Load Curve Diagrams

To discover the web application’s maximum possible capability, you must run the same load test program several times, each time with a different number of users.

We recommend increasing the load in each successive test run logarithmically to get a good overview; for example, successive test runs with 1, 2, 5, 10, 20, 50, 100, 200, 500, 1000 .. users.

These test runs can be combined to produce load curves that will provide an excellent overview of the response time behavior, the throughput, and the stability of the web server or web application and how they vary depending on the number of users.

With small loads, the response times are constant and are independent of the number of users. If the load is increased, and thereby the maximum throughput of the server is reached (measured in URL calls per second, which is the web transaction rate - or also called hits per second), the response times will rise in an at least linear relationship with the number of users.

Web pages and/or URL calls, whose response times rise more strongly than others while under load, are potential tuning candidates; that is, the reason for the sudden, strong rise in their response times should be investigated.

Please note that not all web servers or web applications show a linear response time behavior if they are overloaded. A web server may collapse in this situation; in this case, the throughput falls after a specific load point has been exceeded.

To produce the load curves, you must select - from inside the Analyze Load Tests menu - several test runs made with the same load Test program but with a different number of users.

  • Choose the diagram type Load Curve.

  • Click the Compare button.

Overall Load Curves

In the right upper corner, inside the window's title, you can generate a PDF report, and you can also export the performance data.

You can click within the diagrams on the red rhombuses to display the corresponding test run's detailed results.

9 different diagrams are displayed:

Diagram

Description

Diagram

Description

 Average Session Time per User - per Loop

 the cumulative time for a loop per user; that is, the server's response time behavior.

 Web Transaction Rate - Hits per Second

 the number of successfully-executed URL calls per second (hits per second); that is, server throughput.

 Session Failure Rate

 percentage of failed loops; that is server stability.

 Average TCP Socket Connect Time

 average time per URL call to open a network connection; that is, network performance, combined with the TCP/IP stack performance of the server.

 Users Waiting for Response

 average of the number of users who are waiting for a response from the server.

 URL Error Rate

 percentage of failed URL calls.

 HTTP Keep-Alive Efficiency

 percentage of reused network connections.

 SSL Session Cache Efficiency

 percentage of abbreviated SSL handshakes.

 Completed Loops per Minute

 the number of completed loops per minute (sessions per minute).

 Overall Network Throughput

 total network throughput; that is, network load.

Response Time per Page

This menu option displays all web pages' load curves (average response times and 90% percentile value of the response times). Again, you can click within the diagrams on the red rhombuses to display the corresponding test run's detailed results.

Response Time per URL

This menu option displays all URL calls' load curves (average response times and 90% percentile value of the response times). Again, you can click within the diagrams on the red rhombuses to display the corresponding test run's detailed results.

Errors (formerly Session Failures)

This menu option displays a summary of all errors which did occur in the test runs. By clicking on an error counter, the detailed results of the corresponding test run are shown.

 



Can't find what you're looking for? Send an E-mail to support@apica.io