Ray Serve is a distributed serving library built on the Ray framework. It enables scalable serving of models and business logic, including complex, composite model pipelines. The library is designed for scaling compute-heavy machine learning workloads across distributed clusters. Ray Serve integrates with the broader Ray ecosystem for parallel computing. It focuses on providing scalability for training and deploying machine learning models and applications.
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overview
Ray Serve is a distributed serving library built on the Ray framework. It enables scalable serving of models and business logic, including complex, composite model pipelines. The library is designed for scaling compute-heavy machine learning workloads across distributed clusters.
Ray Serve integrates with the broader Ray ecosystem for parallel computing. It focuses on providing scalability for training and deploying machine learning models and applications.
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