2023/09/10 by Lukas Böhme, Tom Beckmann, Böhme, Lukas +5 · 1 voice
Computer Science · #Cloud Computing and Resource Management #Data Visualization and Analytics #FOS: Computer and information sciences #Software Engineering (cs.SE) #Software System Performance and Reliability #cs.SE
paper · pdf · doi:10.48550/arxiv.2309.04954
openalex publication_date 2023/09/10 · arxiv published 2023/09/10 · arxiv updated 2023/09/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Understanding and managing monetary cost factors is crucial when developing cloud applications. However, the diverse range of factors influencing costs for computation, storage, and networking in cloud applications poses a challenge for developers who want to manage and minimize costs proactively. Existing tools for understanding cost factors are often detached from source code, causing opaqueness regarding the origin of costs. Moreover, existing cost models for cloud applications focus on specific factors such as compute resources and necessitate manual effort to create the models. This paper presents initial work toward a cost model based on a directed graph that allows deriving monetary cost estimations directly from code using static analysis. Leveraging the cost model, we explore visualizations embedded in a code editor that display costs close to the code causing them. This makes cost exploration an integrated part of the developer experience, thereby removing the overhead of external tooling for cost estimation of cloud applications at development time.