David Xia explains how Helios testing framework drives integration tests and spins up self-contained environments during test runs, increasing Spotify’s code quality and successful deployments.
Peter Mounce discusses CD at JUST EAT, covering package contracts, feature toggling, team sizes and responsibility, AWS AutoScaling, ELB, CloudFormation, build scripts for server images, etc..
Perry Timms explains how leaders can create a learning strategy, culture, community and energy to power themselves and their people to a future of better understanding and ability.
Lisa Frazier discusses how to adapt as a leader in different contexts by leveraging Agile methods, sharing lessons learnt from rural and urban Australia and experiences from Silicon Valley start-ups.
Simon Raik-Allen explores how alternative Agile Manifesto style statements can be used for other challenges and specifically around the building of a technology platform.
Ryan McKergow discusses how others have implemented scaled retrospectives, what worked and what didn’t work for his company, sharing tips on how to run scaled retrospectives and avoid wasting time.
Sameer Farooqui demos connecting to the live stream of Wikipedia edits, building a dashboard showing what’s happening with Wikipedia datasets and how people are using them in real time.
Joe Duffy shares some of his key experiences from building an entire operating system in a C# dialect and dealing with errors and concurrency robustly, focusing on open source C# and .NET.
Susan Potter describes a toolchain and principles for defining infrastructure in code, versioned with the code, providing repeatable configuration, ephemeral testing and consistent CI/CD environments.
Fabrizio Romano proposes using TDD to transform business requirements into tests, driving code and tests development in harmony.
Cameron Gough discusses Australia Post’s three phases of growth, the hurdles met, the solutions found, learnings, and the techniques that helped them grow, scale and change the organization.
Theo Schlossnagle talks about lessons learned in building an always-on distributed time-series database with aggressive quality of service guarantees, and techniques for dealing with bad machines.