Detecting anti-patterns in a MSA using distributed tracing

Detecting anti-patterns in a MSA using distributed tracing at ING

Master thesis (2022)

Authors

N.E. Hullegien Electrical Engineering, Mathematics and Computer Science

Contributors

Luis Cruz Software Engineering - EEMCS (supervisor 1)
A. van Deursen Software Technology (supervisor 1)
A Katsifodimos Web Information Systems - EEMCS (supervisor 2)
Pieter Vallen ING (supervisor 1)
Kevin Van Der Vlist ING (supervisor 1)
Jonck van der Kogel ING (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Nils Hullegien
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Published Date

05-07-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Microservice architectures (MSA) have become a dominant architectural style choice in the service oriented software industry. Because of this, as with any other system, some unoptimized approaches might creep into architectures. These are what we call anti-patterns, they can be considered the opposite of design patterns. Furthermore, a microservice architecture can quickly grow to an immense scale due to the number of services.

In this work, we present Luduan, a tool created within ING that provides engineers with insights into their MSA. Using different graph metrics and tracing data, we determine the likelihood of any service containing certain anti-patterns. We validate this methodology by gathering feedback from subject-matter experts, by ways of surveys and one-on-one sessions where Luduan is used as a support tool. Finally, we ask teams that are responsible for services, to figure out whether their service has an anti-pattern or not. We then use these results to fine tune the computations from metrics to anti-pattern likelihood.