Introducing Streamhouse: the open data architecture for AI | Learn More
Testing data streaming applications is always a challenging task. Small, targeted functional tests are easy enough but ensuring that the application performs under different loads, abnormal traffic patterns and in the presence of errors is not so simple. It is not always straightforward, or even permissible, to pull production data for our testing. So what do we do?
In this session, we will first explore the reasons why it is necessary to shape test data in order to properly test our applications. We will then examine the different characteristics that one would want to control when generating the data. Finally we will look at a few of the current crop of tools that go beyond the producer and consumer test clients that come packaged with kafka.
By the end of the talk, you will have an appreciation for the nuances to keep in mind when testing your data streaming application along with a list of tools to try out for your particular use case.