Fangjin Yang covers common problems and failures seen with distributed systems, and discusses design patterns that can be used to maintain data integrity and availability when everything goes wrong.
Yongsheng Wu talks about how to build highly-resilient systems at scale. Wu presents also failure cases that prompted engineers at Pinterest to build such systems, and how they test these systems.
Sangeeta Narayanan looks at the role of containers in simplifying and increasing the reliability of the process of releasing and operating the Netflix software.
Kyle Anderson discusses details on how to tie Mesos, Docker, SmartStack, Haproxy, Git, and Sensu all together into a coherent system that developers can use to ship their code in a self-serve way.
Chris Witeck covers key lessons learned by Citrix Labs as they tackle their goal of customer led innovation, discussing empathy mapping which involves showing off an idea and collecting feedback.
Itamar Syn-Hershko shows using various technologies -Storm, Node.js, Riemann, collectd, D3.js, ELK, PagerDuty, Slack - to power Forter’s service and keep it highly available and under control.
Nate Fink shares how Yammer has changed everything from how they structure teams to the role of managers to how they measure progress so they can not only survive but thrive learning.
Ted Young shares his experience having to build their own solution or choosing an open source project in its infancy, the problems encountered and how they solved them.
Vivian Chandra outlines the benefits of an API they created including how it has helped them automate part of their CRM process and protected them from changes of the CRM system.
Travis Reeder thinks performance, memory, concurrency, reliability, and deployment are key to exploring Go and its value in production. Travis describes how it’s worked for Iron.io.
Brian Holt talks about React, performance issues, some general web performance tips, lessons learned while helping write m.reddit.com using React.
Roy Clarkson and Greg Turnquist discuss using Spring Data REST to build a back-end for a startup, exemplifying with Spring-A-Gram, an app built with Spring Data REST and secured by Spring Security.