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Key performance metrics to monitor

 In performance testing, various key metrics are measured to evaluate the behavior and effectiveness of a system under different loads. The selection of specific metrics may vary depending on the type of application and its intended use. Here are some commonly used performance metrics:

  1. Response Time: The time taken for the system to respond to a user request. It includes the server processing time, network latency, and client-side rendering time.

  2. Throughput: The number of transactions or requests processed by the system within a given time frame. It indicates the system's capacity to handle concurrent user requests.

  3. Concurrent Users: The number of simultaneous users or connections the system can support without significant degradation in performance.

  4. Error Rate: The percentage of failed or erroneous transactions or requests compared to the total number of transactions. It helps identify system stability and reliability.

  5. CPU Usage: The percentage of CPU resources utilized by the system during performance testing. High CPU usage may indicate performance bottlenecks.

  6. Memory Usage: The amount of memory consumed by the system under different load conditions. Excessive memory usage can lead to performance issues.

  7. Network Latency: The time taken for data to travel between the client and server over the network. High latency can impact response time and overall system performance.

  8. Database Performance: Metrics such as database query response time, transaction throughput, and database server resource utilization.

  9. Page Load Time: The time taken to load a complete web page, including all its resources (e.g., HTML, CSS, JavaScript, images). It is crucial for web applications and impacts user experience.

  10. Scalability: The system's ability to handle increased loads by adding more resources (e.g., servers, nodes) without a significant performance drop.

  11. Peak Load Capacity: The maximum number of users or transactions the system can handle before it reaches its limit.

  12. Stress Threshold: The maximum load or stress level the system can sustain without causing critical failures or crashes.

These metrics help identify performance bottlenecks, measure system efficiency, and determine whether the system meets performance goals and requirements. It's important to define relevant metrics based on your application's specific characteristics and user expectations.

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