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While several service-based maintainability metrics have been proposed in the scientific literature, reliable approaches to automatically collect these metrics are lacking. Since static analysis is complicated for decentralized and technologically diverse microservice-based systems, we propose a dynamic approach to calculate such metrics from runtime data via distributed tracing. The approach focuses on simplicity, extensibility, and broad applicability. As a first prototype, we implemented a Java application with a Zipkin integrator, 23 different metrics, and five export formats. We demonstrated the feasibility of the approach by analyzing the runtime data of an example microservice based system. During an exploratory study with six participants, 14 of the 18 services were invoked via the system’s web interface. For these services, all metrics were calculated correctly from the generated traces.
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.
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.
Enterprises are currently transforming their strategy, processes, and their information systems to extend their degree of digitalization. The potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, artificial intelligence, big data with analytics, mobile systems, collaboration networks, and cyber physical systems both drives and enables new business designs. Digitalization deeply disrupts existing businesses, technologies and economies and fosters the architecture of digital environments with many rather small and distributed structures. This has a strong impact for new value producing opportunities and architecting digital services and products guiding their design through exploiting a Service-Dominant Logic. The main result of the book chapter extends methods for integral digital strategies with value-oriented models for digital products and services which are defined in the framework of a multi-perspective digital enterprise architecture reference model.
Presently, many companies are transforming their strategy and product base, as well as their culture, processes and information systems to become more digital or to approach for a digital leadership. In the last years new business opportunities appeared using the potential of the Internet and related digital technologies, like Internet of Things, services computing, cloud computing, edge and fog computing, social networks, big data with analytics, mobile systems, collaboration networks, and cyber physical systems. Digitization fosters the development of IT environments with many rather small and distributed structures, like the Internet of Things, Microservices, or other micro-granular elements. 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 micro-granular system architectures defines the moving context for adaptable systems. We are focusing on a continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, as part of a new digital enterprise architecture for service dominant digital products.
While Microservices promise several beneficial characteristics for sustainable long-term software evolution, little empirical research covers what concrete activities industry applies for the evolvability assurance of Microservices and how technical debt is handled in such systems. Since insights into the current state of practice are very important for researchers, we performed a qualitative interview study to explore applied evolvability assurance processes, the usage of tools, metrics, and patterns, as well as participants’ reflections on the topic. In 17 semi-structured interviews, we discussed 14 different Microservice-based systems with software professionals from 10 companies and how the sustainable evolution of these systems was ensured. Interview transcripts were analyzed with a detailed coding system and the constant comparison method.
We found that especially systems for external customers relied on central governance for the assurance. Participants saw guidelines like architectural principles as important to ensure a base consistency for evolvability. Interviewees also valued manual activities like code review, even though automation and tool support was described as very important. Source code quality was the primary target for the usage of tools and metrics. Despite most reported issues being related to Architectural Technical Debt (ATD), our participants did not apply any architectural or service-oriented tools and metrics. While participants generally saw their Microservices as evolvable, service cutting and finding an appropriate service granularity with low coupling and high cohesion were reported as challenging. Future Microservices research in the areas of evolution and technical debt should take these findings and industry sentiments into account.
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 many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.
The Internet of Things (IoT), enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems with service oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision case management in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering for the digitization and architectural decision support.
Digitization fosters the development of IT environments with many rather small structures, like Internet of Things (IoT), microservices, or mobility systems. They are needed to support flexible and agile digitized products and services. The goal is to create service-oriented enterprise architectures (EA) that are self optimizing and resilient. The present research paper investigates methods for decision-making concerning digitization architectures for Internet of Things and microservices. They are based on evolving enterprise architecture reference models and state of the art elements for architectural engineering for microgranular systems. Decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures, is sorely needed. The challenging of the decision processes can be supported with in a more flexible and intuitive way by an architecture management cockpit.
Digitization of societies changes the way we live, work, learn, communicate, and collaborate. In the age of digital transformation IT environments with a large number of rather small structures like Internet of Things (IoT), microservices, or mobility systems are emerging to support flexible and agile digitized products and services. Adaptable ecosystems with service oriented enterprise architectures are the foundation for self-optimizing, resilient run-time environments and distributed information systems. The resulting business disruptions affect almost all new information processes and systems in the context of digitization. Our aim are more flexible and agile transformations of both business and information technology domains with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision-controlled digitization architectures for Internet of Things and microservices by evolving enterprise architecture reference models and state of the art elements for architectural engineering for micro-granular 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.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new digital enterprise architecture. To integrate micro granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitization of products, services, and processes.
Context
Web APIs are one of the most used ways to expose application functionality on the Web, and their understandability is important for efficiently using the provided resources. While many API design rules exist, empirical evidence for the effectiveness of most rules is lacking.
Objective
We therefore wanted to study 1) the impact of RESTful API design rules on understandability, 2) if rule violations are also perceived as more difficult to understand, and 3) if demographic attributes like REST-related experience have an influence on this.
Method
We conducted a controlled Web-based experiment with 105 participants, from both industry and academia and with different levels of experience. Based on a hybrid between a crossover and a between-subjects design, we studied 12 design rules using API snippets in two complementary versions: one that adhered to a rule and one that was a violation of this rule. Participants answered comprehension questions and rated the perceived difficulty.
Results
For 11 of the 12 rules, we found that violation performed significantly worse than rule for the comprehension tasks. Regarding the subjective ratings, we found significant differences for 9 of the 12 rules, meaning that most violations were subjectively rated as more difficult to understand. Demographics played no role in the comprehension performance for violation.
Conclusions
Our results provide first empirical evidence for the importance of following design rules to improve the understandability of Web APIs, which is important for researchers, practitioners, and educators.
The digital transformation of our life changes the way we work, learn, communicate, and collaborate. Enterprises are presently transforming their strategy, culture, processes, and their information systems to become 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, Microservices and mobile services. Since years a lot of new business opportunities appear using the potential of services computing, Internet of Things, mobile systems, big data with analytics, cloud computing, collaboration networks, and decision support. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self optimizing and resilient run-time environments for intelligent business services and adaptable distributed information systems with service oriented enterprise architectures. This has a strong impact for architecting digital services and products following both a value-oriented and a service perspective. The change from a closed world modeling world to a more flexible open-world composition and evolution of enterprise architectures defines the moving context for adaptable and high distributed systems, which are essential to enable the digital transformation. The present research paper investigates the evolution of Enterprise Architecture considering new defined value-oriented mappings between digital strategies, digital business models and an improved digital enterprise architecture.
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.
Context
Microservices as a lightweight and decentralized architectural style with fine-grained services promise several beneficial characteristics for sustainable long-term software evolution. Success stories from early adopters like Netflix, Amazon, or Spotify have demonstrated that it is possible to achieve a high degree of flexibility and evolvability with these systems. However, the described advantageous characteristics offer no concrete guidance and little is known about evolvability assurance processes for microservices in industry as well as challenges in this area. Insights into the current state of practice are a very important prerequisite for relevant research in this field.
Objective
We therefore wanted to explore how practitioners structure the evolvability assurance processes for microservices, what tools, metrics, and patterns they use, and what challenges they perceive for the evolvability of their systems.
Method
We first conducted 17 semi-structured interviews and discussed 14 different microservice-based systems and their assurance processes with software professionals from 10 companies. Afterwards, we performed a systematic grey literature review (GLR) and used the created interview coding system to analyze 295 practitioner online resources.
Results
The combined analysis revealed the importance of finding a sensible balance between decentralization and standardization. Guidelines like architectural principles were seen as valuable to ensure a base consistency for evolvability and specialized test automation was a prevalent theme. Source code quality was the primary target for the usage of tools and metrics for our interview participants, while testing tools and productivity metrics were the focus of our GLR resources. In both studies, practitioners did not mention architectural or service-oriented tools and metrics, even though the most crucial challenges like Service Cutting or Microservices Integration were of an architectural nature.
Conclusions
Practitioners relied on guidelines, standardization, or patterns like Event-Driven Messaging to partially address some reported evolvability challenges. However, specialized techniques, tools, and metrics are needed to support industry with the continuous evaluation of service granularity and dependencies. Future microservices research in the areas of maintenance, evolution, and technical debt should take our findings and the reported industry sentiments into account.
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.
Microservices are a topic driven mainly by practitioners and academia is only starting to investigate them. Hence, there is no clear picture of the usage of Microservices in practice. In this paper, we contribute a qualitative study with insights into industry adoption and implementation of Microservices. Contrary to existing quantitative studies, we conducted interviews to gain a more in-depth understanding of the current state of practice. During 17 interviews with software professionals from 10 companies, we analyzed 14 service-based systems. The interviews focused on applied technologies, Microservices characteristics, and the perceived influence on software quality. We found that companies generally rely on well established technologies for service implementation, communication, and deployment. Most systems, however, did not exhibit a high degree of technological diversity as commonly expected with Microservices. Decentralization and product character were different for systems built for external customers. Applied DevOps practices and automation were still on a mediocre level and only very few companies strictly followed the you build it, you run it principle. The impact of Microservices on software quality was mainly rated as positive. While maintainability received the most positive mentions, some major issues were associated with security. We present a description of each case and summarize the most important findings of companies across different domains and sizes. Researchers may build upon our findings and take them into account when designing industry-focused methods.
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.