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The euphoria around microservices has decreased over the years, but the trend of modernizing legacy systems to this novel architectural style is unbroken to date. A variety of approaches have been proposed in academia and industry, aiming to structure and automate the often long-lasting and cost-intensive migration journey. However, our research shows that there is still a need for more systematic guidance. While grey literature is dominant for knowledge exchange among practitioners, academia has contributed a significant body of knowledge as well, catching up on its initial neglect. A vast number of studies on the topic yielded novel techniques, often backed by industry evaluations. However, practitioners hardly leverage these resources. In this paper, we report on our efforts to design an architecture-centric methodology for migrating to microservices. As its main contribution, a framework provides guidance for architects during the three phases of a migration. We refer to methods, techniques, and approaches based on a variety of scientific studies that have not been made available in a similarly comprehensible manner before. Through an accompanying tool to be developed, architects will be in a position to systematically plan their migration, make better informed decisions, and use the most appropriate techniques and tools to transition their systems to microservices.
To remain competitive in a fast changing environment, many companies started to migrate their legacy applications towards a Microservices architecture. Such extensive migration processes require careful planning and consideration of implications and challenges likewise. In this regard, hands-on experiences from industry practice are still rare. To fill this gap in scientific literature, we contribute a qualitative study on intentions, strategies, and challenges in the context of migrations to Microservices. We investigated the migration process of 14 systems across different domains and sizes by conducting 16 in-depth interviews with software professionals from 10 companies. Along with a summary of the most important findings, we present a separate discussion of each case. As primary migration drivers, maintainability and scalability were identified. Due to the high complexity of their legacy systems, most companies preferred a rewrite using current technologies over splitting up existing code bases. This was often caused by the absence of a suitable decomposition approach. As such, finding the right service cut was a major technical challenge, next to building the necessary expertise with new technologies. Organizational challenges were especially related to large, traditional companies that simultaneously established agile processes. Initiating a mindset change and ensuring smooth collaboration between teams were crucial for them. Future research on the evolution of software systems can in particular profit from the individual cases presented.
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.
Services Oriented Architectures (SOA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implemented using the Web Services (WS) standards. However, the maintenance and evolution of SOA systems present many challenges. SmartLife applications are intelligent user-centered systems and a special class of SOA systems that present even greater challenges for a software maintainer. Ontologies and ontological modeling can be used to support the evolution of SOA systems. This paper describes the development of a SOA evolution ontology and its use to develop an ontological model of a SOA system. The ontology is based on a standard SOA ontology. The ontological model can be used to provide semantic and visual support for software maintainers during routine maintenance tasks. We discuss a case study to illustrate this approach, as well as the strengths and limitations.
Many future Services Oriented Architecture (SOA) systems may be pervasive SmartLife applications that provide real-time support for users in everyday tasks and situations. Development of such applications will be challenging, but in this position paper we argue that their ongoing maintenance may be even more so. Ontological modelling of the application may help to ease this burden, but maintainers need to understand a system at many levels, from a broad architectural perspective down to the internals of deployed components. Thus we will need consistent models that span the range of views, from business processes through system architecture to maintainable code. We provide an initial example of such a modelling approach and illustrate its application in a semantic browser to aid in software maintenance tasks.
In modern times markets are very dynamic. This situation requires agile enterprises to have the ability to react fast on market influences. Thereby an enterprise’ IT is especially affected, because new or changed business models have to be realized. However, enterprise architectures (EA) are complex structures consisting of many artifacts and relationships between them. Thus analyzing an EA becomes to a complex task for stakeholders. In addition, many stakeholders are involved in decision-making processes, because Enterprise Architecture Management (EAM) targets providing a holistic view of the enterprise. In this article we use concepts of Adaptive Case Management (ACM) to design a decision-making case consisting of a combination of different analysis techniques to support stakeholders in decision-making. We exemplify the case with a scenario of a fictive enterprise.
Enterprise architecture management (EAM) is a holistic approach to tackle the complex Business and IT architecture. The transformation of an organization’s EA towards a strategy-oriented system is a continuous task. Many stakeholders have to elaborate on various parts of the EA to reach the best decisions to shape the EA towards an optimized support of the organizations’ capabilities. Since the real world is too complex, analyzing techniques are needed to detect optimization potentials and to get all information needed about an issue. In practice visualizations are commonly used to analyze EAs. However these visualizations are mostly static and do not provide analyses. In this article we combine analyzing techniques from literature and interactive visualizations to support stakeholders in EA decision-making.
Enterprise Architectures (EA) consists of many architecture elements, which stand in manifold relationships to each other. Therefore Architecture Analysis is important and very difficult for stakeholders. Due changing an architecture element has impacts on other elements different stakeholders are involved. In practice EAs are often analyzed using visualizations. This article aims at contributing to the field of visual analytics in EAM by analyzing how state of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study and accomplishing them in a master’s level class with students.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
Enterprise Governance, Risk and Compliance (GRC) systems are key to managing risks threatening modern enterprises from many different angles. Key constituent to GRC systems is the definition of controls that are implemented on the different layers of an Enterprise Architecture (EA). As part of the compliance aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper we present a metamodel which links controls to the affected elements of an EA and supplies a way of expressing associated assessment techniques and results. We complement the metamodel with an expository instantiation in a cockpit for control compliance applied in an international enterprise in the insurance industry.