A/B testing

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A/B Testing: Server Configuration and Implementation

A/B testing, also known as split testing, is a critical technique for optimizing website and application performance. This article details the server-side configuration necessary to implement A/B tests in a MediaWiki environment. It focuses on the technical aspects of directing traffic and analyzing results, assuming you already have a testing hypothesis and variations prepared. This guide is intended for server engineers and those with a strong understanding of Server administration and Web server configuration.

Understanding the Basics

A/B testing involves showing two or more variations of a page or feature to different segments of users. The goal is to determine which variation performs better based on predefined metrics. Server-side A/B testing allows for greater control and flexibility, enabling tests that impact backend logic and data processing, not just the user interface. This contrasts with client-side testing, which relies on JavaScript and can be vulnerable to manipulation. Successful A/B testing relies on accurate Traffic distribution and reliable Data collection.

Server Configuration Options

Several approaches can be used to configure A/B testing on the server side. The most common involve utilizing a load balancer, web server directives, or application-level code. Each method has its advantages and disadvantages. We’ll focus on a load balancer approach as it provides the most flexibility and minimal impact on MediaWiki’s core code. You’ll need access to your load balancer’s configuration, such as HAProxy or Nginx.

Load Balancer Configuration

This method directs traffic to different backend servers based on a defined percentage split. Each backend server hosts a different variation of the feature being tested. This is the preferred method due to its clean separation of concerns and minimal disruption to MediaWiki itself.

Key Component Description
Load Balancer Distributes traffic based on configured rules. Backend Servers Each server hosts a specific variation of the feature. Traffic Split Percentage of users directed to each variation. Monitoring Tracks performance metrics for each variation.

Example (using pseudo-configuration for clarity):

```

  1. Backend servers for variation A

server variation_a 192.168.1.10:80 check

  1. Backend servers for variation B

server variation_b 192.168.1.11:80 check

  1. Define traffic distribution

balance roundrobin cookie server_selection insert indirect http-request set-header X-AB-Test variation_a if { cookie server_selection contains "A" } http-request set-header X-AB-Test variation_b if { cookie server_selection contains "B" } ```

This example utilizes cookies to maintain user assignment to a specific variation. The `X-AB-Test` header is then passed to MediaWiki, allowing it to display the appropriate content. Refer to your specific load balancer's documentation for precise configuration details. Understanding Load balancing algorithms is critical for optimal performance.

MediaWiki Integration

Once the load balancer is configured, MediaWiki needs to be adapted to respond to the `X-AB-Test` header. This is achieved through the use of Hooks and Extensions.

Utilizing Hooks

The `BeforeDisplayNoContent` hook is ideal for detecting the `X-AB-Test` header and rendering the appropriate variation. You'll need to create a custom extension or modify an existing one to leverage this hook.

Example (PHP code snippet within a MediaWiki extension):

```php <?php class MyABTestingExtension { 

   public static function beforeDisplayNoContent( $out, $skin ) {
       if ( isset( $_SERVER['HTTP_X_AB_TEST'] ) ) {
           $variation = $_SERVER['HTTP_X_AB_TEST'];
           // Logic to display different content based on $variation
           if ( $variation == 'variation_a' ) {
               // Display content for variation A
           } elseif ( $variation == 'variation_b' ) {
               // Display content for variation B
           }
       }
       return true;
   }

} ```

This code checks for the presence of the `X-AB-Test` header and then renders the appropriate content based on its value. Remember to register this hook within your extension's `Extension.php` file. Careful attention to PHP coding standards is essential.

Extension Development

For complex A/B tests, creating a dedicated extension is highly recommended. This allows for better organization, maintainability, and scalability. The extension should handle:

  • Reading the `X-AB-Test` header.
  • Determining the appropriate variation.
  • Rendering the corresponding content.
  • Logging user interactions for analysis.

Monitoring and Analysis

Collecting and analyzing data is crucial for determining the success of your A/B test. This requires integrating with an analytics platform such as Google Analytics or a custom logging system.

Metric Description Collection Method
Conversion Rate Percentage of users completing a desired action. Analytics platform or custom logging. Page Views Number of times a page is viewed. Web server logs or analytics platform. Bounce Rate Percentage of users leaving a page after viewing only one page. Analytics platform. Time on Page Average time users spend on a page. Analytics platform.

Consider using a dedicated A/B testing platform for more advanced features such as statistical significance calculations and multivariate testing. Proper Database queries are important for accurate analytics.

Technical Specifications

Component Version Requirements
MediaWiki 1.40 Properly installed and configured.
Web Server Apache 2.4+ or Nginx 1.18+ Configured to pass the `X-AB-Test` header.
Load Balancer HAProxy 2.0+ or Nginx Plus Configured for traffic splitting and cookie insertion.
PHP 7.4+ Required for MediaWiki extension development.
Analytics Platform Google Analytics, Matomo, or custom logging Integrated for data collection and analysis.

Security Considerations

  • Ensure the `X-AB-Test` header is only used for A/B testing purposes and does not contain sensitive information.
  • Protect your backend servers from unauthorized access.
  • Regularly monitor your A/B testing configuration for any security vulnerabilities. Security audits are recommended.

Conclusion

Implementing A/B testing requires careful planning and configuration. By utilizing a load balancer and integrating with MediaWiki through hooks and extensions, you can effectively test different variations and optimize your website’s performance. Remember to continuously monitor and analyze your results to ensure that your A/B tests are yielding meaningful insights. Further reading on Performance optimization can be beneficial.


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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