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AI in Bournemouth

AI in Bournemouth: Server Configuration

This article details the server configuration supporting the "AI in Bournemouth" project, a local initiative exploring applications of Artificial Intelligence within the Bournemouth, Poole, and Christchurch conurbation. This document is intended for new system administrators and developers contributing to the project. Understanding this configuration is crucial for maintaining stability, scalability, and security.

Overview

The "AI in Bournemouth" project leverages a hybrid server infrastructure, combining on-premise hardware with cloud-based resources. This allows for flexibility in handling varying workloads, from data preprocessing and model training to real-time inference. The on-premise servers are housed within a dedicated data centre at Bournemouth University. Cloud resources are primarily sourced from Amazon Web Services (AWS). A key component is the central data repository, using a Semantic MediaWiki extension for structured data storage.

On-Premise Server Infrastructure

The core on-premise infrastructure consists of three primary server roles: Database Server, Application Server, and File Server. These servers are interconnected via a dedicated Gigabit Ethernet network, with redundant connections for high availability.

Database Server

The Database Server is responsible for storing all project data, including datasets, model metadata, and user information. It’s critical for performance and reliability.

Specification Value
Server Model Dell PowerEdge R740xd
Processor 2 x Intel Xeon Gold 6248R (24 cores per processor)
RAM 256GB DDR4 ECC Registered
Storage 8 x 4TB SAS 12Gbps 7.2K RPM HDD (RAID 6)
Operating System Ubuntu Server 22.04 LTS
Database System MariaDB 10.6

The database is configured with replication for disaster recovery. Regular backups are performed using Bacula. Access to the database is strictly controlled via firewall rules and user authentication. The SQL queries are optimized for performance.

Application Server

The Application Server hosts the core AI applications and APIs. It handles user requests, processes data, and serves predictions.

Specification Value
Server Model HP ProLiant DL380 Gen10
Processor 2 x Intel Xeon Silver 4210 (10 cores per processor)
RAM 128GB DDR4 ECC Registered
Storage 2 x 1TB NVMe SSD (RAID 1)
Operating System CentOS Stream 9
Web Server Apache 2.4
Programming Language Python 3.9

The application utilizes a microservices architecture, deployed using Docker and orchestrated with Kubernetes. Load balancing is handled by a dedicated HAProxy instance.

File Server

The File Server provides central storage for large datasets and model files.

Specification Value
Server Model Synology DiskStation DS1821+
Processor Intel Xeon J4125
RAM 16GB DDR4
Storage 8 x 16TB SATA HDD (RAID 5)
Operating System Synology DSM 7.0
File Protocol NFS, SMB/CIFS

Access to the File Server is managed through network shares and user permissions. Data is backed up regularly to an offsite location using rsync.

Cloud Infrastructure (AWS)

The project utilizes AWS for burst capacity and specialized services.

AWS Services

⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

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