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# How to Scale Rivalz Network Earnings Without Expensive Upgrades

This article is designed for newcomers to the Rivalz network and aims to provide a comprehensive guide on optimizing server performance to maximize earnings *without* resorting to costly hardware upgrades.  We will focus on software configuration, caching strategies, and efficient resource management.  Understanding these concepts will allow you to support a larger number of concurrent users and deliver content faster, ultimately leading to increased revenue. This guide assumes you have a basic understanding of Linux server administration and the MediaWiki platform.

== Understanding the Bottlenecks ==

Before diving into solutions, it's crucial to identify common performance bottlenecks within a MediaWiki installation serving the Rivalz network.  These typically fall into several categories:

*   **Database Load:** The MySQL/MariaDB database is often the primary bottleneck. Complex queries, insufficient indexing, and a lack of caching can significantly slow down page loads.
*   **PHP Execution:**  PHP processes handle the majority of MediaWiki's logic.  Slow scripts, unoptimized code, and inadequate memory allocation can impact performance.
*   **Web Server Load:**  Apache or Nginx must efficiently serve static content and proxy PHP requests.  Configuration errors and insufficient resources can cause delays.
*   **Caching:**  A lack of effective caching forces the server to repeatedly perform the same operations, wasting resources.
*   **Network Bandwidth:** While this article focuses on *avoiding* hardware upgrades, ensure your network connection isn’t a limiting factor.

== Optimizing the Database ==

The database is the heart of your MediaWiki installation. Optimizing it is paramount.

=== MySQL/MariaDB Configuration ===

Adjusting your database configuration can yield significant improvements. Here's a sample configuration optimized for read-heavy workloads, common for the Rivalz network:

{| class="wikitable"
! Parameter
! Value
! Description
|-
| `innodb_buffer_pool_size`
| 512M - 2G (depending on RAM)
| The amount of memory allocated to cache InnoDB data and indexes.
|-
| `query_cache_size`
| 64M - 256M
|  The amount of memory allocated to cache query results. *Note: Query Cache is deprecated in newer versions of MySQL/MariaDB.* Consider using a ProxySQL or similar solution.
|-
| `max_connections`
| 150 - 300
| The maximum number of concurrent connections to the database.
|-
| `key_buffer_size`
| 32M - 64M
|  For MyISAM tables (if any), this buffers index blocks.
|-
| `innodb_log_file_size`
| 64M - 256M
| Size of each InnoDB log file.  Larger values generally improve write performance.
|}

Remember to restart your database service after making changes to the configuration file.  Regular database maintenance, including `OPTIMIZE TABLE` and `ANALYZE TABLE`, is also crucial. See [[Manual:Database_optimization]] for more details.

=== Indexing ===

Proper indexing dramatically speeds up query execution.  Focus on indexing columns frequently used in `WHERE` clauses and `JOIN` operations.  Use the `EXPLAIN` statement to analyze query performance and identify missing indexes. Consult the [[Help:Contents]] for information on using the `EXPLAIN` statement.

== PHP Configuration for Enhanced Performance ==

Optimizing PHP settings is another vital step.

=== PHP-FPM Tuning ===

If you're using PHP-FPM (recommended), tune its configuration to handle the expected load.

{| class="wikitable"
! Parameter
! Value
! Description
|-
| `pm`
| dynamic
| Process manager type.  `dynamic` adjusts the number of processes based on demand.
|-
| `pm.max_children`
| 5 - 10 (per CPU core)
| Maximum number of child processes.
|-
| `pm.start_servers`
| 2 - 5
| Number of processes started at startup.
|-
| `pm.min_spare_servers`
| 1 - 3
| Minimum number of idle processes.
|-
| `pm.max_spare_servers`
| 3 - 5
| Maximum number of idle processes.
|-
| `request_terminate_timeout`
| 60s
|  Maximum time a process can handle a request.
|}

=== Opcode Caching ===

Implement an opcode cache like OpCache (built-in to PHP 5.5 and later).  Opcode caching stores precompiled PHP code in memory, eliminating the need for recompilation on each request. This significantly reduces CPU load.  See [[Manual:Configuration_settings]] for detailed information.

=== Memory Management ===

Ensure PHP has sufficient memory allocated.  A common starting point is 256M or 512M, but adjust based on your usage.  Monitor PHP memory usage and increase the `memory_limit` setting in `php.ini` if necessary.



== Leveraging Caching Mechanisms ==

Caching is key to reducing server load.

=== MediaWiki Caching ===

MediaWiki offers several caching layers:

*   **Parser Cache:** Caches the output of the parser, reducing the need to re-parse pages frequently.  Ensure this is enabled in `LocalSettings.php`.
*   **Object Cache:** A more advanced caching layer that can store database query results and other objects.  Memcached or Redis are excellent options.  See [[Manual:Caching]] for setup instructions.
*   **TransformCache:** Caches transformed output, like resized images.

=== Web Server Caching ===

Configure your web server (Apache or Nginx) to cache static assets like CSS, JavaScript, and images. This reduces the load on PHP and the database. Nginx is generally more efficient for serving static content. See [[Help:Images]] for more information on image handling and caching.

=== Reverse Proxy Caching ===

Consider using a reverse proxy like Varnish or Nginx as a cache layer in front of your web server. This can dramatically improve performance by caching entire pages. See [[Manual:Reverse proxy]] for more details.

== Monitoring and Analysis ==

Regularly monitor your server's performance using tools like `top`, `htop`, `MySQL Enterprise Monitor`, or `New Relic`. Analyze logs to identify slow queries and potential bottlenecks.  Proactive monitoring allows you to identify and address performance issues before they impact users.  Consider using tools like [[Extension:PerformanceLog]] to gather detailed performance data.

== Conclusion ==

Scaling the Rivalz network earnings without expensive hardware upgrades requires a strategic approach focused on optimizing software configurations and leveraging caching mechanisms. By carefully tuning your database, PHP settings, and web server, and by implementing effective caching strategies, you can significantly improve performance and support a growing user base without breaking the bank. Remember to continuously monitor your server's performance and adjust your configurations as needed.




[[Manual:Configuration_settings]]
[[Manual:Database_optimization]]
[[Manual:Caching]]
[[Manual:Reverse proxy]]
[[Help:Images]]
[[Help:Contents]]
[[Extension:PerformanceLog]]
[[Manual:PHP]]
[[Manual:Apache]]
[[Manual:Nginx]]
[[Manual:MediaWiki_installation]]
[[Help:Advanced_installation]]
[[Manual:Configuring_the_database]]
[[Manual:Maintenance]]
[[Manual:Upgrading]]
[[Manual:Security]]
[[Manual:Troubleshooting]]

[[Category:Server Hardware]]


== Intel-Based Server Configurations ==
{| class="wikitable"
! 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 ==
{| class="wikitable"
! 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.* ⚠️