Cost-Profiling Microservice Applications Using an APM Stack

Sjouke de Vries, Frank Blaauw and Vasilios Andrikopoulos ()
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Sjouke de Vries: Researchable BV, 9747 AN Groningen, The Netherlands
Frank Blaauw: Researchable BV, 9747 AN Groningen, The Netherlands
Vasilios Andrikopoulos: Computer Science Department, Faculty of Science and Engineering, University of Groningen, 9747 AG Groningen, The Netherlands

Future Internet, 2023, vol. 15, issue 1, 1-21

Abstract: Understanding how the different parts of a cloud-native application contribute to its operating expenses is an important step towards optimizing this cost. However, with the adoption and rollout of microservice architectures, the gathering of the necessary data becomes much more involved and nuanced due to the distributed and heterogeneous nature of these architectures. Existing solutions for this purpose are either closed-source and proprietary or focus only on the infrastructural footprint of the applications. In response to that, in this work, we present a cost-profiling solution aimed at Kubernetes-based microservice applications, building on a popular open-source application performance monitoring (APM) stack. By means of a case study with a data engineering company, we demonstrate how our proposed solution can provide deeper insights into the cost profile of the various application components and drive informed decision-making in managing the deployment of the application.

Keywords: cloud native applications; microservices; APM; observability; monitoring; cost profiling (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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