This document discusses Knewton's use of ZooKeeper and PettingZoo to implement distributed machine learning on a Python cluster. It begins by explaining what ZooKeeper is and how it provides services for distributed synchronization. It then discusses the state of ZooKeeper libraries for Python, including incomplete bindings and lack of high-level recipes. PettingZoo is introduced as Knewton's library that implements common ZooKeeper recipes for Python, allowing their machine learning models to be sharded and scaled across multiple machines. Distributed discovery, distributed bags, leader queues, and role matching are highlighted as key recipes that enable dynamic reconfiguration and load balancing of their distributed system.