AWS Glue is Amazon's serverless data integration service that orchestrates extract, transform, and load (ETL) workflows at scale. Built on Apache Spark, it eliminates infrastructure management while providing a Data Catalog as a central metadata repository, crawlers for schema inference, and visual and code-based ETL authoring. AWS Glue excels at preparing messy, semi-structured data for analytics—whether through batch jobs, streaming pipelines, or visual no-code transforms. Understanding the distinction between DynamicFrames (Glue's schema-flexible abstraction) and Spark DataFrames, mastering job bookmarks for incremental processing, and leveraging performance optimization techniques like pushdown predicates are essential for cost-effective, production-grade Glue implementations.