Probabilistic algorithms are an awesome and underused tool for engineers building very large scale systems. Making calculations or consistency guarantees “with high probability” instead of “exactly” is often easier to scale and surprisingly reliable. This talk presents two widely useful probabilistic algorithms which have seen successful deployments at massive scale: Bimodal Multicast, an algorithm used for reliably sending messages to a widely-distributed network of servers; Locality-sensitive Hashing, an algorithm used for calculating the similarity of vectors, which can be used in nearest-neighbor search, recommendation systems, and plagiarism detectors.
Tyler McMullen is CTO of Fastly, where he’s responsible for the system architecture and leads the company’s technology vision. As part of the founding team, Tyler built the first versions of Fastly’s instant purging system, API, and Real-time Analytics. Before Fastly, Tyler worked on text analysis and recommendations at Scribd. A self-described technology curmudgeon, he has experience in everything from web design to kernel development, and loathes all of it. Especially distributed systems.