An Initial Insight into Measuring Quality in Cloud-Native Architectures

Cloud-native architectures represent a shift in the IT landscape by delivering ICT services “as a service” and necessitating additional emphasis on the aspects of quality as organizations migrate applications to these environments. This paper presents the findings of an initial review examining quality models, metrics, and thresholds within the domain of cloud-native architectures. The study encompassed 41 relevant publications, offering insights into the evolution of research trends over the years. Extracting key data from these studies, we analyzed facets such as the focus on quality dimensions, research types, contribution types, and citation rates. Our results reveal a prevalence of solution proposals and opinion papers, concentrating on metrics, models, methods, and tools. Notably, the peak of significant publications occurred in 2020. Most studies concentrated on investigating performance-related quality aspects, followed closely by Quality of Service (QoS), monitoring, and scalability. The presented overview provides a valuable reference and starting point for researchers and practitioners navigating the landscape of quality considerations in cloud-native architectures.