CPU Performance Metrics
- CPU Performance Metrics
This article details key CPU performance metrics relevant to running a MediaWiki installation. Understanding these metrics is crucial for capacity planning, troubleshooting performance issues, and ensuring a responsive wiki experience for your users. This guide is aimed at system administrators and those responsible for maintaining the server infrastructure.
Introduction
The Central Processing Unit (CPU) is the brain of your server. Its performance directly impacts the speed at which MediaWiki can process requests, generate pages, and handle concurrent users. Monitoring CPU metrics allows you to identify bottlenecks and optimize your server configuration. Poor CPU performance can manifest as slow page loads, edit conflicts, and even server errors. This article will cover the most important metrics to monitor and how to interpret them. We will also touch on how these metrics relate to Special:MyPreferences and user experience.
Key CPU Performance Metrics
Several metrics provide insight into CPU performance. We'll focus on the most important ones for a MediaWiki environment.
CPU Utilization
CPU utilization represents the percentage of time the CPU is actively working. High CPU utilization (consistently above 80-90%) indicates the CPU is a bottleneck. However, it's important to distinguish between user, system, and idle time. High *user* time suggests MediaWiki processes are consuming significant CPU resources. High *system* time indicates the operating system itself is busy, potentially due to disk I/O or network activity. Monitoring CPU utilization is often done with tools like top, htop, or dedicated server monitoring software.
CPU Load Average
The load average represents the average number of processes waiting to run on the CPU over a specific period (typically 1, 5, and 15 minutes). A load average equal to the number of CPU cores indicates full CPU utilization. A load average significantly higher than the number of cores suggests processes are queuing up, leading to performance degradation. Understanding Server load is critical for maintaining stability.
Context Switches
Context switches occur when the CPU switches between different processes. A high number of context switches can indicate that the CPU is spending too much time managing processes rather than executing them. This can be caused by excessive process creation or inefficient scheduling. This is often related to Database performance as well.
CPU Cache Hit Ratio
The CPU cache is a small, fast memory that stores frequently accessed data. A high cache hit ratio means the CPU is finding most of the data it needs in the cache, reducing the need to access slower main memory. A low cache hit ratio indicates the CPU is frequently accessing main memory, which can slow down performance. Optimizing MediaWiki configuration can improve cache performance.
Detailed Metric Tables
Here are some tables summarizing typical values and interpretations for these metrics.
| Metric | Typical Range | Critical Threshold | Interpretation |
|---|---|---|---|
| CPU Utilization (%) | 20-60% | >90% | Low utilization indicates ample capacity. High utilization suggests a bottleneck. |
| 1-Minute Load Average | Number of CPU Cores | > (Number of Cores * 2) | Indicates processes are queuing up, potentially causing slowdowns. |
| Context Switches per Second | Varies greatly by workload | > 1000 (sustained) | May indicate excessive process creation or inefficient scheduling. |
CPU Core Specific Metrics
Monitoring individual CPU core performance can reveal imbalances in workload distribution.
| Metric | Description | Importance for MediaWiki |
|---|---|---|
| Instructions Per Cycle (IPC) | Average number of instructions executed per clock cycle. | Higher IPC generally indicates better performance. |
| Clock Speed (GHz) | The rate at which the CPU executes instructions. | Higher clock speed generally means faster processing. |
| Temperature (°C) | The CPU's operating temperature. | Excessive heat can lead to throttling and performance degradation. See Server room cooling. |
Example Server Specifications
The following table provides example server specifications suitable for different MediaWiki installation sizes.
| Installation Size | CPU | RAM | Storage |
|---|---|---|---|
| Small ( < 1000 users) | Intel Xeon E3-1220 v6 (4 cores) | 8GB DDR4 | 256GB SSD |
| Medium (1000-10000 users) | Intel Xeon E5-2680 v4 (14 cores) | 32GB DDR4 | 512GB SSD |
| Large ( > 10000 users) | Dual Intel Xeon Gold 6248R (24 cores each) | 64GB+ DDR4 | 1TB+ NVMe SSD |
Tools for Monitoring
Several tools can be used to monitor CPU performance:
- top: A command-line utility for displaying real-time system information.
- htop: An interactive process viewer, similar to top but with more features.
- vmstat: Reports virtual memory statistics.
- iostat: Reports CPU and disk I/O statistics.
- Dedicated server monitoring software (e.g., Nagios, Zabbix, Prometheus). These often integrate with Alerting systems.
Troubleshooting High CPU Usage
If you observe high CPU usage, consider the following:
- **Identify the process:** Use `top` or `htop` to determine which process is consuming the most CPU. Is it a MediaWiki process (e.g., `php-fpm`, `mysqld`)?
- **Check for slow queries:** Slow database queries are a common cause of high CPU usage. Use the Slow query log to identify and optimize them.
- **Review MediaWiki extensions:** Some extensions can be resource-intensive. Disable or optimize problematic extensions.
- **Optimize MediaWiki configuration:** Adjust settings like `$wgCacheDirectory` and `$wgMainCacheType` to improve caching.
- **Consider scaling:** If the CPU is consistently overloaded, consider upgrading to a more powerful CPU or adding more servers to your cluster. See Load balancing.
Conclusion
Monitoring CPU performance metrics is essential for maintaining a healthy and responsive MediaWiki installation. By understanding these metrics and using the appropriate tools, you can identify and resolve performance bottlenecks, ensuring a positive experience for your users. Remember to regularly review these metrics and adjust your server configuration as needed. Also, consider the impact of Caching strategies on CPU load.
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.* ⚠️