Key takeaways. The image below show the concurrent testing. When testing against a server, the single running of Browsing would be a visit consisting of 4 page views and possibly further requests for static content. I am looking at setting up some website load testing scripts and need some help in finding a formula to estimate how many concurrent users are browsing a website at peak times, based on common metrics such as visits, average page views per visit, and average visit duration. K6 offer 50 cloud test for free. which are detected by concurrence testing. Testing is an important part of the web development process. On the other hand, if you're testing a stateless REST API , the concept of concurrent users might not be applicable, and all you really care about is requests per second. Concurrence testing helps improving reliability and robustness of concurrent programs. Alternatively, you can use multiple-user simultaneous testing, or MUST (a term I have from Dennis Wixon). Concurrency Testing is defined as a testing technique to detect the defects in an application when multiple users are logged in. "Hourly Sessions x Average Session Duration (in seconds) / 3,600" is the formula we recommend to get started It’s always good to take the guesswork out of your load testing and test … A second execution of the test with all data and connections (cookies, HTTP-keep-alive, and browser cache) having been reset would result in another visit. But, how many concurrent users should you introduce into your tests? Conclusion. Also, if you calculate the average concurrent sessions between 8 PM and 9 PM on that day when there are more users, the average concurrent sessions are 41.4808. 'Also JMeter concurrent threads are not "concurrent users" as real-life people do pauses between actions on web pages. Test Studio enables customers to gather the performance and stability information of the server, such as throughput, CPU usage and web methods’ response time when there are thousands of concurrent users. In other words monitoring the effect while multiple users perform the same action at the same time. When multiple users are performing the same action at the same time then there can be issues like increased response time, application crashes etc. Concurrent Users. When you have those two values you use this formula to calculate the number of concurrent users to use in your load test: concurrent_users = (peak_hourly_visits * average_session_duration) / 3600 Provided that each simulated user (VU) in your load test behaves realistically (i.e. You can scale for up to 100,000 concurrent users and execute tests using CLI, CI pipelines, or web GUI. Concurrency Testing is also known as multi-user testing. tl;dr — This post is about using Google Analytics to determine how many concurrent users to specify in your load tests. This is almost 2x than the monthly average concurrent users. Concurrent testing is also referred as multi-user testing. If you're testing a website, then the concept of concurrent users, each with their own set of cookies and session data, is indeed applicable. You can initiate a test from 17 geolocation. If you don't set any pauses in your tests then 20 concurrent threads will stand for something like 200-250 concurrent users.' Read on for helpful tips. While designing your load test, look at the right numbers and right time frames. Yes, I am in an argument with a client about this fact. Test results are easy to understand, and you can filter them for in-depth visualization. They are thinking 50 Threads = 50 Users. 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