A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda
The shift towards microservisation which can be observed in recent developments of the cloud landscape for applications has led towards the emergence of the Function as a Service (FaaS) concept, also called Serverless. This term describes the event driven, reactive programming paradigm of functional components in container instances, which are scaled, deployed, executed and billed by the cloud provider on demand. However, increasing reports of issues of Serverless services have shown significant obscurity regarding its reliability. In particular, developers and especially system administrators struggle with latency compliance. In this paper, following a systematic literature review, the performance indicators influencing traffic and the effective delivery of the provider's underlying infrastructure are determined by carrying out empirical measurements based on the example of a File Upload Stream on Amazon's Web Service Cloud. This popular example was used as an experimental baseline in this study, based on different incoming request rates. Different parameters were used to monitor and evaluate changes through the function's logs. It has been found that the so called Cold Start, meaning the time to provide a new instance, can increase the Round Trip Time by 15% on average. Cold Start happens after an instance has not been called for around 15 min, or after around 2 h have passed, which marks the end of the instance's lifetime. The research shows how the numbers have changed in comparison to earlier related work, as Serverless is a fast growing field of development. Furthermore, emphasis is given towards future research to improve the technology, algorithms, and support for developers.
Big Data Cogn. Comput.