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. As the name indicates, with MUST, you test multiple users at the same time so you get done sooner. When multiple users are performing the same action at the same time then there can be issues like increased response time, application crashes etc. 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. 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. Concurrent testing is also referred as multi-user testing. While designing your load test, look at the right numbers and right time frames. Concurrency Testing is also known as multi-user testing. which are detected by concurrence testing. Concurrence testing helps improving reliability and robustness of concurrent programs. Concurrency Testing is defined as a testing technique to detect the defects in an application when multiple users are logged in. Test results are easy to understand, and you can filter them for in-depth visualization. "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 … If you don't set any pauses in your tests then 20 concurrent threads will stand for something like 200-250 concurrent users.' This is almost 2x than the monthly average concurrent users. K6 offer 50 cloud test for free. In other words monitoring the effect while multiple users perform the same action at the same time. 'Also JMeter concurrent threads are not "concurrent users" as real-life people do pauses between actions on web pages. 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. The image below show the concurrent testing. Yes, I am in an argument with a client about this fact. Testing is an important part of the web development process. They are thinking 50 Threads = 50 Users. 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. Key takeaways. But, how many concurrent users should you introduce into your tests? tl;dr — This post is about using Google Analytics to determine how many concurrent users to specify in your load tests. Concurrent Users. You can scale for up to 100,000 concurrent users and execute tests using CLI, CI pipelines, or web GUI. You can initiate a test from 17 geolocation. 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. Modern web applications employ a variety of web services and many pages have AJAX calls to RESTful web … Alternatively, you can use multiple-user simultaneous testing, or MUST (a term I have from Dennis Wixon). 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. Read on for helpful tips. 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. Conclusion. 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