This blog post explores scaling up a pipeline that generates text embeddings using Ray Data and Sentence Transformers. The author demonstrates an easy migration from a pandas-based pipeline to a Ray Data-based pipeline, highlighting significant performance improvements with minimal code changes. The improved Ray Data pipeline delivers a 10x performance improvement over the naive implementation and allows for distribution of workload across a cluster of machines with GPUs and CPUs compared to running pandas on a single machine.