Neville Li and Igor Maravić cover the evolution of Spotify’s event delivery system, discussing lessons learned moving it into the cloud using Scio, a high level Scala API for the Dataflow SDK.
John Langford discusses how to use Vowpal Wabbit in and as a machine learning system including architecture, unique capabilities, and applications, applied to personalized news recommendation.
Neha Narkhede explains how Apache Kafka was designed to support capturing and processing distributed data streams by building up the basic primitives needed for a stream processing system.
Edo Liberty presents some basic concepts and an introduction to the subfields of machine learning and data mining.
John Allspaw provides a glimpse into how other fields handle incident response, including active steps companies can take to support engineers in those uncertain and ambiguous scenarios.
Katherine Kirk shares real life, practical steps and techniques that she's successfully used to help solve tough tech people issues with teams, executives and divisions.
Heidi Howard explores how to construct resilient distributed systems on top of unreliable components. Howard discusses which algorithms are best suited to different situations.
Alex Wilson and Vikki Read talk about their XP journey and how they have evolved from basic XP into a high functioning lean product development environment.
Aysylu Greenberg discusses some of the new architectural patterns from systems she has worked on at Google and the related work that provides insights into the motivations behind them.
Justin Cormack talks about the Docker unikernels build, ship and run pipelines and how the changes they are seeing lead to unikernels in production.
Mitchell Hashimoto takes a look at VMs, which solution architectures worked there, and discusses why these architectures are no longer adequate and what are the solutions in a containerized world.