Key Performance Metrics for Effective Performance Testing

Key Performance Metrics for Effective Performance Testing

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The success of a website or application is dependent on its performance. This necessitates effective performance testing to ensure high performance. The speed, stability, and scalability are the key areas focused on performance testing. Measuring performance requires the use of certain metrics. With the help of the performance metrics, the effectiveness and the quality of performance can be easily calculated.

Some of the effective metrics to use during performance testing are listed below:

1. Response Time

In the fast-moving world, no one likes waiting. The response time is an important metric to be used during performance testing. The response time metric calculates the total time between the sending of the request and receiving the response. Faster the response time, higher will be the performance.

2. Connections per Second

The connection per the second metric during the performance testing gives information about the TCP/IP connections that are opened and closed every second. If the number of connections per second is less than the hit per second, it indicates effective performance.

3. Average Load Time

Average load time is another important metric during performance testing. The loading time is important, especially from the user’s point of view. The faster is the loading; higher is the performance. The average load time metric calculates the time take to deliver each request.

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4. Latency

The latency metric in performance metrics helps in indicating the time taken for the first response. Latency metric is at times, also referred to as wait metric in performance testing. It is useful to measure the time taken for receiving the first byte as a response. The latency metrics generally help in measuring the performance levels of the web servers.

5. Error Rate

Errors can occur due to connection timeouts, broken connections, or refusals. The error rate metrics indicate the percentage of error generated during the performance testing. The error rate metrics compare the request percentage that ends up in errors in comparison to all the requests. The low error rate is essential for meeting high-performance requirements.

Also Read: A Comprehensive Guide To Software Performance Testing

6. CPU Usage

The metric of CPU usage indicates the amount of CPU utilization. The high CPU utilization is sure to bring in performance problems. With the help of monitoring alerts, the CPU usage can be easily tracked down. The monitoring of CPU usage is a critical aspect of enhancing performance. CPU usage below 70% ensures effective performance.

7. Concurrent Users

The number of users using the web server or an application at a particular time also has an impact on the performance. The concurrent user metrics help in measuring the number of users active at a given point of time.

8. Request Rate

The traffic on the web servers or any given application is an important factor to determine the performance and success rate. The request rate metric of performance testing helps in calculating the number of requests received at a given time. More request rates signal better performance. The requested rate metrics are also helpful in tracking inactivity.

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9. Throughput

The throughput metrics help in measuring the bandwidth amount that gets used up during the performance test. It is indicative of the rate at which a network or a computer receives the request per second. The throughput rate is measured in terms of kilobytes per second.

10. Memory Usage

The memory usage metric determines the amount of memory required to process a request. The metrics also gives information about the amount of memory used during the execution and the free space available.

11. Transactions Passed or Failed

Having an idea about the number of transactions passed or failed during performance testing is important. The transactions passed or failed metrics help in calculating the total number of successful and unsuccessful requests. The higher the number of successful transactions better will be the performance.

Also Read: Top 7 Open Source Load and Performance Testing Tools

12. Hits per Second

A hit per the second metric is usually helpful during the performance testing of the web servers. The hit per the second metric helps in calculating the number of hits on the web server every second during the performance test.

13. Private Bytes

The private byte metrics are used to measure the usage and leaks of memory. The private byte metric indicates the number of bytes that have been allocated by a particular process and connected be shared among the other processes.

Also Read: How Performance Testing Enhances Mobile User Experience?

14. Garbage Collection

The garbage collection metric helps in making you aware of the different performance problems. It provides information about the amount of the unused memory that is returned to the system. Monitoring the garbage collection helps in enhancing performance and efficiency.

Performance testing helps enhance the effectiveness of a website or an application. Understanding the different performance metrics is important for conducting performance testing efficiently. Before any launch or marketing, effective performance testing is a key necessity. Using the appropriate metrics of performance testing can help in bringing customer satisfaction, loyalty, and better retention ability.

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