Localhost: Bonnie Eisenman

Abstract: Caching data is awesome, but introduces new problems. How do you balance availability against correctness when you need to worry about consistency across data centers, unreliable underlying data stores, or race conditions in your request path? In this talk, I'll start with an overview of naive caching strategies, the problems they solve, and the ways they can backfire, including real stories from production experience with services-based architectures. Then, I'll discuss a relatively simple augmentation to existing cache strategies - dynamically scaled TTLs - that can defend you against inconsistent cached data, and let you cheat the CAP Theorem to boot!

About the speaker: Bonnie came to the Recurse Center in early 2018 and worked on generative jigsaw puzzles in Clojure. She is currently a Senior Software Engineer at Twitter and a member of the hacker space, NYC Resistor. She has previous experience at Codecademy, Fog Creek Software, and Google.

Bonnie is the author of Learning React Native, an O'Reilly book on building native iOS and Android applications with JavaScript. In her spare time, she enjoys learning languages, sewing, and knitting.

Find her on Twitter: @brindelle.