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Scalability testing

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Scalability Testing, is the testing of a software application to measure its capability to scale up or scale out in terms of any of its non-functional capability.

Performance, scalability and reliability testing are usually grouped together by software quality analysts.

The primary goals of scalability testing are to determine the user limit for the Web application, determine and end user experience under load, for example, can users access a web page in a timely manner. Another goal is to determine server-side robustness and degradation i.e. Will the server crash if it is under a heavy load? [1]

Dependent on the application that is being tested, different parameters are tested. If a webpage is being tested, the number of simultaneous users making requests of the site would be tested. [2] Also dependent on the application being tested is the attributes that are tested - these can include CPU usage, network usage or user experience [3] which can be tested by response times in the case of web pages.

Successful testing will project most of the issues which could be related to the network, database or hardware/software. [4]

How to Create a Scalability Test

When creating a new application, it is difficult to know the number of users it will have at any given time. Although an estimate can be made, it is not a definite number. An issue with an increasing number of users is that it can create new areas of failure. For example, if you have 10,000 new visitors, it’s not just access to an application that could be a problem; you might also experience issues with the database where you need to store all the data on these new customers.[5]    

This is why when creating a scalability test, it is important to scale up in increments. These steps can be split into small, medium and high loads.

The environment should be constant throughout testing in order to provide accurate and reliable results. If the testing is a success, we should see a proportional and linear change in performance. For example, if we double the users on the system, we should see a drop in user end performance of 50% [6]

Alternatively, if measuring system statistics such as memory or CPU usage over time, this may have a different graph that is not proportional as users are not being plotted on either axis.

References

  1. ^ "Planning for Load Testing". docs.oracle.com. Retrieved 2015-10-23.
  2. ^ "Scalability Testing". Performance Blog. Retrieved 2015-10-25.
  3. ^ "What is Scalability Testing? | Software Testing Class". www.softwaretestingclass.com. Retrieved 2015-10-25.
  4. ^ Joshi, Prateek. "Why Do We Need Performance Testing?". Perpetual Enigma. Retrieved 2015-10-25.
  5. ^ "Discovering the right metrics for scalability testing". www.theserverside.com. Retrieved 2015-10-25.
  6. ^ "IBM Cognos Proven Practices: Designing a Successful Performance and Scalability Test for IBM Cognos BI". www.ibm.com. 2011-11-17. Retrieved 2015-10-25.


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