@IndeedEnd March: Wednesday, March 27th …
@IndeedEnd March: Wednesday, March 27th
Video available: http://www.youtube.com/watch?v=MeRHetCMiHg
The goal of Indeed's aggregation engine is to find and retrieve every job in the world, as quickly and accurately as possible. As we described in our previous tech talk, we strive to build products that are simple, fast, comprehensive, and relevant. The world's most comprehensive job search site is fueled by the more than 35 million job postings we process every day, which we deliver to jobseekers within minutes of discovery.
Our original aggregation architecture was implemented using standard patterns. Our growth required levels of scalability, performance, and resilience this architecture simply could not handle. In a case study of scaling for the web, we will discuss how we tackled this problem. We will cover the issues we saw with our original architecture, how we analyzed our options to guide a solution, how we used RabbitMQ as a key component in the new architecture, and benchmarks to evaluate how successful we were.
Speaker Ketan Gangatirkar is the development manager responsible for Indeed's continuous deployment infrastructure as well as its aggregation system.
Speaker Cameron Davison is a software engineer on the aggregation team at Indeed and a graduate of UT Austin. He re-architected Indeed's aggregation pipeline using RabbitMQ to sustain high write volumes, and continues to improve products in the aggregation system to make it run more efficiently.