Set Of Microservices Research Articles

A fuzzy logic-based quality model for identifying microservices with low maintainability

Microservice Architecture (MSA) is a popular architectural style that offers many advantages regarding quality attributes, including maintainability and scalability. Developing a system as a set of microservices with expected benefits requires a quality assessment strategy that is established on the measurements of the system's properties. This paper proposes a hierarchical quality model based on fuzzy logic to measure and evaluate the maintainability of MSAs considering ISO/IEC 250xy SQuaRE (System and Software Quality Requirements and Evaluation) standards. Since the qualitative bounds of low-level quality attributes are inherently ambiguous, we use a fuzzification technique to transform crisp values of code metrics into fuzzy levels and apply them as inputs to our quality model. The model generates fuzzy values for the quality sub-characteristics of the maintainability, i.e., modifiability and testability, converted to numerical values through defuzzification. In the last step, using the values of the sub-characteristics, we calculate numerical scores indicating the maintainability level of each microservice in the examined software system. This score was used to assess the quality of the microservices and decide whether they need refactoring. We evaluated our approach by creating a test set with the assistance of three developers, who reviewed and categorized the maintainability levels of the microservices in an open-source project based on their knowledge and experience. They labeled microservices as low, medium, or high, with low indicating the need for refactoring. Our method for identifying low-labeled microservices in the given test set achieved 94% accuracy, 78% precision, and 100% recall. These results indicate that our approach can assist designers in evaluating the maintainability quality of microservices.

Digital Twin is a complex of microservices

Industry 4.0 is an actively developing concept, of which the concept of the Digital Twin is becoming a part. The digital twin is a complex cyber-physical system that consists of many components. One of the main tasks in the construction of a twin is to organize the interaction of the parts of the twin with each other. Previously, an approach called the enterprise service bus was used, but over the years of its use it became clear that it is not suitable for constantly evolving and growing systems. The digital twin is just such a system and therefore it is required to use a different approach, called microservice. If we imagine the parts of the twin as a set of microservices, then it will be possible to create a system suitable for constant evolution and replacement of its parts. This approach was used to solve the problem of building a prototype digital twin of methanol production. The solution of this problem showed the possibility of using a microservice approach.

Towards Migrating from Monolithic-Based Web Application to Micro Service: A Case Study of ezScrum Product Backlog

The software ezScrum is a legacy web application that has been developed and maintained for more than ten years. With web technology constantly evolving, the ezScrum development team has found it increasingly difficult to keep up and many older technologies are still used. A consequence is the slowdown of release. Examining the issues, we have found the main cause to be the coupling of ezScrum modules since ezScrum is a monolith. Thus, effort has been taken to convert ezScrum into a set of microservices so that coupling is reduced. This thesis reports our work on extracting the product backlog from ezScrum. As demonstrated, the extracted product backlog microservice operates as an independent web application that collaborates with other extracted microservices from ezScrum including account management.

Facilitating the migration to the microservice architecture via model-driven reverse engineering and reinforcement learning

The microservice architecture has gained remarkable attention in recent years. Microservices allow developers to implement and deploy independent services, so they are a naturally effective architecture for continuously deployed systems. Because of this, several organizations are undertaking the costly process of manually migrating their traditional software architectures to microservices. The research in this paper aims at facilitating the migration from monolithic software architectures to microservices. We propose a framework which enables software developers/architects to migrate their software systems more efficiently by helping them remodularize the source code of their systems. The framework leverages model-driven reverse engineering to obtain a model of the legacy system and reinforcement learning to propose a mapping of this model toward a set of microservices.

Service-based Analytics for 5G open experimentation platforms

A scalable, flexible and reliable Analytics service has become a requirement toward building efficient Fifth Generation (5G) experimental platforms that can support a suite of end-user experiments and verticals. Our paper presents the challenges that come with designing such a service-based Analytics component, and shows how we have used it in the context of open experimental platforms in the 5GENESIS project. Our Analytics service was designed both for enabling the efficient setup and configuration of the underlying platform, and also for ensuring that it provides useful insights into the experimentation Key Performance Indicators (KPIs) toward the end-user. Thus, Analytics proved to be a useful tool across several stages, starting from ensuring correct operation during the initial phases of the network setup and continuing into the normal day-to-day experimentation. Our experiments show how the tool was used in our setup and provide information on how to apply it to different environments. The Analytics component, designed as a set of microservices that serve several goals in the analytics workflow, is also provided as open source, being part of the Open5Genesis suite.

MSN: A Playground Framework for Design and Evaluation of MicroServices-Based sdN Controller

Software-defined networking decouples control and data plane in softwarized networks. This allows for centralized management of the network, but complete centralization of the controller functions raises potential issues related to failure, latency, and scalability. Distributed controller deployment is adopted to optimize scalability and latency problems. However, existing controllers are monolithic, resulting in code inefficiency for distributed deployment. Some seminal ongoing efforts have been proposed with the idea of disaggregating the SDN controller architecture into an assembly of various subsystems, each of which can be responsible for a certain controller task. These subsystems are typically implemented as microservices and deployed as virtual network functions, in particular as Docker Containers. This enables flexible deployment of controller functions. However, these proposals (e.g., muONOS) are still in their early stage of design and development, so that a full decomposition of the SDN controller is not been available yet. To fill that gap, this article derives some important design guidelines to decompose an SDN controller into a set of microservices. Next, it also proposes a microservices-based decomposed controller architecture, foreseeing communications issues between the controller sub-functions. These design and performance considerations are also proven via the implementation of the proposed architecture as a solution, called Micro-Services based SDN controller (MSN), based on the Ryu SDN controller. Moreover, MSN includes different network communication protocols, such as gRPC, WebSocket, and REST-API. Finally, we show experimental results that highlight the robustness and latency of the system on a networking testbed. Collected results prove the main pros and cons of each network communication protocol and an evaluation of our proposal in terms of system resilience, scalability and latency.

Design of an Educational Virtual Assistant Software

Despite the great creators’ efforts of e-learning educational materials, it is not possible to define the content of these materials specifically for all students. Based on this, it is necessary to provide in e-learning education the possibility of a more detailed interpretation of specific parts of the educational material that may be unclear to specific students. Based on this fact, we decided to take the first step in the form of software design, which will represent a virtual assistant in teaching computer science. The role of this assistant will be the ability to answer technical questions related to the presented curriculum. From an architectural point of view, it will be a set of micro-services, each of which will serve a specific task. The prerequisite is the use of decision trees to determine a specific micro-service, which will be implemented in the form of a neural network. Main aim of this paper is to provide detail description of global software architecture for such a virtual assistant

A Framework for Cloud-Based Spatially-Explicit Uncertainty and Sensitivity Analysis in Spatial Multi-Criteria Models

Global sensitivity analysis, like variance-based methods for massive raster datasets, is especially computationally costly and memory-intensive, limiting its applicability for commodity cluster computing. The computational effort depends mainly on the number of model runs, the spatial, spectral, and temporal resolutions, the number of criterion maps, and the model complexity. The current Spatially-Explicit Uncertainty and Sensitivity Analysis (SEUSA) approach employs a cluster-based parallel and distributed Python–Dask solution for large-scale spatial problems, which validates and quantifies the robustness of spatial model solutions. This paper presents the design of a framework to perform SEUSA as a Service in a cloud-based environment scalable to very large raster datasets and applicable to various domains, such as landscape assessment, site selection, risk assessment, and land-use management. It incorporates an automated Kubernetes service for container virtualization, comprising a set of microservices to perform SEUSA as a Service. Implementing the proposed framework will contribute to a more robust assessment of spatial multi-criteria decision-making applications, facilitating a broader access to SEUSA by the research community and, consequently, leading to higher quality decision analysis.

Patient empowerment in connecare

Background: In a context of growing incidence of chronic diseases and aging populations, there is the need to research and find new solutions to shift resources into the community in an effort to deal more effectively with chronic conditions. In that direction, patient empowerment plays an important role. Approaches to increase patient empowerment vary from patient self-management programs to promoting patient involvement in treatment shared decision-making, to facilitating the clinician-patient cooperation. Methods: In the CONNECARE project ID: 689802, we focus on patient’s monitoring with the final goal of providing self-management features to people in needs, such as chronic patients. To be modular and scalable and to allow us to have a disease-independent system, the proposed solution is based on the software-engineering concept of microservices. They are modularization concepts that may be developed independently of each other, possess their own data storage, and can bring their own support service. In CONNECARE, each microservice is in charge of performing a simple task; whereas a complex task is achieved by the collaboration, interaction, and coordination of one or more simple microservices. In so doing, the proposed solution allows a better maintenance and bugs fixing. Seemly, scalability is obtained by dividing each task into less complex ones. Thus, when changes are needed in a microservice, they do not affect the rest of the system. Moreover, when a new functionality is required, a new microservice or set of microservices collaborating together may be defined and simply added to the system. In so doing, the proposed solution is robust to changes and improvements. Right now, 9 microservices have been defined and developed, each one aimed at providing a functionality to provide self-management to the patients. Patient’s monitoring is performed through the following microservices: physical activity, self-checked questionnaires, sleeping, and health status. Also 5 further functionalities are provided, each one by a specific microservice: notifications, alerts, recommendations, third-party integration, and messaging. Results: According to a co-design approach with clinicians of the 4 sites in the project i.e., Barcelona, Lleida, Israel, and Groningen, clinical studies have been designed for field-testing the self-management system in real clinical practice. Those studies will be carried out during 18 months starting in March 2018 and will focus on 3 use cases: community-based management of chronic complex patients, integrated management of patients undergoing surgical procedures, and pre-habilitation of high-risk candidates for complex abdominal surgical procedures the latter only in Barcelona. Currently, a feasibility test with selected clinicians and patients is running in the 4 sites. Conclusions: The first release of the presented system is under testing to be ready to be evaluated and refined in 4 sites throughout clinical studies next March. CONNECARE will consequently help to improve real practice deployment of integrated care in those sites and will be able to bring practical insight to the potential of transferability of new methods and technologies to other regions in Europe and beyond.