AI in Essex

AI in Essex: Server Configuration

This document details the server configuration supporting the "AI in Essex" project. It is intended for new members of the server team and provides a comprehensive overview of the hardware and software components. This project focuses on applying Artificial Intelligence techniques to analyze data related to Essex County, with applications in traffic management, environmental monitoring, and public health.

Overview

The "AI in Essex" project relies on a distributed server infrastructure to handle the large datasets and computationally intensive AI models. The core infrastructure is located in a secure data center in Chelmsford, with backup and disaster recovery systems in place at a secondary site in Colchester. The system is designed for scalability and high availability. We utilize a combination of bare-metal servers and virtual machines to optimize performance and resource allocation. Please refer to the Data Security Policy for information on data protection.

Hardware Specifications

The primary server cluster consists of the following hardware components. These are detailed in the table below. Regular hardware audits are conducted, as per the Hardware Audit Procedure.

Server Role	Manufacturer	Model	CPU	RAM	Storage	Network Interface
AI Training Nodes (x4)	Dell	PowerEdge R750	2 x Intel Xeon Gold 6338	512 GB DDR4 ECC	8 x 4TB NVMe SSD (RAID 0)	100 Gbps Ethernet
Inference Servers (x6)	HP	ProLiant DL380 Gen10	2 x Intel Xeon Silver 4310	256 GB DDR4 ECC	4 x 2TB NVMe SSD (RAID 1)	25 Gbps Ethernet
Database Server	Lenovo	ThinkSystem SR650	2 x AMD EPYC 7763	1TB DDR4 ECC	12 x 8TB SAS HDD (RAID 6)	10 Gbps Ethernet
Data Storage Server	NetApp	FAS2750	Dual Intel Xeon Gold 6248R	256 GB DDR4 ECC	16 x 16TB SAS HDD (RAID-DP)	40 Gbps Ethernet

Software Stack

The software stack is built on a Linux foundation, utilizing open-source tools wherever possible. All software installations are managed through our Configuration Management System. Version control is handled by Git Repository Access.

Operating System: Ubuntu Server 22.04 LTS
Containerization: Docker and Kubernetes
AI Frameworks: TensorFlow, PyTorch, scikit-learn
Database: PostgreSQL 14
Data Processing: Apache Spark, Apache Kafka
Monitoring: Prometheus and Grafana (see Monitoring Dashboard Access)
Version Control: Git

Network Configuration

The network is segmented into several VLANs for security and performance. The Network Diagram provides a visual representation of the network topology. Key VLANs include:

VLAN 10: Management Network
VLAN 20: AI Training Network
VLAN 30: Inference Network
VLAN 40: Data Storage Network
VLAN 50: Database Network

Firewall rules are configured using iptables and are regularly reviewed by the Security Team. All communication between servers is encrypted using TLS. See the Firewall Configuration Guide for details.

Database Schema

The PostgreSQL database stores various datasets related to Essex County. The key tables are described below:

Table Name	Description	Key Columns
traffic_data	Real-time and historical traffic data.	timestamp, location_id, speed, volume
environmental_data	Air quality, water quality, and weather data.	timestamp, sensor_id, parameter, value
public_health_data	Anonymized public health statistics.	timestamp, age_group, postcode, condition

Regular database backups are performed, following the Database Backup Policy. Database access is restricted to authorized personnel only.

Security Considerations

Security is paramount. All servers are hardened according to the Server Hardening Checklist. Regular vulnerability scans are conducted using Nessus. Intrusion detection and prevention systems (IDS/IPS) are deployed to monitor for malicious activity. All access to the servers is logged and audited. Refer to the Incident Response Plan in case of a security breach.

Future Scalability

The system is designed to scale horizontally. Adding more AI training nodes or inference servers is straightforward using Kubernetes. We are also exploring the use of cloud-based services for burst capacity. The Scalability Plan outlines the future expansion strategy.

Component	Current Capacity	Projected Capacity (12 months)
AI Training Nodes	4	8
Inference Servers	6	12
Data Storage	128 TB	256 TB

Related Pages

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.* ⚠️