AI in the North America Rainforest
AI in the North America Rainforest: Server Configuration
This article details the server configuration used to support the “AI in the North America Rainforest” project. This project utilizes machine learning algorithms to analyze data collected from sensor networks deployed within several rainforest ecosystems across North America. This document is intended for new engineers onboarding to the project and assumes a basic understanding of Linux server administration and networking.
Project Overview
The “AI in the North America Rainforest” project aims to predict and mitigate the effects of climate change on these fragile ecosystems. We collect data on temperature, humidity, soil moisture, animal activity, and plant health. This data is processed using a combination of edge computing and centralized server infrastructure. The data pipeline involves real-time analysis at the sensor level, followed by more complex modeling and analysis on our central servers. Data Pipeline Overview provides a more detailed explanation of the whole process.
Server Infrastructure
Our central server infrastructure is hosted in a secure data center in Oregon. It consists of a cluster of high-performance servers, utilizing both physical and virtualized instances. We employ a hybrid cloud architecture, leveraging both on-premise hardware and cloud resources for scalability and redundancy. Hybrid Cloud Architecture details the benefits of this design. The server cluster is managed using Kubernetes for container orchestration. Kubernetes Documentation is a valuable resource for learning more about this.
Physical Server Specifications
The core of our processing power resides in a cluster of eight physical servers. Their specifications are detailed below:
| CPU | Memory | Storage | Network Interface |
|---|---|---|---|
| 2 x Intel Xeon Gold 6248R (24 cores each) | 512 GB DDR4 ECC Registered RAM | 16 TB NVMe SSD (RAID 10) | 100 Gbps Ethernet |
| 2 x AMD EPYC 7763 (64 cores each) | 1 TB DDR4 ECC Registered RAM | 32 TB NVMe SSD (RAID 10) | 200 Gbps Ethernet |
These servers are running Ubuntu Server 22.04 LTS. We utilize a custom kernel optimized for machine learning workloads. Kernel Optimization Guide provides details on the kernel configuration.
Virtual Machine Specifications
In addition to the physical servers, we also utilize virtual machines for less demanding tasks, such as data ingestion and preprocessing. These VMs are hosted on a VMware vSphere cluster.
| VM Name | vCPUs | Memory | Storage | Operating System |
|---|---|---|---|---|
| Data Ingestion 1 | 8 | 64 GB | 2 TB SSD | Ubuntu Server 22.04 LTS |
| Data Preprocessing 1 | 16 | 128 GB | 4 TB SSD | Ubuntu Server 22.04 LTS |
| Database Server 1 | 16 | 256 GB | 8 TB SSD | CentOS 7 |
These VMs are regularly backed up using Veeam Backup & Replication. Veeam Documentation is available for backup procedures.
Database Server Details
The primary database server is a dedicated VM running PostgreSQL 14. It stores all the collected sensor data, metadata, and model outputs.
| Parameter | Value | ||||||
|---|---|---|---|---|---|---|---|
| Database Engine | PostgreSQL 14 | Maximum Connections | 500 | WAL Level | Replica | Shared Buffers | 128GB |
The database is regularly monitored using Prometheus and Grafana. Prometheus Monitoring Guide will help with setting up monitoring. Regular database maintenance, including vacuuming and analyzing, is performed weekly. PostgreSQL Maintenance Guide provides detailed instructions.
Software Stack
The software stack used for the project includes:
- Python 3.9: Used for data analysis and machine learning model development.
- TensorFlow 2.8: Our primary machine learning framework.
- PyTorch 1.12: Used for specialized model architectures.
- Jupyter Notebook: For interactive data exploration and model prototyping.
- Git: For version control. Git Best Practices are strongly enforced.
- Docker: For containerizing applications.
- Kubernetes: For container orchestration.
Networking
The servers are connected to a private network within the data center. A firewall protects the network from external access. Access to the servers is restricted to authorized personnel via SSH with key-based authentication. SSH Security Guide outlines the best practices. Internal communication between servers is secured using TLS/SSL. TLS/SSL Configuration Guide provides instructions on configuring TLS/SSL. The network is monitored by Nagios for uptime and performance.
Security Considerations
Security is paramount. All servers are hardened using industry best practices. Regular security audits are conducted. Intrusion detection and prevention systems are in place. Data is encrypted both in transit and at rest. Data Encryption Standards details our encryption policies.
Contact Support if you have any questions or concerns.
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 |
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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️