Jeremy Edberg shares some of the lessons learned scaling Reddit, advising on pitfalls to avoid.
Nathan Marz shares lessons learned building Storm, an open-source, distributed, real-time computation system.
Trevor Lalish-Menagh shares his experience introducing Kanban, what has worked and what hasn’t.
Andrew Godwin tells Lanyrd’s story, covering the technology stack, tricks used, and what they would do differently if they could start afresh.
Jay Kreps discusses the evolution of LinkedIn's architecture and lessons learned scaling from a monolithic application to a distributed set of services, from one database to distributed data stores.
Marc Frons discusses the New York Times’ digital subscription model. Rajiv Pant shares their experiences transitioning to continuous delivery, and using NodeJS, Scala, cloud and big data.
Benjamin Mitchell shares experiences gained working with teams over the last five years, highlighting mistakes that were made following simplistic guidance and outlining key examples that worked.
Paul Downey explains what they did to redirect all traffic from DirectGov and Business Link to gov.uk, along with the tools, techniques and testing involved for the operation to succeed.
Tony Tam shares tips for modeling data with MongoDB for a fast and scalable system based on his experience migrating billions of records from MySQL to MongoDB.
Mike Solomon shares some of the experiences and lessons learned scaling YouTube over the years.
OpenStack Extensions: Challenges and Lessons Learned in the Development and Governance of Extensible REST Services
Jorge Williams shares some of the challenges and lessons learned while adding extensions to OpenStack.
Francesco Cesarini shares business lessons learnt while growing Erlang Solutions from a one man band to a multinational company with 70 employees, offices in 3 countries, and clients on 5 continents.