GFS model
- GFS Model Server Configuration
This article details the server configuration for the GFS (Google File System) model utilized within our infrastructure. This setup is crucial for handling large-scale data storage and retrieval, underpinning many of our core services like MediaStorage and VariantHandling. This is intended as a tutorial for new server engineers.
Overview
The GFS model, adapted for our MediaWiki environment, prioritizes scalability, fault tolerance, and high throughput. It’s a distributed file system designed to provide reliable access to data across a cluster of commodity hardware. Unlike traditional file systems, GFS is optimized for large files, such as the images and videos used throughout the wiki and related projects. We don't implement the complete GFS system as Google does, but we borrow key concepts for improved performance. Our implementation focuses on data sharding across multiple servers and utilizes a redundancy system to ensure data availability. Understanding this model is critical for troubleshooting and maintaining our server infrastructure. See also Data Backup Procedures.
Hardware Specifications
The following table outlines the hardware specifications for each server node within the GFS model cluster:
| Component | Specification |
|---|---|
| CPU | Intel Xeon Gold 6248R (24 cores) |
| RAM | 256 GB DDR4 ECC Registered |
| Storage | 8 x 4TB SAS 7.2k RPM HDDs (configured in RAID 6) |
| Network Interface | Dual 100 Gbps Ethernet |
| Motherboard | Supermicro X11DPG-QT |
| Power Supply | 2 x 1600W Redundant Power Supplies |
These specifications are standardized across all GFS nodes to ensure consistent performance and manageability. Regular hardware audits are conducted; see Server Audit Logs.
Software Configuration
The software stack is carefully chosen to complement the hardware and provide a robust and scalable file system. We utilize a custom-built layer on top of Linux, integrating elements of distributed file system principles.
| Software | Version | Purpose |
|---|---|---|
| Operating System | Ubuntu Server 22.04 LTS | Base operating system for all nodes. |
| File System | Custom Distributed File System (based on XFS) | Provides the core file storage and retrieval functionality. |
| Networking | RDMA over Converged Ethernet (RoCEv2) | Enables high-speed, low-latency communication between nodes. |
| Monitoring | Prometheus & Grafana | System monitoring and alerting. See Monitoring Dashboard. |
| Configuration Management | Ansible | Automated server configuration and deployment. See Ansible Playbooks. |
Data Replication and Chunking
Data within the GFS model is broken down into fixed-size chunks, typically 64MB. Each chunk is replicated across multiple nodes for fault tolerance. We maintain a replication factor of three, meaning each chunk exists on three different servers. This ensures that data remains accessible even if one or two servers fail. The Chunk Server is responsible for storing and retrieving these chunks.
The following table details the data replication strategy:
| Replication Factor | Description |
|---|---|
| 3 | Each data chunk is replicated on three separate servers. |
| Geographic Distribution | Replicas are distributed across different physical locations to mitigate the risk of regional outages. |
| Dynamic Replication | The system dynamically adjusts the replication factor based on data access patterns and server health. |
Master Server Role
The Master Server plays a critical role in managing the GFS cluster. It maintains metadata about all files, including the location of chunks and their replicas. The Master Server does *not* store the actual file data; it only manages metadata. The Master Server is also responsible for garbage collection, rebalancing chunks across nodes, and handling file system namespace operations. We employ a primary-backup configuration for the Master Server, with automatic failover in case of primary server failure. See Master Server Failover.
Future Enhancements
We are continually working to improve the performance and reliability of our GFS model. Future enhancements include:
- Implementation of erasure coding for increased storage efficiency.
- Integration with a more advanced caching layer.
- Automated data tiering based on access frequency.
- Improved monitoring and alerting capabilities.
- Enhancements to the Security Protocols.
Related Articles
- Network Topology
- Storage Architecture
- Disaster Recovery Plan
- Performance Tuning
- Server Maintenance Schedule
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.* ⚠️