We will have three talks: The main talk will detail GraphQL (as opposed to REST) and two lightning talks the first will be discussing AssertJ and the second will show how Kafka Streams can be useful when you try to develop real time fraud detection system.
18:00 - 18:30 Rally-up - Light Food, beer and wine - courtesy of our host - Outbrain
18:30 - 18:40 AssertJ - fluent assertions in Java - Danny Bulshtien / Duda
18:40 - 18:55 Lightning: Real-time fraud detection with Kafka Streams - Ofir Sharony / MyHeritage
18:55 - 19:05 A Short break
19:05 - 19:50 GraphQL for API junkies - Yonatan Maman / Outbrain
19:50 - 20:00 A Short break
20:00 - 20:30 An open Discussion
20:30 - ... Wrap up and drinks at the nearest bar
* GraphQL for API junkies - Yonatan Maman / Outbrain *
Never heard of GraphQL? Already have REST APIs? About to build a public API? API junkie ? Come and hear about GraphQL, its advantages and its weak points, see a live demo of GraphQL on-top of existing REST API and examine the Kotlin code I used to do that.
Yonatan is the VP Engineering of Outbrain, and doing software from the happy days of Atari XL. He loves to build new products, to kill tech debt and to educate his team about software craftsmanship.
* AssertJ - fluent assertions in Java - Danny Bulshtien / Duda *
AssertJ provides fluent assertions for Java. In this talk, you will see how using AssertJ can make tests easier to read and easier to write. You will see examples, tips and tricks of using AssertJ.
Danny Bulshtien - Duda
Danny is a software developer at Duda. Loves writing in Java and to write tests.
* Real-time fraud detection with Kafka Streams - Ofir Sharoni / MyHeritage*
In this talk, we'll build a gatekeeper to your website. Our fraud detection system will target various types of malicious activities, such as account takeover, parameter tampering, forbidden access and more. We'll try to identify potential attacks and react to them in near real-time. Addressing this problem in a classical batch fashion will result with a complex, non-scalable nor real-time solution. We'll adjust our clumsy implementation to a modern, stream processing windowed-aggregation, use Kafka Streams as our streaming framework, and end up with a beautiful, clean and maintainable code.
Ofir is a BackEnd team lead at MyHeritage, with a passion for event-driven design and stream processing frameworks. Ofir has acquired most of his experience by planning scalable server-side solutions and developing data pipelines. Ofir has spoke of these ideas in local and global conferences, and wrote about them here: https://medium.com/@ofirsharony