Understanding Cost Dynamics of Serverless Computing: An Empirical Study

TL;DR

This empirical study investigates the cost dynamics of serverless computing through expert interviews, revealing its suitability for unpredictable workloads but potential cost issues for high-scale applications, and provides a taxonomy for comparison.

Contribution

It offers the first empirical analysis of serverless cost dynamics and introduces a taxonomy for comparing serverless and traditional cloud costs.

Findings

Serverless is suitable for unpredictable workloads.

High-scale applications may not be cost-effective in serverless.

Provides a taxonomy for cost comparison between serverless and traditional cloud.

Abstract

The advent of serverless computing has revolutionized the landscape of cloud computing, offering a new paradigm that enables developers to focus solely on their applications rather than managing and provisioning the underlying infrastructure. These applications involve integrating individual functions into a cohesive workflow for complex tasks. The pay-per-use model and nontransparent reporting by cloud providers make it difficult to estimate serverless costs, imped-ing informed business decisions. Existing research studies on serverless compu-ting focus on performance optimization and state management, both from empir-ical and technical perspectives. However, the state-of-the-art shows a lack of em-pirical investigations on the understanding of the cost dynamics of serverless computing over traditional cloud computing. Therefore, this study delves into how organizations anticipate the costs of adopting serverless. It also aims to com-prehend workload suitability and identify best practices for cost optimization of serverless applications. To this end, we conducted a qualitative (interviews) study with 15 experts from 8 companies involved in the migration and development of serverless systems. The findings revealed that, while serverless computing is highly suitable for unpredictable workloads, it may not be cost-effective for cer-tain high-scale applications. The study also introduces a taxonomy for comparing the cost of adopting serverless versus traditional cloud.