Cloud-Native Architectural Characteristics and their Impacts on Software Quality: A Validation Survey
Robin Lichtenth\"aler, Jonas Fritzsch, Guido Wirtz

TL;DR
This paper investigates how architectural characteristics of cloud-native applications impact software quality, validating and updating a quality model through a survey of professionals to guide better design and development practices.
Contribution
It presents a validated and revised quality model for cloud-native architectures, supported by survey data, and introduces a survey tool for assessing complex quality structures.
Findings
Survey supports the quality model to a fair extent
Identifies parts of the model needing revision
Provides a survey tool for complex quality assessments
Abstract
Cloud-native architectures are often based on microservices and combine different aspects that aim to leverage the capabilities of cloud platforms for software development. Cloud-native architectural characteristics like patterns and best practices aim to design, develop, deploy, and operate such systems efficiently with minimal time and effort. However, architects and developers are faced with the challenge of applying such characteristics in a targeted manner to improve selected quality attributes. Hence, we aim to investigate relationships, or more specifically impacts, between architectural characteristics of cloud-native applications, and quality aspects. The architectural characteristics in consideration are based on our recently proposed quality model for cloud-native software architectures. To validate its elements and revise this literature-based quality model, we conducted a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · Big Data and Business Intelligence
