Load Testing Statistics 2024 – Everything You Need to Know

by

Are you looking to add Load Testing to your arsenal of tools? Maybe for your business or personal use only, whatever it is – it’s always a good idea to know more about the most important Load Testing statistics of 2024.

My team and I scanned the entire web and collected all the most useful Load Testing stats on this page. You don’t need to check any other resource on the web for any Load Testing statistics. All are here only 🙂

How much of an impact will Load Testing have on your day-to-day? or the day-to-day of your business? Should you invest in Load Testing? We will answer all your Load Testing related questions here.

Please read the page carefully and don’t miss any word. 🙂

On this page, you’ll learn about the following:

Best Load Testing Statistics

☰ Use “CTRL+F” to quickly find statistics. There are total 34 Load Testing Statistics on this page 🙂
  • The Statistics page displays the number of tests, requests, fails, median, 90%ile, Min, Max and Average duration, RPS and failures. [0]

Load Testing Latest Statistics

  • Using the nearest rank method on results with fewer than 100 distinct values can result in the same value being used for more than one Percentile which is another reason to ensure that you use large sample sizes when analysing performance test results. [1]
  • The 90th Percentile, as an example, is the value in your results below which 90% of the response times are found, with 10% being above the 90th Percentile. [1]
  • This, alongside the 95th and 99th Percentile are commonly used in performance results analysis as they account for any significant number of longer response times that would not be found using the average whilst still allowing for any anomalies to be ignored. [1]
  • To get our 90th Percentile we take the value below the tenth value which is in row twelve in our example which matches our JMeter aggregate report value. [1]
  • The 95th Percentile will be in the value below our fifth value which will be row seven and. [1]
  • the 99th Percentile will be the value below the top one. [1]
  • When compared with performance data obtained from extensive performance tests, PT4Cloud provides testing results with 95.4% accuracy on average while reducing the number of test runs by 62%. [2]
  • We also propose two test execution reduction techniques for PT4Cloud, which can reduce the number of test runs by 90.1% while retaining an average accuracy of 91%. [2]
  • 90th percentile, COUNT, Min, Last, Sum,. [3]
  • 75th percentile, Median, Standard Deviation, 25th percentile. [3]
  • The slowest response time, in milliseconds, the 90th percentile receives. [4]
  • The response time for the 90th percentile 95% line. [4]
  • The response time for the 95th percentile 99% line. [4]
  • The response time for the 99th percentile. [4]
  • The response time of the transaction for the VU at the 50% percentile. [4]
  • Enter 3 in the edit box next to the percent/users option and select users. [5]
  • Enter 6 in the edit box next to the percent/users option and select users. [5]
  • The percentile value for 95% Page Time report that 95% of the pages completed in less than this time in onds. [6]
  • The percentile value for 95% Test Time report that 95% of the tests completed in less than this time in onds. [6]
  • The percentile values report the following transaction information 90% of the total transactions were completed in less than
  • 95% of the total transactions were completed in less than
  • Efforts are ongoing in different countries to scaleup access to viral load testing to meet the Joint United Nations Programme on HIV and AIDS target of achieving 90% viral suppression among HIV infected patients receiving antiretroviral therapy. [7]
  • According to Gartner, The average cost of network downtime is around $5,600 per minute. [8]
  • some overview information (100.00%). [9]
  • To learn more about the metrics k6 collects and reports, read the Trend metrics collect trend statistics for a series of values. [9]
  • According to the Locust documentation, Python 3.6 or a later version is currently required. [0]
  • You get the median and 95%ile to the number of users. [0]
  • In the user class, we have defined only 3 methods that are equally likely to be executed – an authorized get request ‘/users’, the same unauthorized request, and an unauthorized get request ‘/comments’. [0]
  • That’s why it is not recommended to define service level agreements using averages; instead, have something like “The service must respond in less than 1 second for 99% of cases. [10]
  • For example, the 90th percentile indicates that 90% of the sample is below that value and the rest of the values (that is, the other 10%). [10]
  • Some percentiles have particular names, such as p100 which is the maximum (100% of the data is below this value). [10]
  • The percentile is typically used to establish acceptance criteria, indicating that 90% of the sample should be below a certain value. [10]
  • Observe the percentile values and define acceptance criteria based on that, keeping in mind that if you select the 90th percentile, you’re basically saying,“I don’t care if 10% of my users experience bad response times”. [10]

I know you want to use Load Testing Software, thus we made this list of best Load Testing Software. We also wrote about how to learn Load Testing Software and how to install Load Testing Software. Recently we wrote how to uninstall Load Testing Software for newbie users. Don’t forgot to check latest Load Testing statistics of 2024.

Reference

  1. performancelabus – https://performancelabus.com/load-testing-using-locust/.
  2. octoperf – https://octoperf.com/blog/2020/08/16/statistical-analysis/.
  3. acm – https://dl.acm.org/doi/10.1145/3338906.3338912.
  4. smartbear – https://support.smartbear.com/readyapi/docs/performance/results/metrics/statistics.html.
  5. blazemeter – https://www.blazemeter.com/blog/understanding-your-reports-part-4-how-read-your-load-testing-reports-blazemeter.
  6. oracle – https://docs.oracle.com/cd/E91471_01/ATSGS/chap4_olt_fm.htm.
  7. microsoft – https://docs.microsoft.com/en-us/visualstudio/test/load-test-results-summary-overview.
  8. nih – https://pubmed.ncbi.nlm.nih.gov/28059956/.
  9. loadninja – https://loadninja.com/load-testing/.
  10. k6 – https://k6.io/docs/getting-started/results-output/.
  11. dzone – https://dzone.com/articles/3-performance-testing-metrics-every-tester-should.

How Useful is Load Testing

One of the key benefits of load testing is its ability to predict how a system will perform under certain conditions before it goes live. By gradually increasing the number of users, transactions, or data volumes that the system can handle, load testing allows developers to identify performance issues early on in the development process and address them proactively. This can save valuable time and resources by avoiding costly performance bottlenecks and downtime once the system is in production.

Moreover, load testing can help uncover hidden performance issues that may not be apparent during regular testing. For example, a system may function correctly under normal load conditions but struggle when faced with a sudden surge of traffic or a particularly complex transaction. By subjecting the system to a variety of load scenarios, load testing can reveal these weaknesses and enable developers to implement targeted optimizations to improve overall performance.

Another important aspect of load testing is its role in capacity planning. By determining the maximum load a system can handle without performance degradation, load testing can help organizations plan for future growth and expansion. Understanding the limits of a system’s scalability allows developers to make informed decisions about resource allocation, infrastructure upgrades, and other strategic investments to support the system’s long-term needs.

In addition to improving performance and scalability, load testing can also enhance the overall user experience. A system that responds quickly, reliably, and consistently to user interactions is more likely to retain and engage users, leading to higher levels of satisfaction and loyalty. By identifying and addressing performance issues early on, load testing can help ensure that users have a seamless and enjoyable experience when interacting with a system, which ultimately benefits both the organization and its customers.

Overall, load testing is a valuable tool for ensuring the stability, reliability, and performance of software systems. By simulating real-world load conditions, identifying performance bottlenecks, and optimizing system performance, load testing enables developers to deliver a more robust product that meets the needs of end-users. Whether it’s predicting system behavior, uncovering hidden performance issues, planning for capacity growth, or enhancing the user experience, load testing plays a crucial role in the development process and is an essential component of any comprehensive testing strategy.

In Conclusion

Be it Load Testing benefits statistics, Load Testing usage statistics, Load Testing productivity statistics, Load Testing adoption statistics, Load Testing roi statistics, Load Testing market statistics, statistics on use of Load Testing, Load Testing analytics statistics, statistics of companies that use Load Testing, statistics small businesses using Load Testing, top Load Testing systems usa statistics, Load Testing software market statistics, statistics dissatisfied with Load Testing, statistics of businesses using Load Testing, Load Testing key statistics, Load Testing systems statistics, nonprofit Load Testing statistics, Load Testing failure statistics, top Load Testing statistics, best Load Testing statistics, Load Testing statistics small business, Load Testing statistics 2024, Load Testing statistics 2021, Load Testing statistics 2024 you will find all from this page. 🙂

We tried our best to provide all the Load Testing statistics on this page. Please comment below and share your opinion if we missed any Load Testing statistics.

Leave a Comment