Presentation: Understanding Python Memory at Instagram

Instagram server is one of the biggest Python deployments in the world to support more than 700M active users. At Instagram, the computing parallelism is based on multi-processing instead of threading. Memory utilization becomes critical in such model, i.e., with less memory per process, we are able to improve the parallelism hence overall capacity. In this talk, we will start with how Python memory profiling is done at Instagram, what useful insights we got from memory profiling data, and how such insights turned into efficiency wins for Instagram servers. We are also going to share our learnings from tuning and improving Python memory garbage collection.