John Hughes discusses automated techniques that can improve testing, with war stories from Ericsson, Klarna and Volvo Cars, showing how to nail the hard stuff.
Nellwyn Thomas discusses how Etsy is using A/B testing, how Etsy's data-driven culture has evolved over time and how continuous delivery and big data can coexist.
Fabrice Aresu discusses the challenges faced using HTML5 and data visualization at a large European Investment Bank, covering performance, architectural & design choices, and lessons learnt.
Shawn Gandhi provides an overview of the key scenarios and business use cases suitable for real-time processing, and how developers are using AWS Kinesis to shift from a traditional batch-oriented approach to a continual real-time data processing model.
Máté Nádasdi presents how Ustream uses unit testing and continuous integration for the front-end to ensure the website’s stability and growth.
Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.
Paul Hill presents a case study of building an API with a short deadline using Node.js, WebSocket, MongoDB, JSON, Promises, Swagger, Memcached, Varnish and Hypermedia ReST.
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications: Physician Finder, Symptom Checker and WebMD Runtime.
Oliver Wegner, Stefan Tilkov show how OTTO, Germany’s largest online fashion retailer, used a system-of-systems approach to enable modular, parallel development of its ambitious shop relaunch.
Sponsored by Twilio. Matt Makai explores why deployments are difficult and shows solutions with case studies on how other organizations cut their production deployment times down from months to hours.
Darren Hobbs shares lessons learned building polyglot systems, the technology choices made. mitigating risk and delivering value.
Marcel Kornacker presents a case study of an EDW built on Impala running on 45 nodes, reducing processing time from hours to seconds and consolidating multiple data sets into one single view.