Challenge: Your scripting path brings you to a page that has multiple drop-down lists with similar source structure. You need to randomly select a value from both lists what will be used later in the script.
If you view the source of this page you will see that it has 2 drop down lists. The values in each are structured in the following way: <option value=”ABCD”>ABCD</option>.
The other day I decided to test the performance of my SSD (solid state device) against the performance of the hard drive in my home desktop. As expected the SSD device performed much better than the hard disk. I was surprised to find that the performance of the hard disk was different as you move across the disk. A little time on Google and I found three interesting facts.
You will encounter situations when you are asked to test an application / websites that will have unknown usage. Common situations causing unknown usage are first year applications or increased marketing for an application.
The purpose of this article is to give performance engineers a starting point to create a load profile (used in testing) based on incomplete production usage or projections.
You are asked to test an eCommerce application. Your are given the following data on projected production usage:
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After some tweaks we were able to run 5000 users on a single load generator with the Neoload 64-bit agent (v3.2.4) for windows on both Windows 2008 R2 64-bit and Windows 7 64-bit.
From past experience we have observed that 1 simple http/html user in Neoload uses 2-3 MB of memory. To meet our target of 5000 VUs per load generator we build out the load generators to have 12 GB of Ram. 2 GB was allocated for the OS and the other 10 GB was allocated for the Neoload JVM. Next you have to configure Neoload to use the 10 GB of memory.
This applies to LR 11.x and LR 9.x using the web (http/html) protocol.
Sometimes it’s necessary in loadrunner to capture a large amount data with a web_reg_save_param function. Let’s say we want to capture an entire page response into a param for data extraction.
