Efficient large-scale serverless data processing for slow downstream systems

This article discusses efficient serverless data processing for large-scale systems with slow downstream capabilities, specifically focused on education data management using AWS services.

• Highlights the challenges of processing massive amounts of student records across educational systems
• Introduces AWS Step Functions Distributed Map for processing large datasets in parallel
• Presents three concurrency control strategies:
  • External data store locking (using DynamoDB)
  • Queue-based buffering (using Amazon SQS)
  • Step Functions activities for precise rate limiting
• Enables processing of millions of student records efficiently without overwhelming legacy systems
• Provides mechanisms to modernize data processing while respecting infrastructure limitations

The solution allows public sector agencies to process large volumes of semi-structured data more effectively using serverless technologies.