AI in the Brunei Rainforest

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AI in the Brunei Rainforest: Server Configuration

This article details the server configuration used to support the "AI in the Brunei Rainforest" project. This project utilizes artificial intelligence to analyze data collected from remote sensors deployed within the rainforest ecosystem. This document is aimed at new system administrators and developers contributing to the project's infrastructure. It covers hardware, software, and network considerations. Understanding these configurations is crucial for maintaining system stability and enabling future expansion. Refer to Special:MyPreferences to customize your MediaWiki experience.

Project Overview

The "AI in the Brunei Rainforest" project gathers data from a network of sensors monitoring biodiversity, climate conditions, and forest health. This data is streamed to a central server cluster for processing using machine learning algorithms. The processed data is then used to generate reports and visualizations accessible through a web interface. For details on the data analysis pipeline, see Data Processing Pipeline. A comprehensive overview of the project goals can be found at Project Goals.

Server Hardware Configuration

The server infrastructure is comprised of three primary server roles: data ingestion, processing, and web serving. Each role is hosted on dedicated hardware for optimal performance.

Server Role Hardware Specifications Quantity
Data Ingestion CPU: 2 x Intel Xeon Gold 6248R
RAM: 128 GB DDR4 ECC
Storage: 2 x 4TB NVMe SSD (RAID 1)
Network: 10 Gbps Ethernet 		2
Processing (AI/ML) CPU: 2 x AMD EPYC 7763
RAM: 256 GB DDR4 ECC
Storage: 1 x 1TB NVMe SSD (OS) + 4 x 8TB SAS HDD (Data)
GPU: 4 x NVIDIA A100 (40GB) 		4
Web Serving CPU: 2 x Intel Xeon Silver 4210
RAM: 64 GB DDR4 ECC
Storage: 2 x 2TB SSD (RAID 1)
Network: 1 Gbps Ethernet 		2

All servers run a 64-bit operating system (see Software Configuration section). Power consumption is monitored using Power Monitoring System.

Software Configuration

The servers utilize a Linux-based operating system and a suite of software tools for data processing and web serving. The operating system is hardened according to Security Hardening Guide.

Server Role Operating System Key Software Version
Data Ingestion Ubuntu Server 22.04 LTS Apache Kafka, Fluentd, PostgreSQL Kafka 3.3.1, Fluentd 1.14, PostgreSQL 14.7
Processing (AI/ML) Ubuntu Server 22.04 LTS Python 3.10, TensorFlow, PyTorch, CUDA Toolkit Python 3.10.6, TensorFlow 2.12, PyTorch 1.13, CUDA 11.8
Web Serving Ubuntu Server 22.04 LTS Apache HTTP Server, PHP, MariaDB Apache 2.4.55, PHP 8.1, MariaDB 10.6

All software packages are managed using the `apt` package manager. Regular security updates are applied automatically using Automated Patch Management. Version control is handled through Git Repository.

Network Configuration

The server cluster is connected to the internet via a dedicated 10 Gbps fiber optic connection. Internal network traffic is isolated using VLANs.

Network Segment VLAN ID Purpose Security Level
Management Network 10 Server administration and monitoring High
Data Ingestion Network 20 Data transfer from sensors Medium
Processing Network 30 Internal communication between processing servers High
Web Serving Network 40 Public access to the web interface Medium

Firewall rules are configured using `iptables` to restrict access to necessary ports. Detailed firewall configuration can be found at Firewall Rules. Network monitoring is performed using Network Monitoring Tools. DNS resolution is handled by DNS Server Configuration.

Data Storage

Data is stored in a combination of SSDs and HDDs. SSDs are used for frequently accessed data, such as the operating system and active processing datasets. HDDs are used for long-term data archival. Regular backups are performed to an offsite location using Backup and Recovery Procedures. Data retention policies are defined in Data Retention Policy.

Future Expansion

The server infrastructure is designed to be scalable. Additional processing servers can be added to the cluster as needed. The network infrastructure can also be upgraded to support increased data throughput. Plans for future expansion are outlined in Future Infrastructure Plans. Please contribute to the Server Documentation to improve this resource.

Special:Search can help you find more information.


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.* ⚠️

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