The Ray Community Pulse Survey, launched by the Ray project team, seeks to gather feedback from its users to guide future developments and enhancements of the Ray framework, which has seen significant growth since its inception at UC Berkeley. The survey aims to understand how users utilize Ray for scaling Python applications and libraries, including machine learning model training, serving, and non-ML workflows like data processing and ETL. With contributions from over 450 contributors across 100+ companies, Ray has integrated with libraries such as Horovod and XGBoost and improved features in Ray Serve and RLlib. To better prioritize features and address user pain points, the survey also explores the usage of new Java and C++ APIs, infrastructure setups, and cluster launch methods. As an incentive, the project offers a $2 donation to one of three charities for each completed survey, emphasizing the value of feedback from both new and long-term users to enhance the Ray experience.