-name
• Setting environment variables
• Using IAM roles if running on AWS infrastructure

Usage

Run the script with the following required parameters:

python fsx_to_s3_int.py --fsx-id fs-xxxxxxxxxxxxxxxxx \
                        --volume-id fsvol-xxxxxxxxxxxxxxxxx \
                        --region your-aws-region \
                        --profile your-aws-profile

Parameters

• --fsx-id: Your FSx File System ID
• --volume-id: Your FSx Volume ID
• --region: AWS Region where your FSx system is located
• --profile: AWS CLI profile to use for authentication

Output

The tool provides detailed metrics including:

• Total storage usage and capacity
• File count and average object size
• Access patterns for different time periods
• Estimated distribution across S3 Intelligent-Tiering access tiers
• Monthly operation counts (read, write, metadata)

Metrics Collected

• Storage metrics (capacity, usage, available space)
• Data access patterns (7-day and 14-day periods)
• Operation counts (read, write, metadata)
• File system statistics
• Throughput measurements

Limitations

• Historical data is limited to 14 days due to CloudWatch metrics retention
• Access pattern analysis is based on available CloudWatch metrics
• Estimates are projections and actual results may vary

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Support

For issues, questions, or contributions, please open an issue in the GitHub repository.