Achieving Concurrency Control: Practical Throttling Techniques for AWS Lambda

Abstract

This technical paper explores nuanced approaches for managing concurrency in Lambda functions, shedding light on the intricacies of AWS services like SQS and Kinesis. It underscores the significance of reserved concurrency to regulate function execution, acknowledging its effectiveness while cautioning about its limitations, particularly in scenarios requiring scalable solutions. The focus extends to the advantages of SQS as a pull-based service, emphasizing its built-in concurrency control and dynamic scalability capabilities. The paper then delves further into Kinesis data streams, showcasing the distinctive architecture of shard-based scaling and introducing parallelization factors for precise control over Lambda concurrency. Notably, these concurrency control strategies are presented as a means to scale Lambda and as a mechanism to manage traffic downstream, considering potential technical constraints. The discussion highlights multiple factors in selecting an appropriate messaging service: cost, message replay capability, error-handling mechanisms, message processing order, and concurrency management. Collectively, these insights serve as a comprehensive reference for architects and developers striving to create efficient and scalable serverless applications within the AWS environment, addressing Lambda scalability and downstream traffic control challenges.