How good is your streaming framework at failure? Does it die gracefully telling you exactly at which point it died? Does it tell you why it died? Does it pick-up where it left off afterwards? Can it easily skip the "erroneous" portions of the stream? Do you always know what was processed and what wasn't? Does it even have to die when process, host, data-center fail?

In this talk we focus on "What Ifs" scenarios and how to evaluate and architect a streaming platform that has high level of resilience. We'll look at Kafka and Spark Streaming as specific examples and share our experience of using these frameworks to process financial transactions answering the questions above along the way. We'll also show examples of tools that we built along our streaming journey which we found invaluable during failure scenarios.