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Real Time Charging (RTC) applications that reside in the telecommunications domain have the need for extremely fast database transactions. Today´s providers rely mostly on in-memory databases for this kind of information processing. A flexible and modular benchmark suite specifically designed for this domain provides a valuable framework to test the performance of different DB candidates. Besides a data and a load generator, the suite also includes decoupled database connectors and use case components for convenient customization and extension. Such easily produced test results can be used as guidance for choosing a subset of candidates for further tuning/testing and finally evaluating the database most suited to the chosen use cases. This is why our benchmark suite can be of value for choosing databases for RTC use cases.
The fast moving process of digitization1 demands flexibility in order to adapt to rapidly changing business requirements and newly emerging business opportunities. New features have to be developed and deployed to the production environment a lot faster. To be able to cope with this increased velocity and pressure, a lot of software developing companies have switched to a Microservice Architecture (MSA) approach. Applications built this way consist of several fine-grained and heterogeneous services that are independently scalable and deployable. However, the technological and business architectural impacts of microservices based applications directly affect their integration into the digital enterprise architecture. As a consequence, traditional Enterprise Architecture Management (EAM) approaches are not able to handle the extreme distribution, diversity, and volatility of micro-granular systems and services. We are therefore researching mechanisms for dynamically integrating large amounts of microservices into an adaptable digital enterprise architecture.
Towards a practical maintainability quality model for service- and microservice-based systems
(2017)
Although current literature mentions a lot of different metrics related to the maintainability of service-based systems (SBSs), there is no comprehensive quality model (QM) with automatic evaluation and practical focus. To fill this gap, we propose a Maintainability Model for Services (MM4S), a layered maintainability QM consisting of service properties (SPs) related with automatically collectable Service Metrics (SMs). This research artifact created within an ongoing Design Science Research (DSR) project is the first version ready for detailed evaluation and critical feedback. The goal of MM4S is to serve as a simple and practical tool for basic maintainability estimation and control in the context of BSs and their specialization
microservice-based systems (μSBSs).
In a time of digital transformation, the ability to quickly and efficiently adapt software systems to changed business requirements becomes more important than ever. Measuring the maintainability of software is therefore crucial for the long-term management of such products. With service-based systems (SBSs) being a very important form of enterprise software, we present a holistic overview of such metrics specifically designed for this type of system, since traditional metrics – e.g. object oriented ones – are not fully applicable in this case. The selected metric candidates from the literature review were mapped to 4 dominant design properties: size, complexity, coupling, and cohesion. Microservice-based systems (μSBSs) emerge as an agile and fine grained variant of SBSs. While the majority of identified metrics are also applicable to this specialization (with some limitations), the large number of services in combination with technological heterogeneity and decentralization of control significantly impacts automatic metric collection in such a system. Our research therefore suggests that specialized tool support is required to guarantee the practical applicability of the presented metrics to μSBSs.
While the recently emerged microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high costs and effort of a refactoring process which has several other implications, e.g. overall processes (DevOps) and team structure. Software architects facing this challenge are in need of selecting an appropriate strategy and refactoring technique. One of the most discussed aspects in this context is finding the right service granularity to fully leverage the advantages of a microservices architecture. This study first discusses the notion of architectural refactoring and subsequently compares 10 existing refactoring approaches recently proposed in academic literature. The approaches are classified by the underlying decomposition technique and visually presented in the form of a decision guide for quick reference. The review yielded a variety of strategies to break down a monolithic application into independent services. With one exception, most approaches are only applicable under certain conditions. Further concerns are the significant amount of input data some approaches require as well as limited or prototypical tool support.
While there are several theoretical comparisons of Object Orientation (OO) and Service Orientation (SO), little empirical research on the maintainability of the two paradigms exists. To provide support for a generalizable comparison, we conducted a study with four related parts. Two functionally equivalent systems (one OO and one SO version) were analyzed with coupling and cohesion metrics as well as via a controlled experiment, where participants had to extend the systems. We also conducted a survey with 32 software professionals and interviewed 8 industry experts on the topic. Results indicate that the SO version of our system possesses a higher degree of cohesion, a lower degree of coupling, and could be extended faster. Survey and interview results suggest that industry sees systems built with SO as more loosely coupled, modifiable, and reusable. OO systems, however, were described as less complex and easier to test.
In current times, a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT environments with many rather small and distributed structures, like Internet of Things. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world and living software and system architectures defines the moving context for adaptable and evolutionary software approaches, which are essential to enable the digital transformation. In this paper, we are putting a spotlight to service oriented software evolution to support the digital transformation with micro granular digital architectures for digital services and products.
To bring a pattern-based perspective to the SOA vs. microservices discussion, we qualitatively analyzed a total of 118 SOA patterns from 2 popular catalogs for their (partial) applicability to microservices. Patterns had to hold up to 5 derived microservices principles to be applicable. 74 patterns (63%) were categorized as fully applicable, 30 (25%) as partially applicable, and 14 (12%) as not applicable. Most frequently violated microservices characteristics werde Decentralization and Single System. The findings suggest that microservices and SOA share a large set of architectural principles and solutions in the general space of service-based systems while only having a small set of differences in specific areas.
Maintainability assurance techniques are used to control this quality attribute and limit the accumulation of potentially unknown technical debt. Since the industry state of practice and especially the handling of service- and microservice-based systems in this regard are not well covered in scientific literature, we created a survey to gather evidence for a) used processes, tools, and metrics in the industry, b) maintainability-related treatment of systems based on service orientation, and c) influences on developer satisfaction w.r.t. maintainability. 60 software professionals responded to our online questionnaire. The results indicate that using explicit and systematic techniques has benefits for maintainability. The more sophisticated the applied methods the more satisfied participants were with the maintainability of their software while no link to a hindrance in productivity could be established. Other important findings were the absence of architecture-level evolvability control mechanisms as well as a significant neglect of service-oriented particularities for quality assurance. The results suggest that industry has to improve its quality control in these regards to avoid problems with long living service-based software systems.
Enterprises are presently transforming their strategy, culture, processes, and their information systems to become more digital. The digital transformation deeply disrupts existing enterprises and economies. Digitization fosters the development of IT systems with many rather small and distributed structures, like Internet of Things or mobile systems. Since years a lot of new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. This has a strong impact for architecting digital services and products. The change from a closed-world modeling perspective to more flexible open-world composition and evolution of system architectures defines the moving context for adaptable systems, which are essential to enable the digital transformation. In this paper, we are focusing on a decision-oriented architectural composition approach to support the transformation for digital services and products.