Alexandre Freire discusses what his team has learned through experiments, from the very fundamentals of what a team needs to be successful to Modern Agile engineering techniques.
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
Akshat Vig and Khawaja Shams discuss DynamoDB Streams and what it takes to build an ordered, highly available, durable, performant, and scalable replicated log stream.
Molly Watt and Chris Bush discuss designing for people with specific visual, auditory, cognitive and mobility needs, accessibility features and challenges for certain users engaging digital services.
Oliver Gould discusses Finagle, a library providing a uniform model for handling failure at the communications layer, enabling Twitter to fail, safely and often.
Victor Hu covers the challenges, both technical and cultural, of building a data science team and capability in a large, global company.
Casey Stella talks about discovering missing values, values with skewed distributions and likely errors within data, as well as a novel approach at finding data interconnectedness.
Claudia Perlich presents scenarios in which the combination of different and highly informative features can have significantly negative overall impact on the usefulness of predictive modeling.
Slava Oks talks about SQL Server’s history, high-level architecture and dives into core of I/O Manager, Memory Manager, and Scheduler. Topics include lessons learned and experiences behind the scenes.
Alasdair Allan discusses the security problems when building Internet of Things devices, and the underlying differences between the IoT and the digital Internet that drive those security issues.
Michelle Brush discusses modeling complex systems and architectural changes that could introduce new modes of failure, using examples from embedded systems to large stream processing pipelines.
Ali Basiri discusses the motivation behind ChAP (Chaos Automation Platform), how they implemented it, and how Netflix service teams are using it to identify systemic weaknesses.