AI in the Marshall Islands Rainforest
- AI in the Marshall Islands Rainforest: Server Configuration
This article details the server configuration used to support the “AI in the Marshall Islands Rainforest” project. This project aims to utilize Artificial Intelligence to analyze data collected from remote sensors deployed within the unique rainforest ecosystem of the Marshall Islands. This document is intended for new system administrators and developers contributing to the project.
Project Overview
The Marshall Islands rainforest presents unique challenges for data collection and analysis. High humidity, limited infrastructure, and the need for low-power operation necessitate a carefully designed server infrastructure. The project relies on a hybrid approach, utilizing edge computing at the sensor locations and a central server for advanced analysis and long-term data storage. The edge devices process initial data and transmit summaries to the central server, reducing bandwidth requirements and improving responsiveness. This central server is the focus of this documentation.
Server Hardware Specifications
The central server is housed in a secure, climate-controlled facility in Majuro, the capital of the Marshall Islands. The following table details the hardware specifications:
| Component | Specification |
|---|---|
| CPU | Dual Intel Xeon Gold 6248R (24 Cores/48 Threads per CPU) |
| RAM | 256 GB DDR4 ECC Registered 3200MHz |
| Storage (OS) | 2 x 960 GB NVMe PCIe Gen4 SSD (RAID 1) |
| Storage (Data) | 8 x 16 TB SAS 7.2K RPM HDD (RAID 6) |
| Network Interface | Dual 10 Gigabit Ethernet |
| Power Supply | Redundant 1600W 80+ Platinum |
| Chassis | 4U Rackmount Server |
This hardware configuration provides substantial processing power, ample memory, and large storage capacity for the project's data analysis needs. RAID configurations ensure data redundancy and availability, crucial for long-term data preservation. See RAID configurations for more details.
Software Stack
The server runs a customized Linux distribution based on Ubuntu Server 22.04 LTS. This provides a stable and secure foundation for the software stack. The key software components are detailed below:
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Base Operating System |
| Database | PostgreSQL 14 | Data Storage and Management |
| Programming Language | Python 3.10 | AI Model Development and Execution |
| AI Framework | TensorFlow 2.10 | Machine Learning and Deep Learning |
| Web Server | Nginx 1.22 | Serving API endpoints and web interface |
| Data Visualization | Grafana 8.5 | Real-time data monitoring and visualization |
| Containerization | Docker 20.10 | Application Packaging and Deployment |
The software stack is designed for scalability, maintainability, and security. Docker containers are used to isolate applications and simplify deployment. See the Docker documentation for more information. Python, TensorFlow and PostgreSQL are integrated to manage the AI models and the data sets. Consider reviewing the Python tutorial and PostgreSQL basics for assistance.
Network Configuration
The server is connected to the internet via a dedicated fiber optic connection. A firewall (iptables) is configured to restrict access to only authorized ports and IP addresses. The server is also behind a reverse proxy (Nginx) to enhance security and performance.
The following table outlines the key network settings:
| Setting | Value |
|---|---|
| IP Address | 192.168.1.100 (Internal) / 203.0.113.5 (External) |
| Subnet Mask | 255.255.255.0 |
| Gateway | 192.168.1.1 |
| DNS Servers | 8.8.8.8, 8.8.4.4 |
| Firewall Rules | Allow SSH (port 22) from authorized IPs only. Allow HTTPS (port 443) for web interface. Allow PostgreSQL (port 5432) from internal network only. |
Proper network segmentation and a robust firewall configuration are essential to protect the server from unauthorized access. Review the Network Security Guide for additional information on securing your network.
Data Backup and Recovery
A comprehensive data backup and recovery plan is in place to ensure data integrity and availability. Daily full backups are performed and stored offsite. Incremental backups are performed hourly. The backup system utilizes rsync for efficient data transfer. A disaster recovery plan is also in place, detailing the steps to restore the server in the event of a hardware failure or other disaster. See Data Backup Strategies for more details.
Monitoring and Alerting
The server is continuously monitored using Prometheus and Grafana. Key metrics such as CPU usage, memory usage, disk I/O, and network traffic are monitored in real-time. Alerts are configured to notify administrators of any potential issues. See Prometheus documentation and Grafana tutorials for detailed information.
Security Considerations
Security is a paramount concern. Regular security audits are conducted to identify and address vulnerabilities. The server is hardened according to industry best practices. All software is kept up-to-date with the latest security patches. Access to the server is restricted to authorized personnel only. Please review the Server Hardening Checklist for a comprehensive guide. Furthermore, consider the Security Policy for more detailed information.
Main Page Data Collection Methods AI Model Training Sensor Network Topology Data Analysis Pipelines
Intel-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Core i7-6700K/7700 Server | 64 GB DDR4, NVMe SSD 2 x 512 GB | CPU Benchmark: 8046 |
| Core i7-8700 Server | 64 GB DDR4, NVMe SSD 2x1 TB | CPU Benchmark: 13124 |
| Core i9-9900K Server | 128 GB DDR4, NVMe SSD 2 x 1 TB | CPU Benchmark: 49969 |
| Core i9-13900 Server (64GB) | 64 GB RAM, 2x2 TB NVMe SSD | |
| Core i9-13900 Server (128GB) | 128 GB RAM, 2x2 TB NVMe SSD | |
| Core i5-13500 Server (64GB) | 64 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Server (128GB) | 128 GB RAM, 2x500 GB NVMe SSD | |
| Core i5-13500 Workstation | 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000 |
AMD-Based Server Configurations
| Configuration | Specifications | Benchmark |
|---|---|---|
| Ryzen 5 3600 Server | 64 GB RAM, 2x480 GB NVMe | CPU Benchmark: 17849 |
| Ryzen 7 7700 Server | 64 GB DDR5 RAM, 2x1 TB NVMe | CPU Benchmark: 35224 |
| Ryzen 9 5950X Server | 128 GB RAM, 2x4 TB NVMe | CPU Benchmark: 46045 |
| Ryzen 9 7950X Server | 128 GB DDR5 ECC, 2x2 TB NVMe | CPU Benchmark: 63561 |
| EPYC 7502P Server (128GB/1TB) | 128 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/2TB) | 128 GB RAM, 2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (128GB/4TB) | 128 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/1TB) | 256 GB RAM, 1 TB NVMe | CPU Benchmark: 48021 |
| EPYC 7502P Server (256GB/4TB) | 256 GB RAM, 2x2 TB NVMe | CPU Benchmark: 48021 |
| EPYC 9454P Server | 256 GB RAM, 2x2 TB NVMe |
Order Your Dedicated Server
Configure and order your ideal server configuration
Need Assistance?
- Telegram: @powervps Servers at a discounted price
⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️