Nathan Marz discusses Storm concepts –streams, spouts, bolts, topologies-, explaining how to use Storms’ Clojure DSL for real-time stream processing, distributed RPS and continuous computations.
John Allspaw discusses fault tolerance, anomaly detection and anticipation patterns helpful to create highly available and resilient systems.
Daniel Jacobson covers the history of Netflix’s APIs, adaptation for the cloud, development and testing, resiliency, and the future of their APIs.
Michael Brunton-Spall talks about various types of system failure that can happen, sharing the lessons learned at the Guardian and measures taken to prevent and mitigate failure.
Joe Armstrong discusses highly available (HA) systems, introducing different types of HA systems and data, HA architecture and algorithms, 6 rules of HA, and how HA is done with Erlang.
Nathan Marz explain Storm, a distributed fault-tolerant and real-time computational system currently used by Twitter to keep statistics on user clicks for every URL and domain.
Jonas Bonér introduces Akka, a JVM platform that wants to address the complex problems of concurrency, scalability and fault tolerance using Actors, STM and self-healing from crashes.
Justin Sheehy talks about failure and the need to prepare for it, giving some real life examples along with techniques implemented in Riak to make it resilient to faults.
Joe Armstrong explains through Erlang examples that message passage concurrency represents the foundation of scalable fault-tolerant systems.
Michael Nygard encourages us to have a failure oriented mindset. He presents many anti-patterns leading to systems instability and failure, accompanied by design patterns that should be used instead.
Ulf Wiger shows typical Erlang programs, patterns that scale well on multicore and patterns that don't, profiling and debugging parallel applications and ensuring correct behaviour with QuickCheck.
In this talk from RubyFringe, Damien Katz explains what drove him to create CouchDB, why he chose Erlang and more.