Peter Bakas presents in detail how Netflix has used Kafka, Samza, Docker, and Linux to implement a multi-tenant pipeline processing 700B events/day in the Amazon AWS cloud.
Rachel Davies shares how Unruly keeps their values alive and kicking by employing passionate people. Unruly has grown from a tiny startup to global organisation, being recently acquired by News.
Sam Adams talks about testing at LMAX Exchange, extending functional tests into live monitoring of production through isolation, and moving fast through incremental delivery, quality and automation.
Chris Rasmussen discusses NGA's open source strategy, how contributing to open source is changing government partnerships, and the agency's cultural pivot toward a more unclassified future.
Jan Neumann presents how Comcast uses machine learning and big data processing to facilitate search for users, for capacity planning, and predictive caching.
Aaratee Rao discusses some practical and real world examples of how some well-known hyper growth companies accumulated and managed technical debt.
Nikhil Garg talks about the mental frameworks, processes and tools that allow Quora to strike a good balance and move fast sustainably, both in the short-term and in the long-term.
Roy Rapoport discusses the power of alignment (or lack thereof) using real-world examples, his experience introducing Python in production, and the organizational structures and culture within Netflix
Pete Smith shares from his experience, discussing what it means to fail and how to make the most of it
Ben Hall shares his experience working with Docket for development, testing and deployment into production, discussing scalability, resource management, security and other related issues.
Tony Printezis presents how services are deployed and monitored at Twitter, the benefits of using a custom-built JVM, and the challenges of the use of the JVM in an environment like Twitter.
Sudhir Tonse discusses using stream processing at Uber: indexing and querying of geospatial data, aggregation and computing of streaming data, extracting patterns, TimeSeries analyses and predictions.