08:30 Registration

09:45 Welcome

10:00 Keynote: Functional (Future) Ruby - Yukihiro Matsumoto

10:30 Break

10:50 From multiple apps to Monolith - #BuildingMonsterservices - Kaja Santro

We are currently transferring our 5 public Rails apps to 1 big monolith. All five of them are job boards with seemingly similar logic but historically grown exceptions and weird peculiarities. The perspective to have multiple data bases managed in 1 app in Rails 6 sparked our idea. The whole story!

11:20 Surrounded by Microservices - Damir Svrtan

How to architect an app that consumes endless data sources via various different protocols? How to support easy swapping of those data sources and how to test it with confidence? Let's checkout how these and many other requirements are fulfilled within the Netflix Studio space.

11:50 Break

12:10 What causes Ruby memory bloat? - Hongli Lai

Ruby apps can use a lot of memory. But why? I set out on a journey of discovery, and not only found evidence that defies common wisdom, but also a simple way to reduce memory usage by 70%.

12:40 It's very effective; using Pokemon to catch all code smells - Melanie Keatley

When learning new skills, connecting what you already know is key. Studying the most common code smells in Ruby and their fixes, exposes a pattern that is similar to how the game mechanic in the popular video game Pokemon works. Grouping certain types and finding the way to beat them.

13:10 Lunch

14:30 Building bricks with MRuby: A journey to MRuby on LEGO robots - Torsten Schönebaum

Constructing robots with LEGO is fun, programming them using Ruby even more. If you ever wanted to know how to start with MRuby on a device that can be changed into anything you can build with LEGO — this talk is for you.

15:00 A gentle introduction to Data Structure Trees - Ashley Jean

In this talk, we’ll dive into Data Structure Trees. We’ll talk about how to work with them and why they’re useful. Also, we’ll discuss how they’re visible in our codebase and look at some modern examples using applications and systems.

15:30 Break

16:00 Closing notes

16:15 Closing keynote: The Miseducation of This Machine - Laura Linda Laugwitz

While machines continue to learn with more sophisticated algorithms and larger amounts of data, humans need to understand how such learning works in order to take its results with the proper grain of salt. Let's make ML tangible and thus help you become a better machine teacher!