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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 digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change drive current and next 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 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 composed digital architecture. To integrate micro-granular architecture models into living architectural model versions we are extending enterprise architecture reference models by state of art elements for agile architectural engineering to support digital products, services, and processes.
Background: Design patterns are supposed to improve various quality attributes of software systems. However, there is controversial quantitative evidence of this impact. Especially for younger paradigms such as service- and microservice-based systems, there is a lack of empirical studies.
Objective: In this study, we focused on the effect of four service-based patterns - namely process abstraction, service façade, decomposed capability, and event-driven messaging - on the evolvability of a system from the viewpoint of inexperienced developers.
Method: We conducted a controlled experiment with Bachelor students (N = 69). Two functionally equivalent versions of a service-based web shop - one with patterns (treatment group), one without (control group) - had to be changed and extended in three tasks. We measured evolvability by the effectiveness and efficiency of the participants in these tasks. Additionally, we compared both system versions with nine structural maintainability metrics for size, granularity, complexity, cohesion, and coupling.
Results: Both experiment groups were able to complete a similar number of tasks within the allowed 90 min. Median effectiveness was 1/3. Mean efficiency was 12% higher in the treatment group, but this difference was not statistically significant. Only for the third task, we found statistical support for accepting the alternative hypothesis that the pattern version led to higher efficiency. In the metric analysis, the pattern version had worse measurements for size and granularity while simultaneously having slightly better values for coupling metrics. Complexity and cohesion were not impacted.
Interpretation: For the experiment, our analysis suggests that the difference in efficiency is stronger with more experienced participants and increased from task to task. With respect to the metrics, the patterns introduce additional volume in the system, but also seem to decrease coupling in some areas.
Conclusions: Overall, there was no clear evidence for a decisive positive effect of using service-based patterns, neither for the student experiment nor for the metric analysis. This effect might only be visible in an experiment setting with higher initial effort to understand the system or with more experienced developers.
Context: Fast moving markets and the age of digitization require that software can be quickly changed or extended with new features. The associated quality attribute is referred to as evolvability: the degree of effectiveness and efficiency with which a system can be adapted or extended. Evolvability is especially important for software with frequently changing requirements, e.g. internet-based systems. Several evolvability-related benefits were arguably gained with the rise of service-oriented computing (SOC) that established itself as one of the most important paradigms for distributed systems over the last decade. The implementation of enterprise-wide software landscapes in the style of service-oriented architecture (SOA) prioritizes loose coupling, encapsulation, interoperability, composition, and reuse. In recent years, microservices quickly gained in popularity as an agile, DevOps-focused, and decentralized service-oriented variant with fine-grained services. A key idea here is that small and loosely coupled services that are independently deployable should be easy to change and to replace. Moreover, one of the postulated microservices characteristics is evolutionary design.
Problem Statement: While these properties provide a favorable theoretical basis for evolvable systems, they offer no concrete and universally applicable solutions. As with each architectural style, the implementation of a concrete microservice-based system can be of arbitrary quality. Several studies also report that software professionals trust in the foundational maintainability of service orientation and microservices in particular. A blind belief in these qualities without appropriate evolvability assurance can lead to violations of important principles and therefore negatively impact software evolution. In addition to this, very little scientific research has covered the areas of maintenance, evolution, or technical debt of microservices.
Objectives: To address this, the aim of this research is to support developers of microservices with appropriate methods, techniques, and tools to evaluate or improve evolvability and to facilitate sustainable long-term development. In particular, we want to provide recommendations and tool support for metric-based as well as scenario-based evaluation. In the context of service-based evolvability, we furthermore want to analyze the effectiveness of patterns and collect relevant antipatterns. Methods: Using empirical methods, we analyzed the industry state of the practice and the academic state of the art, which helped us to identify existing techniques, challenges, and research gaps. Based on these findings, we then designed new evolvability assurance techniques and used additional empirical studies to demonstrate and evaluate their effectiveness. Applied empirical methods were for example surveys, interviews, (systematic) literature studies, or controlled experiments.
Contributions: In addition to our analyses of industry practice and scientific literature, we provide contributions in three different areas. With respect to metric-based evolvability evaluation, we identified a set of structural metrics specifically designed for service orientation and analyzed their value for microservices. Subsequently, we designed tool-supported approaches to automatically gather a subset of these metrics from machine-readable RESTful API descriptions and via a distributed tracing mechanism at runtime. In the area of scenario-based evaluation, we developed a tool-supported lightweight method to analyze the evolvability of a service-based system based on hypothetical evolution scenarios. We evaluated the method with a survey (N=40) as well as hands-on interviews (N=7) and improved it further based on the findings. Lastly with respect to patterns and antipatterns, we collected a large set of service-based patterns and analyzed their applicability for microservices. From this initial catalogue, we synthesized a set of candidate evolvability patterns via the proxy of architectural modifiability tactics. The impact of four of these patterns on evolvability was then empirically tested in a controlled experiment (N=69) and with a metric-based analysis. The results suggest that the additional structural complexity introduced by the patterns as well as developers' pattern knowledge have an influence on their effectiveness. As a last contribution, we created a holistic collection of service-based antipatterns for both SOA and microservices and published it in a collaborative repository.
Conclusion: Our contributions provide first foundations for a holistic view on the evolvability assurance of microservices and address several perspectives. Metric- and scenario-based evaluation as well as service-based antipatterns can be used to identify "hot spots" while service-based patterns can remediate them and provide means for systematic evolvability construction. All in all, researchers and practitioners in the field of microservices can use our artifacts to analyze and improve the evolvability of their systems as well as to gain a conceptual understanding of service-based evolvability assurance.
Social networks, smart portable devices, Internet of Things (IoT) on base of technologies like analytics for big data and cloud services are emerging to support flexible connected products and agile services as the new wave of 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 extending Enterprise Architecture (EA) with mechanisms for flexible adaptation and evolution of information systems having distributed IoT and other micro-granular digital architecture to support next digitization products, services, and processes. Our aim is to support flexibility and agile transformation for both IT and business capabilities through adaptive digital enterprise architectures. The present research paper investigates additionally decision mechanisms 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 and digitization.
The internet of things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud environments are emerging to support smart connected i.e. digital products and services and the digital transformation. Biological metaphors for living and adaptable ecosystems are currently providing the logical foundation for resilient run-time environments with serviceoriented digitization architectures and for self-optimizing intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution of information systems with digital architecture in the context of the ongoing digital transformation. The goal is to support flexible and agile transformations for both business and related information systems through adaptation and dynamical evolution of their digital architectures. The present research paper investigates mechanisms of decision analytics for digitization architectures, putting a spotlight to internet of things micro-granular architectures, by extending original enterprise architecture reference models with digitization architectures and their multi-perspective architectural decision management.
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.
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.
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.
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.