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Software Architectural Metrics for the Scania Internet of Things Platform: From a Microservice Perspectiv
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
2017 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

There are limited tools to evaluate a microservice architecture and no common definition of how the architecture should be designed. Moreover, developing systems with microservices introduces additional complexity to the software architecture. That, together with the fact the systems are becoming more complex has led to a desire for architecture evaluation methods.

In this thesis a set of quality attributes measured by structural metrics are used to evaluate Scania's IoT Offboard platform. By implementing a metrics evaluation program the quality of the software architecture can be improved. Also, metrics can assist developers and architects while they are becoming more efficient since they better understand how performance is measured, i.e. which quality attributes are the most important and how these are measured.

For Scania's IoT Offboard platform the studied quality attributes are listed in decreasing importance: flexibility, reusability and understandability. All the microservices are loosely coupled in the platform, which results in a loosely coupled architecture. This indicates a flexible, reusable and understandable system, in terms of coupling. Furthermore, the architecture is decentralized, i.e. the system is unflexible and difficult to change. The other metrics were lacking a reference scale, hence they will act as a point of reference for future measurements as the architecture evolves.

To improve the flexibility, reusability and understandability of the architecture the large microservices should be divided into several smaller microservices. Also aggregators should be utilized more to make the system more flexible.

Place, publisher, year, edition, pages
2017. , p. 54
Series
UPTEC F, ISSN 1401-5757 ; 17033
Keywords [en]
software architecture, architectural metrics, software metrics, microservices, msa, service metrics, soa metrics
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:uu:diva-325592OAI: oai:DiVA.org:uu-325592DiVA, id: diva2:1115342
External cooperation
Scania AB
Educational program
Master Programme in Engineering Physics
Supervisors
Examiners
Available from: 2017-06-30 Created: 2017-06-26 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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