Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.
Wojciech Seliga shares from experience how complex it can be to deal with thousands of tests -unit, functional, integration, performance- for Atlassian JIRA and what they did to bring it under control.
Ian Robinson discusses the complexity of highly connected data and how graph databases can help, illustrating the talk with practical examples implemented using Neo4j.
Nathan Marz outlines several sources of complexity introduced in data systems - Lack of human fault-tolerance, Conﬂation of data and queries, Schemas done wrong - and what can be done to avoid them.
Stefan Tilkov suggests breaking a system into several subsystems, separating the micro and macro architecture, and addressing various integration issues in order to get a suppler architecture.
Michael Nygard outlines 8 rules for dealing with complex systems: Embrace Plurality, Contextualize Downstream, Beware Grandiosity, Decentralize, Isolate Failure Domains, Data Outlives Applications, Applications Outlive Integrations, Increase Discoverability.