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.
Tamar Bercovici presents Box’s transition from a single MySQL database to a fully sharded MySQL architecture, all the while serving 2 billion queries per day.
Zoltan Toth-Czifra shares scalability lessons learned at Softonic, a company that has developed and grew along with the Internet for over 15 years.
Joshua Suereth designs a scalable distributed search service with Akka and Scala using actors, and covering practical aspects of how to scale out with Akka’s clustering API.
Michael Hausenblas introduces Apache Drill, a distributed system for interactive analysis of large-scale datasets, including its architecture and typical use cases.
Peter Boros discusses a MySQL architecture useful for the majority of projects, backup, online schema changes, reliability and scalability issues, and basics of sharding.