On Preventively Minimizing the Performance Impact of Black Swans (Vision Paper)

Abstract

Recent episodes of web overloads suggest the need to test system performance under loads that reflect extreme variations in usage patterns well outside normal anticipated ranges. These loads are sometimes expected or even scheduled. Examples of expected loads include surges in transactions or request submission when popular rock concert tickets go on sale, when the deadline for the submission of census forms approaches, and when a desperate population is attempting to sign up for a vaccination during a pandemic. Examples of unexpected loads are the surge in unemployment benefit applications in many US states with the onset of COVID19 lockdowns and repeated queries about the geographic distribution of signatories on the U.K. Parliament's petition website prior to a Brexit vote in 2019. We will consider software performance ramifications of these examples and the architectural questions they raise. We discuss how modeling and performance testing and known processes for evaluating architectures and designs can be used to identify potential performance issues that would be caused by sudden increases in load or changes in load patterns.