AI Project Documentation Hub
- AI Project Documentation Hub
This article details the server configuration for the "AI Project Documentation Hub," a central repository for all documentation related to our ongoing Artificial Intelligence projects. This hub serves as a critical component of our development lifecycle, providing a consistent and accessible source of information for researchers, engineers, and project managers. The system is designed for high availability, scalability, and security, leveraging a robust server infrastructure. The core function of the AI Project Documentation Hub is to host a comprehensive collection of documents, including design specifications, API documentation, training datasets details, model performance reports, and troubleshooting guides. It utilizes a MediaWiki platform, customized for efficient information retrieval and collaborative editing. This configuration aims to balance performance, cost-effectiveness, and maintainability. This documentation will cover the hardware specifications, software stack, performance characteristics, and key configuration details. Understanding these aspects is crucial for effective maintenance, troubleshooting, and future scaling of the platform. We will also discuss security considerations and disaster recovery strategies.
System Overview
The AI Project Documentation Hub operates on a three-tier architecture: a web server tier, an application server tier, and a database server tier. This separation of concerns enhances scalability and maintainability. The web server handles incoming HTTP requests and serves static content. The application server executes the MediaWiki software and processes dynamic requests. The database server stores all wiki content, user data, and configuration information. Load balancing is implemented across the web and application server tiers to distribute traffic and ensure high availability. A dedicated caching layer further improves performance by reducing the load on the database server. A robust backup and recovery system guarantees data integrity and minimizes downtime in the event of a failure. This hub is vital for maintaining the integrity of our AI projects and ensuring knowledge transfer within the team. Understanding the interplay between these tiers is paramount for all administrators and developers. We also utilise a dedicated monitoring system to proactively identify and address potential issues.
Hardware Specifications
The following table details the hardware specifications for each tier of the AI Project Documentation Hub. These specifications are designed to handle the expected load and provide room for future growth.
| Tier | Component | Specification | Quantity |
|---|---|---|---|
| Web Server | CPU | Intel Xeon Gold 6248R (24 cores, 3.0 GHz) | 2 |
| Web Server | Memory (RAM) | 128 GB DDR4 ECC Registered | 2 |
| Web Server | Storage | 1 TB NVMe SSD (RAID 1) | 2 |
| Application Server | CPU | Intel Xeon Gold 6248R (24 cores, 3.0 GHz) | 2 |
| Application Server | Memory (RAM) | 256 GB DDR4 ECC Registered | 2 |
| Application Server | Storage | 2 TB NVMe SSD (RAID 1) | 2 |
| Database Server | CPU | Intel Xeon Platinum 8280 (28 cores, 2.5 GHz) | 1 |
| Database Server | Memory (RAM) | 512 GB DDR4 ECC Registered | 1 |
| Database Server | Storage | 4 TB SAS HDD (RAID 5) | 5 |
The choice of NVMe SSDs for the web and application servers is driven by the need for low latency and high throughput. The database server utilizes SAS HDDs for cost-effectiveness and capacity, as the primary workload is read-intensive. The redundancy provided by RAID configurations ensures data protection and availability. The Server Room Cooling System is designed to maintain optimal temperature and humidity levels. The entire infrastructure is powered by a redundant power supply and backed up by a UPS (Uninterruptible Power Supply). Further details on Storage Area Networks are available in the related documentation.
Performance Metrics
The following table displays key performance metrics observed during peak load testing. These metrics are monitored continuously to ensure the system is operating within acceptable parameters.
| Metric | Value | Unit | Notes |
|---|---|---|---|
| Average Response Time (Web Server) | 0.25 | Seconds | Measured using Apache Bench |
| Average Response Time (Application Server) | 0.5 | Seconds | Measured using MediaWiki's internal timing mechanisms |
| Database Query Latency (Average) | 15 | Milliseconds | Measured using MySQL's slow query log |
| Concurrent Users (Maximum) | 500 | Users | Sustained load without significant performance degradation |
| CPU Utilization (Average - All Servers) | 60 | Percent | During peak load |
| Memory Utilization (Average - All Servers) | 70 | Percent | During peak load |
| Disk I/O (Average - Database Server) | 200 | MB/s | Measured using iostat |
These metrics are constantly monitored using Monitoring Tools and Processes. Performance is regularly assessed against established Service Level Agreements. We use tools like Grafana and Prometheus to visualize these metrics and set up alerts for anomalies. Regular Database Performance Tuning is crucial to maintain optimal query performance. The Network Bandwidth Capacity is also a critical factor impacting overall performance.
Software Configuration
The AI Project Documentation Hub relies on a specific software stack to deliver its functionality. This section details the key software components and their configurations.
| Component | Version | Configuration Details | Notes |
|---|---|---|---|
| Operating System (All Servers) | Ubuntu Server 20.04 LTS | Kernel 5.4.0-166-generic, configured for optimal performance | See Operating System Hardening Guide for security settings. |
| Web Server | Apache 2.4 | Virtual host configured for the AI Project Documentation Hub, SSL enabled with Let's Encrypt | Apache Configuration Best Practices are followed. |
| Application Server | MediaWiki 1.40 | PHP 7.4, MySQL database, configured with caching extensions (Memcached) | Detailed installation instructions available in MediaWiki Installation Guide. |
| Database Server | MySQL 8.0 | InnoDB storage engine, configured for high concurrency and data integrity | Refer to MySQL Configuration Optimization for advanced settings. |
| Load Balancer | HAProxy 2.4 | Round-robin load balancing algorithm, health checks enabled | HAProxy Configuration Details provides further information. |
| Caching Server | Memcached 1.4 | Configured with sufficient memory to cache frequently accessed data | Memcached Usage and Configuration details caching strategies. |
| Monitoring System | Prometheus & Grafana | Monitoring all key server metrics and providing visual dashboards | Monitoring System Architecture explains the overall design |
The choice of Ubuntu Server 20.04 LTS provides a stable and secure platform. MediaWiki 1.40 is the latest stable release and offers the latest features and security patches. MySQL 8.0 is a robust and scalable database system. HAProxy is a reliable and performant load balancer. Memcached significantly improves performance by caching frequently accessed data. Regular software updates and security patches are applied to all components. The Security Audit Procedures are followed rigorously.
Security Considerations
Security is paramount for the AI Project Documentation Hub. Several measures are implemented to protect the system from unauthorized access and data breaches. These include:
- **Firewall:** A firewall is configured to restrict access to the servers based on IP address and port number.
- **SSL/TLS:** All communication between the web server and clients is encrypted using SSL/TLS.
- **User Authentication:** Strong password policies and multi-factor authentication are enforced for all user accounts.
- **Access Control:** Access to sensitive data and configuration files is restricted based on the principle of least privilege.
- **Regular Security Audits:** Regular security audits are conducted to identify and address potential vulnerabilities.
- **Intrusion Detection System:** An intrusion detection system is in place to monitor for malicious activity.
- **Data Encryption:** Data is encrypted both in transit and at rest.
- **Backup and Recovery:** Regular backups are performed to ensure data can be recovered in the event of a disaster.
- **Web Application Firewall (WAF):** A WAF is implemented to protect against common web attacks.
Detailed security guidelines can be found in the Server Security Policy. We also adhere to the Data Privacy Regulations. Regular Vulnerability Scanning is conducted to identify and address potential security flaws.
Disaster Recovery
A comprehensive disaster recovery plan is in place to ensure business continuity in the event of a major outage. This plan includes:
- **Regular Backups:** Full and incremental backups are performed regularly and stored offsite.
- **Replication:** The database server is replicated to a secondary site.
- **Failover Procedures:** Automated failover procedures are in place to switch to the secondary site in the event of a primary site failure.
- **Recovery Time Objective (RTO):** The RTO is 4 hours.
- **Recovery Point Objective (RPO):** The RPO is 1 hour.
- **Testing:** The disaster recovery plan is tested regularly to ensure its effectiveness.
The complete disaster recovery plan is documented in the Disaster Recovery Plan Document. We also conduct regular Business Continuity Drills to ensure preparedness. The Data Backup and Restore Procedures are essential components of the disaster recovery strategy.
Future Enhancements
Several enhancements are planned for the AI Project Documentation Hub, including:
- **Improved Search Functionality:** Implementing a more advanced search engine to facilitate efficient information retrieval.
- **Integration with AI Tools:** Integrating the documentation hub with our AI development tools to automate documentation generation and updates.
- **Enhanced Collaboration Features:** Adding features to improve collaboration among users, such as real-time co-editing and commenting.
- **Scalability Improvements:** Further optimizing the infrastructure to handle increasing traffic and data volume. We are investigating Containerization Technologies like Docker and Kubernetes.
- **Automated Deployment:** Implementing a fully automated deployment pipeline for faster and more reliable updates. See Continuous Integration and Continuous Deployment (CI/CD).
This documentation provides a comprehensive overview of the AI Project Documentation Hub server configuration. Regular updates will be provided as the system evolves. Please refer to the linked documentation for more detailed information on specific topics. Understanding this configuration is crucial for maintaining and improving this vital resource for our AI projects. Further questions can be directed to the System Administration Team.
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.* ⚠️