Leveraging Event - Based Architecture, AWS Step Functions, AWS Batch, and DynamoDB to Run ETL or ELT Jobs Concurrently While Allowing Granular Replay Capabilities

Traditional Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) jobs are often perceived as hardware - intensive, necessitating the use of persistent EC2 instances to handle large data sets. This conventional approach presents challenges, including the need for manual monitoring of long -running jobs and the inability to replay jobs from specific points or stages in the ETL/ELT process. Additionally, the intricate nature of ETL/ELT phases, each with potential failure points, complicates the operational management of these workflows. AWS provides a suite of serverless services such as EventBridge, S3, SNS, Lambda, Step Functions, and Batch that can be leveraged to create a scalable and resilient ETL/ELT architecture. This paper explores how integrating these services can transform traditional ETL/ELT processes into a more flexible, state -managed saga (1) with granular replay capabilities. The goal is to offer insights into how this architecture using the above -mentioned AWS services can enhance traditional data processing workflows, focusing on concurrent job execution and precise error recovery, especially targeted for Software Architects and Engineers.