Frequently Asked Questions
A: According to Wikipedia , Apdex is an open standard for performance measurement. “Its purpose is to convert measurements into insights about user satisfaction, by specifying a uniform way to analyze and report on the degree to which measured performance meets user expectations.” With other words: it’s a user-experience measurement method.
A: This means if the selected number of visitors would visit your site and browse your pages at the same time, more than half of them would not be satisfied with the time they need to wait for the page to load. This score was calculated by the Apdex open standard, you can read more about this method here.
To calculate this score, we were using 1.5s as Toleration limit and 15s as Frustration limit to divide the users into 3 groups: satisfied users (max. 1.5s loading time), just OK users (between 1.5s and 15s loading time) and frustrated users (15s or more loading time for the page). Applying the Apdex formula resulted a percentage of the total users, who were considered as satisfied with the performance. Failing the test means your Apdex score was under 50, so majority of your visitors were not satisfied with the performance.
A: When you’re visiting a site, your browser is generating a lot of requests to the server in the most cases: these are elements your browser needs to download to be able to build up your page. Each simulated user was constantly loading your website, this can result in a very high number of requests and code-executions.
A: Both of them represents something different. While The “Total” Apdex score represents the Apdex score calculated by each requests, the “home_page” Apdex score is calculated by grouping the requests together which belongs to the same pageload. As an example, if your page needs 10 elements to load your page and all of them are loading under 1s except one, the whole pageload will wait for that one request to finish before the user could see the page. It doesn’t matter if 99% of the requests were loaded under 1s, we should examine the whole pageload-time if we would like to calculate with user-experience, so we grouped the users into thread-groups, and calculated the Apdex score based on the loading time of one thread.
A: We’ve collected tremendous amount of telemetry data during the test. Those charts are trying to summarize them by grouping different data together. The “Over Time” charts are showing the telemetry data against elapsed time, the “Throughput” charts are showing “per second” and “per Requests” data and the “Response Times” charts are showing the response times in different distributions. If you need further explanation or analysis on your results, you can contact us any time at email@example.com , we are happy to help!