Julien Lavigne du Cadet discusses how Criteo uses Druid: an open-source, real-time data store designed to power interactive applications at scale, covering Druid's architecture and internals.
Kevlin Henney discusses unscalable tests, tricks and tips that make tests more specification-like and scalable to large codebases, and choosing between scenario-based and property-based test cases.
Sylvia Isler presents a microservices case study and lessons learnt - how VMTurbo took the plunge to evolve its monolithic system architecture into a system based on composable microservices.
Diptanu Choudhury discusses the design of Netflix’ distributed scheduler based on Mesos and Titan, focusing on bin packing algorithms, scaling in and out of clusters, fault tolerance, and redundancy.
York Xyander, Bodo Junglas discuss strategies for service discoverability and transparent failover in a microservices architecture, how to achieve zero downtime and an auto-scaling architecture.
Niklas Gustavsson presents Spotify's 2-layer services, and how the UNIX philosophy of composing components that does a single thing well works on a greater scale.
Randy Shoup discusses modern service architectures at scale, using specific examples from both Google and eBay. He covers some interesting lessons learned in building and operating these sites.
Kevlin Henney advises on writing Good Unit Tests (GUTs) by treating testing as a form of communication with multiple levels and forms of feedback.
Emily Green is taking a look at how SoundCloud uses Cassandra. She describes a couple of Cassandra instances, from the point of view of the products and functionality they support.
Francesco Cesarini illustrates how the Erlang way of thinking about problems leads to scalable and fault-tolerant designs, describing 3 ways of clustering Erlang nodes within the server side domain.
John Wilkes shares lessons learned managing clusters at the scale of Google.
Gabriel Monroy demonstrates using Deis to orchestrate Docker deployments, as well as Deis' integration with popular schedulers like Fleet, Mesos, and Kubernetes.