Application Deployment Strategies for Reducing the Cold Start Delay of AWS Lambda

Serverless computing has emerged in recent years as the new computing paradigm adopted by key players in the industry for software development. This new paradigm has seen rapid growth in adoption due to its unique billing model and scaling characteristics. Public cloud providers such as Amazon Web Services (AWS) offer several configurations and language runtimes for their serverless functions. Although extensively explored by the research community, this field still lacks current studies that address the many challenges developers face when leveraging serverless functions for real-world applications. One of these challenges that are often overseen by many programmers is the cold start problem which is present in any serverless application. For this reason, we propose the first study to characterize the underlying cold start impacts caused by the choice of language runtime, application size, memory size and deployment type on AWS Lambda. In this paper, we analyze the performance of the container-based deployment and ZIP-based deployment of AWS Lambda using a variety of language runtimes and applications running with different function configurations; then we propose guidelines for developers and cloud managers to consider when deploying/managing the workloads on the cloud.