Nathan Marz discusses building NoSQL-based data systems that are scalable and easy to reason about.
Richard Crowley introduces Go standard library's HTTP packages, the relationship between JSON and Go's data structures, and Go's support for reflection, useful to create safe APIs.
Andrew Crump shows how to deploy and scale applications written in a variety of languages (including Clojure and Erlang) to Cloud Foundry.
Summly: An Award Winning Mobile App's Journey to the Cloud with Five-9s Availability on a Shoestring Budget
Eugene Ciurana describes the architectural choices, servers configuration, database, and caching systems that enabled Summly to achieve Five-9-Availability with cross-continental deployments.
Petar Maymounkov introduces Go Circuit, a system that reduces the human development and sustenance costs of complex massively-scaled systems nearly to the level of their single-process counterparts.
Crista Lopes discusses if scale affects the internal structure of projects and whether the popularity of libraries is correlated with internal software metrics such as bug density.
Delivering Performance Under Schedule and Resource Pressure: Lessons Learned at Google and Microsoft
Ivan Filho shares lessons learned during the development and release of several large scale services at Microsoft and Google from the perspective of a performance manager.
Randy Shoup shares war stories from eBay and Google about performance, consistency, iterative development, and autoscaling, connecting them with experiences building KIXEYE's gaming platform.
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
Ben Christensen describes Netflix API's evolution to a web service platform serving all devices and users, the challenges met in operations, deployment, performance, fault-tolerance, and innovation.
Mike Krieger discusses Instagram's best and worst infrastructure decisions, building and deploying scalable and extensible services.
Nick Kolegraff discusses common problems and architecture to support all the phases of data science and how to start a data science initiative, sharing lessons from Accenture, Best Buy, and Rackspace.
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