Caitie McCaffrey talks about scaling game backend services for Halo 4 and others, stress & performance testing, the Orleans actor framework, and the future of distributed programming.
Natalia Chechina explains the challenges of scaling distributed Erlang beyond a certain number of systems and how SD Erlang helps to overcome those problems.
Peter Bourgon discusses distributed programming with commutative replicated data types (CRDTs), how they work, what problems they solve, and his experience with using the Go language at SoundCloud.
Aviran Mordo explains the service oriented architecture behind web hoster WiX, when to choose MySQL vs NoSQL products, introducing Scala, and much more.
Francesco Cesarini and Viktor Klang explain the motivation behind the Reactive Manifesto and what exactly it brings to the table. Also: what Erlang and Scala/Akka can learn from each other.
Alex Papadimoulis shares his thoughts on distribution vs delivery, decoupling infrastructure (pull) from application (push) deployments and keeping delivery systems simple, especially for web scale applications. In particular Alex describes three different types of roll-outs: Live, Rolling and Parallel and their applicability (cloud-based delivery vs in-house servers).
In this InfoQ interview, Michael Nygard explores some of the available loopholes in the CAP theorem helping architects to engineer distributed systems that meet their needs. He also discusses new patterns he’s observed since his book, Realease IT and shares his thoughts on continuous delivery, DevOps and ALM.
Ken Little talks about scaling Tumblr to keep up with their blogging users: scaling the data model, sharding, their PHP frontend and the Scala backend, and much more.
Serkan Piantino explains how Facebook has managed to scale up, what types of errors occur in an architecture that size and how to handle them, RAM vs disk, and much more.
Rich Hickey and Justin Sheehy talk about scalability and transactionability of datastores. They explain tradeoffs for achieving read and/or write scalability on top of Datomic and Riak.
Attila Szegedi talks about performance tuning Java and Scala programs at Twitter: how to approach GC problems, the importance of asynchronous I/O, when to use MySQL/Cassandra/Redis, and much more.
Martin Thompson and David Farley discuss how to use the scientific method to create high performance systems by measuring performance and adapting the implementation to approach the limits of current hardware. The disruptor architecture is an open sourced result of their work at low-latency, high throughput systems for the retail trading platform of LMAX Ltd.