44. AWS Glue Auto Scaling Tutorial | Dynamically Scale Workers & Executors in Glue ETL Jobs

code used : https://github.com/bedwalsanjay/aws-d... In this video, you'll learn how AWS Glue Auto Scaling works and how it can automatically add or remove executors during the execution of a Glue ETL job. Auto Scaling helps optimize resource utilization, reduce costs, and improve job performance by allocating compute resources based on the actual workload. In this hands-on demonstration, I show: What AWS Glue Auto Scaling is How Auto Scaling works in Glue ETL jobs Difference between fixed workers and Auto Scaling How executors are added dynamically during job execution Monitoring worker and executor scaling in Glue job runs Benefits of Auto Scaling for cost optimization Best practices for using Auto Scaling in production workloads This tutorial is useful for AWS Data Engineers, Data Architects, ETL Developers, and anyone preparing for AWS Data Engineering interviews or certifications. If you're working with AWS Glue, Spark, PySpark, Data Lakes, Amazon S3, Redshift, or modern data engineering pipelines, understanding Auto Scaling is an important skill for building efficient and cost-effective ETL solutions.