AI in the Brunei Rainforest
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.* ⚠️