A Comparative Review of Microservices and Monolithic Architectures

Al-Debagy, Omar; Martinek, Péter

doi:10.1109/cinti.2018.8928192

Cited by 82 publications

(29 citation statements)

References 7 publications

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“…As long as the public API does not change, internal modifications of one service are more straightforward, easier, and less costly than in the case of a similar change in a traditional model. Microservices are autonomous and communicate via open protocols, hence they can be developed fairly independently and even with different technologies [5], [41]- [43].…”

Section: B Microservice Architecturementioning

confidence: 99%

Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation

2022

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Context. Since its proclamation in 2012, microservices-based architecture has gained widespread popularity due to its advantages, such as improved availability, fault tolerance, and horizontal scalability, as well as greater software development agility. Motivation. Yet, refactoring a monolith to microservices by smaller businesses and expecting that the migration will bring benefits similar to those reported by top global companies, such as Netflix, Amazon, eBay, and Uber, might be an illusion. Indeed, for systems that do not have thousands of concurrent users and can be scaled vertically, the benefits of such migration have not been sufficiently investigated, while the existing evidence is inconsistent. Objective. The purpose of this paper is to compare the performance and scalability of monolithic and microservice architectures on a reference web application. Method. The application was implemented in four different versions, covering not only two different architectural styles (monolith vs. microservices) but also two different implementation technologies (Java vs. C# .NET). Next, we conducted a series of controlled experiments in three different deployment environments (local, Azure Spring Cloud, and Azure App Service). Findings. The key lessons learned are as follows: (1) on a single machine, a monolith performs better than its microservice-based counterpart; (2) The Java platform makes better use of powerful machines in case of computation-intensive services when compared to .NET; the technology platform effect is reversed when non-computationally intensive services are run on machines with low computational capacity; (3) vertical scaling is more cost-effective than horizontal scaling in the Azure cloud; (4) scaling out beyond a certain number of instances degrades the application performance; (5) implementation technology (either Java or C# .NET) does not have a noticeable impact on the scalability performance.

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Section: B Microservice Architecturementioning

confidence: 99%

Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation

2022

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“…Microservices implement a remote service using a collection of small, independent services potentially deployed on different platforms or technology stacks [141]. Some of their advantages over monolithic architectures for software [142] include adaptability to changes in technology, reduced time-to-market (new features for a given remote service may be released as a microservice on its own), scalability, and flexible software engineering development practices (e.g., DevOps [143]) which suit many startup companies designing wearable systems and services. Data collected by remote systems can be analyzed using AI and ML techniques [26,45] such as deep learning (DL) [34], and feedback may be provided to users or to external third parties based on privacy policies or terms of use and commercial agreements [144].…”

Section: Human-centric Systemsmentioning

confidence: 99%

Recent Advances in Wearable Sensing Technologies

Pérez

Zeadally

2021

Sensors

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Wearable sensing technologies are having a worldwide impact on the creation of novel business opportunities and application services that are benefiting the common citizen. By using these technologies, people have transformed the way they live, interact with each other and their surroundings, their daily routines, and how they monitor their health conditions. We review recent advances in the area of wearable sensing technologies, focusing on aspects such as sensor technologies, communication infrastructures, service infrastructures, security, and privacy. We also review the use of consumer wearables during the coronavirus disease 19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and we discuss open challenges that must be addressed to further improve the efficacy of wearable sensing systems in the future.

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“…The application architecture adopted by the traditional power automation system is based on monolithic application architecture. With the development of power Internet of Things, the advantages of microservice architecture become more obvious due to the higher requirements of diversified function and efficient application exploitation [25]. Using the microservice architecture, an application can be decomposed into microservices and only when all the microservices are finished can an application end.…”

Section: A Logical Relationship Of Microservicesmentioning

confidence: 99%

Workload Modeling for Microservice-Based Edge Computing in Power Internet of Things

et al. 2021

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Microservice-based edge computing is a key technology to support power system to adapt to the high concurrency and diversification of application in power Internet of Things. Workload modeling is not only the basis for analyzing the logical design and computing resource requirements of application, but also the premise of optimizing the computing resource configuration and scheduling of edge computing. In this paper, a workload modeling method for microservice-based edge computing is proposed. The composition of an application and the logical relationship among the microservices are elaborated. Then, the topological structure graph and model are proposed to describe the logical relationship of the microservices. Based on the established model, the workload model is formulated to calculate the computing resource demand and latency of the application. Besides, a microservice-based workload evaluation algorithm is proposed to obtain the configuration results and the latency performance. The influence of the application architecture, topological structure of microservices and virtualization technology of edge computing terminal are analyzed. Simulation results verify the validity of the proposed model and method.

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A Comparative Review of Microservices and Monolithic Architectures

Cited by 82 publications

References 7 publications

Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation

Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation

Recent Advances in Wearable Sensing Technologies

Workload Modeling for Microservice-Based Edge Computing in Power Internet of Things

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