How to Monitor Performance on a Development Server
How to Monitor Performance on a Development Server
This article details how to monitor the performance of your MediaWiki development server. Understanding server performance is critical for identifying bottlenecks, optimizing configurations, and ensuring a smooth development experience. We will cover tools and techniques for monitoring CPU usage, memory consumption, disk I/O, and MySQL performance. This guide assumes you have a basic understanding of server administration and the command line.
1. Understanding the Key Metrics
Before diving into specific tools, it’s important to understand what metrics are most relevant to MediaWiki performance. These include:
- CPU Usage: High CPU usage can indicate inefficient code, excessive database queries, or a generally overloaded server.
- Memory Consumption: Insufficient memory can lead to swapping, dramatically slowing down performance. MediaWiki benefits from ample RAM.
- Disk I/O: Slow disk I/O can bottleneck database operations and file access.
- MySQL Performance: As MediaWiki relies heavily on MySQL, its performance is crucial. Key metrics include query execution time, connection count, and cache hit rates.
- Network I/O: While less common on a development server, network bottlenecks can still occur if the server is accessed remotely.
2. Monitoring CPU and Memory Usage
Several tools can help monitor CPU and memory usage.
2.1. `top`
The `top` command is a standard Linux/Unix utility that provides a dynamic real-time view of running processes. It displays CPU usage, memory consumption, and other important metrics.
To use `top`, simply type `top` in your terminal. Press `1` to see CPU usage per core. Press `M` to sort by memory usage, and `P` to sort by CPU usage. Understanding the processes consuming the most resources is the first step to identifying performance issues.
2.2. `htop`
`htop` is an interactive process viewer similar to `top`, but with a more user-friendly interface and improved features. It often needs to be installed separately (e.g., `sudo apt-get install htop` on Debian/Ubuntu, or `sudo yum install htop` on CentOS/RHEL).
`htop` provides color-coded CPU usage, a clearer process tree, and the ability to kill processes directly from the interface.
2.3. `vmstat`
`vmstat` reports virtual memory statistics. It’s useful for identifying memory swapping and other memory-related issues.
Example Usage: `vmstat 1` (reports statistics every 1 second). Pay attention to the `si` (swap in) and `so` (swap out) columns. High values indicate excessive swapping.
3. Monitoring Disk I/O
Disk I/O can significantly impact MediaWiki performance, especially during database operations.
3.1. `iostat`
`iostat` reports disk I/O statistics. It shows read/write speeds, disk utilization, and other important metrics.
Example Usage: `iostat -x 1` (reports extended statistics every 1 second). The `%util` column indicates disk utilization. Values close to 100% suggest a disk bottleneck.
3.2. `iotop`
`iotop` is similar to `top`, but it displays I/O usage by process. It helps identify which processes are performing the most disk I/O. Like `htop`, it usually requires separate installation.
4. Monitoring MySQL Performance
As MediaWiki relies heavily on MySQL, monitoring its performance is crucial.
4.1. `mysqladmin`
The `mysqladmin` utility can provide basic MySQL status information.
Example Usage: `mysqladmin status` (shows server uptime, threads, queries per second, etc.).
4.2. MySQL Slow Query Log
Enabling the slow query log is one of the most effective ways to identify performance bottlenecks. This log records queries that take longer than a specified time to execute. Configure this in your `my.cnf` file:
| Parameter | Value |
|---|---|
| `long_query_time` | `2` (seconds – adjust as needed) |
| `slow_query_log` | `1` (enable logging) |
| `slow_query_log_file` | `/var/log/mysql/mysql-slow.log` (adjust path as needed) |
After configuring, restart the MySQL server. Analyze the slow query log using tools like `mysqldumpslow` or `pt-query-digest`. See MySQL Configuration for more details.
4.3. `SHOW GLOBAL STATUS`
Within the MySQL client, the `SHOW GLOBAL STATUS` command provides a wealth of performance information. Pay attention to:
| Metric | Description |
|---|---|
| `Connections` | Total number of connection attempts. |
| `Threads_connected` | Current number of open connections. |
| `Queries` | Total number of queries executed. |
| `Slow_queries` | Number of queries that took longer than `long_query_time`. |
| `Key_read_requests` | Number of requests to read a key from the key cache. |
| `Key_reads` | Number of physical reads of a key from disk. (High ratio of `Key_reads` to `Key_read_requests` indicates a cache miss) |
5. Advanced Monitoring Tools
For more comprehensive monitoring, consider using dedicated monitoring tools.
5.1. Prometheus & Grafana
Prometheus is a time-series database, and Grafana is a data visualization tool. They can be used to collect and visualize various server metrics, including those related to MediaWiki and MySQL. See Prometheus Setup and Grafana Configuration for more details.
5.2. Nagios/Icinga
Nagios and Icinga are popular open-source monitoring systems that can alert you to performance issues. They require more setup but provide robust monitoring and alerting capabilities.
6. Conclusion
Regularly monitoring your MediaWiki development server's performance is essential for maintaining a smooth and efficient development workflow. By utilizing the tools and techniques outlined in this article, you can identify bottlenecks, optimize configurations, and ensure your MediaWiki instance runs optimally. Refer to Server Security and Database Maintenance for related best practices. Remember to document your findings and adjustments for future reference. Also, consider reviewing Performance Tuning documentation for MediaWiki-specific optimization options.
Help:Contents
Manual:Configuration
Manual:Installing MediaWiki
Manual:Upgrading
MySQL Configuration
Prometheus Setup
Grafana Configuration
Server Security
Database Maintenance
Performance Tuning
Debugging
Extension Installation
API Usage
Skin Customization
MediaWiki Roadmap
Troubleshooting
Command Line Interface
Caching
Load Balancing
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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