Processing over 10 billion messages per day, PayPal's product performance tracking platform is one of the busiest systems in PayPal. And it is all constitutes an end-to-end reactive data processing pipeline consisting of Akka Streams, Kafka, Spark and Druid components.
In this session, we will share our experiences putting together this pipeline in real life. We will address the technical and the organizational challenges of converting a well-established team into this reactive mindset. We will show how we channel the enthusiasm and the energy we had into large-scale adoption. We will also highlight economic benefits derived from greater resource utilization inherent with reactive systems adoption.
This session puts explicit and implicit lessons we have learned into a single narrative useful for both beginner and intermediate audiences, builders and managers alike, helping contextualize conceptual and practical aspects of switching to reactive systems.
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PayPal, Senior member of technical staff and architect
At PayPal, my current role is a senior member of technical staff and architect. For the past four years, I've been responsible for product performance tracking and experimentation eco-systems at PayPal's Core Platform Services division. Prior to that, I was lead solution architect at PayPal's Data Technology division responsible for implementing Big Data platforms. Overall, I have close to thirty years of experience in various industries and companies including household names like SAP, Motorola, Bristol-Myers Squibb, several less known Silicon Valley startups and, for the last 8 years, PayPal. Originally from the former Soviet Union republic of Ukraine, I got my masters in computer science at Tallinn University of Technology in Estonia, where I also started my professional career. I lived and worked in Israel for close to five years prior to coming to California about 20 years ago.