How to Scale Your Server as Your Business Grows

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How to Scale Your Server as Your Business Grows

As your business expands, your MediaWiki installation will face increasing demands. Properly scaling your server infrastructure is crucial to maintain performance, reliability, and a positive user experience. This guide outlines strategies for scaling your MediaWiki server, covering hardware, software, and configuration adjustments. We will assume a baseline installation of MediaWiki 1.40 and a LAMP (Linux, Apache, MySQL/MariaDB, PHP) stack.

1. Understanding Your Current Limits

Before making any changes, it's essential to understand your current server’s bottlenecks. Monitoring tools are invaluable here. Consider using tools like `top`, `htop`, `vmstat`, `iostat`, and database-specific monitoring tools (e.g., `mysqladmin processlist` for MySQL). Pay attention to CPU usage, memory consumption, disk I/O, and network traffic. Also, monitor your Special:Statistics page within MediaWiki itself for usage patterns. Slow queries in the database are a common cause of performance issues; examine your Special:SlowQueries regularly.

2. Hardware Scaling

The first step in scaling is often increasing hardware resources. This can involve vertical scaling (increasing resources on the existing server) or horizontal scaling (adding more servers).

2.1 Vertical Scaling

This is the simplest approach. Upgrade components of your existing server.

Component Baseline Recommended (Medium Load) Recommended (High Load)
CPU 2 Cores 4-8 Cores 8+ Cores
RAM 4 GB 8-16 GB 32+ GB
Storage 100 GB HDD 500 GB SSD 1+ TB SSD (RAID 1 or 10)
Network 1 Gbps 1 Gbps 10 Gbps

Consider using Solid State Drives (SSDs) for significantly faster read/write speeds compared to traditional Hard Disk Drives (HDDs). RAID configurations (e.g., RAID 1 for redundancy, RAID 10 for performance and redundancy) can further improve reliability and speed.

2.2 Horizontal Scaling

This involves adding more servers to distribute the load. This is more complex but provides greater scalability and redundancy. Common approaches include:

  • Load Balancing: Distribute traffic across multiple web servers using a load balancer like Apache HTTP Server with `mod_proxy_balancer` or a dedicated hardware load balancer.
  • Database Replication: Replicate your database to multiple servers. Configure one as the primary (writable) and others as read-only replicas. This offloads read operations from the primary database. See Manual:Database replication for more details.
  • Caching Servers: Implement dedicated caching servers (e.g., Memcached or Redis) to store frequently accessed data, reducing the load on the database.

3. Software Configuration

Optimizing your software stack is just as important as upgrading hardware.

3.1 Web Server (Apache)

  • MPM Configuration: Choose the appropriate Multi-Processing Module (MPM) for your needs. `prefork` is stable but less efficient. `worker` and `event` are more efficient but require more configuration. Review Apache MPM documentation for details.
  • Caching: Enable browser caching and use Apache’s caching modules (e.g., `mod_cache`, `mod_disk_cache`).
  • Compression: Enable Gzip compression (`mod_deflate`) to reduce the size of transferred data.

3.2 Database (MySQL/MariaDB)

  • Configuration Tuning: Adjust the `my.cnf` (or `my.ini`) configuration file. Key parameters to tune include `innodb_buffer_pool_size` (allocate sufficient memory to the buffer pool), `query_cache_size` (enable and tune the query cache – though note that it's deprecated in later versions), and `max_connections`.
  • Indexing: Ensure proper indexing of database tables, especially those frequently used in searches and queries. Use `EXPLAIN` to analyze query performance and identify missing indexes.
  • Slow Query Log: Regularly analyze the slow query log to identify and optimize inefficient queries.

Here's an example of recommended MySQL/MariaDB configuration settings (adjust based on your server's resources):

Parameter Value (Example) Description
`innodb_buffer_pool_size` 8G Amount of memory allocated to the InnoDB buffer pool.
`query_cache_size` 64M Size of the query cache (deprecated in newer versions).
`max_connections` 200 Maximum number of concurrent connections to the database.
`key_buffer_size` 32M Size of the key buffer for MyISAM tables.

3.3 PHP

  • Opcode Caching: Use an opcode cache like OpCache (built-in since PHP 5.5) to significantly improve PHP performance.
  • Memory Limit: Increase the PHP memory limit (`memory_limit` in `php.ini`) if you encounter memory-related errors.
  • Realpath Cache: Optimize the `realpath_cache_size` and `realpath_cache_ttl` settings in `php.ini`.

4. MediaWiki-Specific Optimizations

  • Caching: Enable and configure MediaWiki’s built-in caching mechanisms. Consider using a more robust caching solution like Memcached or Redis as mentioned earlier. See Manual:Caching.
  • Job Queue: Monitor the Special:JobQueue and ensure jobs are being processed efficiently. Adjust the number of worker threads if necessary.
  • Database Maintenance: Regularly run database maintenance tasks like `OPTIMIZE TABLE` and `ANALYZE TABLE` to improve performance.
  • Extensions: Evaluate the performance impact of installed Extension:Extensions. Disable or optimize extensions that are causing performance issues.
  • Search Engine: Consider using an external search engine like Elasticsearch or Solr for faster and more accurate search results, especially on large wikis. See Manual:ElasticSearch.

5. Monitoring and Future Planning

Scaling is an ongoing process. Continuously monitor your server’s performance and adjust your configuration as needed. Regularly review your hardware and software configurations to ensure they are aligned with your business growth and user demands. Plan for future scalability by anticipating increased traffic and data volume. Consider adopting a DevOps approach to automate deployment and monitoring.



Special:Statistics Special:SlowQueries Manual:Database replication Apache MPM documentation Manual:Caching OpCache Manual:JobQueue Extension:Extensions Manual:ElasticSearch Manual:Configuration Manual:Upgrade process Help:Contents Help:System administrators Help:FAQ Manual:Load balancer configuration


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.* ⚠️

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