Chapter 1: AI in Performance Testing

Performance testing has always been a time- and effort-consuming process. Recording or writing scripts takes time. Parameterizing and correlating them takes even more time. And when the test execution is complete, you end up staring at hundreds of metrics trying to figure out what went wrong and where.

AI does not replace any of that work. It does a lot of it for you, or at least gets you most of the way there much faster than doing it manually.

In this chapter you will learn:

• Where AI fits in the performance testing lifecycle and where it does not.
• What problems AI is actually good at solving in the performance testing context.
• What to watch out for because AI gets things wrong too, and in performance testing that can be expensive.

By the end of this chapter, you will have a clear picture of where AI adds value, which will provide more context for the rest of this guide.

Now, let’s move on to Where AI Fits In.