Ensuring and Assessing Architecture Conformance to Microservice Decomposition Patterns

Microservice-based software architecture design has been widely discussed, and best practices have been published as architecture design patterns. However, conformance to those patterns is hard to ensure and assess automatically, leading to problems such as architectural drift and erosion, especially in the context of continued software evolution or large-scale microservice systems. In addition, not much in the component and connector architecture models is specific (only) to the microservices approach, whereas other aspects really specific to that approach, such as independent deployment of microservices, are usually modeled in other views or not at all. We suggest a set of constraints to check and metrics to assess architecture conformance to microservice patterns. In comparison to expert judgment derived from the patterns, a subset of these constraints and metrics shows a good relative performance and potential for automation

Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making

The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences

To ensure sustainable software maintenance and evolution, a diverse set of activities and concepts like metrics, change impact analysis, or antipattern detection can be used. Special maintainability assurance techniques have been proposed for service- and microservice-based systems, but it is difficult to get a comprehensive overview of this publication landscape. We therefore conducted a systematic literature review (SLR) to collect and categorize maintainability assurance approaches for service-oriented architecture (SOA) and microservices. Our search strategy led to the selection of 223 primary studies from 2007 to 2018 which we categorized with a threefold taxonomy: a) architectural (SOA, microservices, both), b) methodical (method or contribution of the study), and c) thematic (maintainability assurance subfield). We discuss the distribution among these categories and present different research directions as well as exemplary studies per thematic category. The primary finding of our SLR is that, while very few approaches have been suggested for microservices so far (24 of 223, ?11%), we identified several thematic categories where existing SOA techniques could be adapted for the maintainability assurance of microservices

Software Architecture in Practice: Challenges and Opportunities

Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice. Despite past efforts, we have little understanding of how practitioners perform software architecture related activities, and what challenges they face. Through interviews with 32 practitioners from 21 organizations across three continents, we identified challenges that practitioners face in software architecture practice during software development and maintenance. We reported on common software architecture activities at software requirements, design, construction and testing, and maintenance stages, as well as corresponding challenges. Our study uncovers that most of these challenges center around management, documentation, tooling and process, and collects recommendations to address these challenges.Comment: Preprint of Full Research Paper, the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE '23

Exploring and categorizing maintainability assurance research for service and microservice-based systems

Im Laufe des Softwarelebenszyklus eines Programms innerhalb einer sich ständig wechselnden Softwareumgebung ist es wahrscheinlich, dass dieses Programm regelmäßig gewartet werden muss. Wartungen kosten Geld und somit ist es wichtig, dass ebensolche Wartungen effizient und effektiv durchgeführt werden können. Im Laufe der Geschichte der Softwareentwicklung traten unter anderem zwei Architekturmuster hervor: Serviceorientierte Architektur und Microservices. Da diese Architekturmuster ein hohes Maß an Wartbarkeit versprechen, wurden viele Altsysteme hin zu diesen modernen Architekturen migriert. Es kann fatale Folgen für Unternehmen haben, wenn Änderungen an einem System nicht schnell, risikofrei und fehlerfrei umgesetzt werden können. Es wurden bereits viele Forschungsarbeiten bezogen auf die Wartbarkeit von serviceorientierter Architektur publiziert. Systeme basierend auf Microservices fanden jedoch, bezogen auf Wartbarkeitssicherung, nicht viel Beachtung. Sämtliche Forschungsarbeiten befinden sich verteilt auf viele Literaturdatenbanken, wodurch ein umfassender Überblick erschwert wird. Um einen solchen Überblick bereitzustellen, führten wir im Rahmen dieser Bachelorarbeit eine systematische Literaturstudie durch, die sich mit der Wartbarkeitssicherung von serviceorienter Architektur und Systemen basierend auf Microservices beschäftigt. Zur Durchführung dieser systematischen Literaturstudie entwickelten wir eine Reihe von relevanten Forschungsfragen sowie ein striktes Forschungsprotokoll. Aufbauend auf diesem Protokoll sammelten wir insgesamt 223 Forschungsarbeiten von verschiedenen Herausgebern. Diese Arbeiten wurden bezüglich ihres Inhalts zuerst in drei Gruppen von Kategorien unterteilt (architektonisch, thematisch und methodisch). Danach wurden die jeweils relevantesten Forschungsrichtungen aus jeder thematischen Kategorie herausgearbeitet und vorgestellt. Zum Abschluss wurden deutliche Unterschiede der in den Forschungsarbeiten präsentierten Inhalte in Bezug auf serviceorientierte Architektur und Microservice-basierte Systeme herausgearbeitet und dargestellt. Unsere Ergebnisse zeigten eine deutliche Unterrepräsentation von Forschungsarbeiten zur Wartbarkeitssicherung für Microservice-basierte Systeme. Während der Untersuchung der Kategorien konnten wir diverse Forschungsrichtungen innerhalb dieser feststellen. Ein Beispiel hierfür ist die Forschungsrichtung "change impact in business processes" in der Kategorie "Change Impact and Scenarios". Abschließend konnten wir einige Unterschiede bezogen auf die gesammelten Forschungsarbeiten zwischen Systemen basierend auf einer serviceorientierten Architektur und Systemen basierend auf Microservices feststellen. Ein solcher Unterschied kann zum Beispiel in der Kategorie "Antipatterns and Bad Smells" gefunden werden. Im Vergleich zu Forschungsarbeiten, welche sich auf serviceorientierte Architektur beziehen, beinhalten Forschungsarbeiten im Zusammenhang mit Systemen auf Basis von Microservices nur grundlegende Informationen zu Antipatterns, jedoch keine Herangehensweisen, um diese zu erkennen. Aufgrund unserer Ergebnisse schlagen wir einen stärkeren Fokus auf Forschung zur Wartbarkeitssicherung in Microservice-basierten Systemen vor. Mögliche zukünftige Forschungsarbeiten könnten überprüfen, ob Herangehensweisen zur Wartbarkeitssicherung von serviceorientierter Architektur auch bei Microservices anwendbar sind. Darüber hinaus schlagen wir die Durchführung von systematischen Literaturstudien vor, welche Themen wie "runtime adaptation", "testing" und "legacy migration" untersuchen, da diese Themen in unserer Literaturstudie ausgeschlossen wurden.It is very likely that software running in an everchanging environment needs to evolve at multiple points during its lifecycle. Because maintenance costs money, it is important for such tasks to be as effective and efficient as possible. During the history of software development service- and microservice-based architectures have emerged among other architectures. Since these architectures promise to provide a high maintainability, many legacy systems are or were migrated towards a service- or microservice-based architecture. In order to keep such systems running, maintenance is inevitable. While a lot of research has been published regarding maintainability assurance for service-based systems, microservice-based systems have not gotten a lot of attention. All published research is spread across several scientific databases which makes it difficult to get an extensive overview of existing work. In order to provide such overview of maintainability assurance regarding service- and microservice-based systems, we conducted a systematic literature review. To support our literature review, we developed a set of meaningful research questions and a rigid research protocol. Based on our protocol we collected a set of 223 different papers. These papers were first categorized into a threefold set of categories (architectural, thematical and methodical). After that, the most relevant research directions from each thematical category were extracted and presented. Lastly, we extracted and presented notable differences between approaches relating to service-oriented architecture or microservice-based systems. Our findings show a clear underrepresentation of maintainability assurance approaches suitable for microservice-based systems. We further discovered that regarding our formed categories, we could find several research directions such as change impact in business processes in "Change Impact and Scenarios". In the end, we could identify some differences between service- and microservice-based systems concerning approaches we retrieved in this thesis. A difference, for example was that in comparison with papers related to service-oriented architecture in "Antipatterns and Bad Smells", microservices related papers only contained basic information on antipatterns, but no approaches to detect them. Due to our findings we suggest a higher participation in research regarding maintainability assurance for microservice-based systems. Possible future work in this area could include further research on the applicability of service-oriented maintainability assurance approaches or techniques in microservice-based systems. Furthermore, future researchers could conduct follow-up literature reviews and investigate topics such as runtime adaptation, testing and legacy migration, since we excluded such topics from this thesis

Road to Microservices

This document intends to elucidate the complexity of microservices decomposition and this its inherent process of implementation. Developments in technology and design, achieving higher performance, reliability, or lowering costs are valid reasons to consider controlling the product’s quality by guaranteeing its conformance with established characteristics and standards. Control is made possible by adding quality control, inspection routines, and trend analysis to a manufacturing process. These techniques are established in the Quality field academically and business-wise. Repeat Part Management (RPM) is software that allows users to apply these techniques efficiently and has brought value to the company. However, RPM has been growing, and issues have emerged due to customer needs - accumulated technical debt. These ever-growing modifications are common through different business areas, and architectures’ research evolution has accompanied them. This demand for highly modifiable, rapid development, and independent systems has resulted in the adoption of microservices. There is a concern for existing systems for decomposition due to the characteristics of microservices, which encourages approach/technique research. This architecture promotes legacy system analysis to map current functionalities and dependencies between components. Furthermore, critical concepts in a microservices architecture are researched and implemented in a new system that encompasses Repeat Part Management’s functionalities. This thesis explores the microservices’ architecture evolution with an already defined mature domain in quality assessment.Este documento pretende especificar a complexidade do processo de decomposição em microsserviços e do seu processo de implementação. Avanços na tecnologia e design, alcançar melhor performance, ou a confiabilidade do produto, ou diminuir custos são justificações válidas para considerar controlar a qualidade do produto e, inerentemente, garantir a sua conformidade com as características previamente definidas e com padrões da indústria. É possível garantir controlo sob os produtos ao acrescentar, ao processo produtivo, métodos de controlo de qualidade, rotinas de inspeção e análise de tendências (de desvio). Estas técnicas estão bem estabelecidas academicamente e, de um ponto de vista do mercado, na área da Qualidade e garantia da qualidade. O Repeat Part Management (RPM) é um software que permite aos seus utilizadores a utilização eficiente destas técnicas de qualidade, o que resulta numa adição de valor para a empresa. Porém, devido às crescentes necessidades dos clientes, alguns problemas têm sido identificados - relacionados com o conceito de acumulação de technical debt. Esta crescente necessidade de alteração é comum em diversas áreas de negócio, e a investigação de soluções arquiteturais tem acompanhado esta pesquisa. Esta solução arquitetura pode ser caracterizada pela facilidade de sistemas facilmente modificáveis, pelo rápido desenvolvimento e implementação, e pela independência dos serviços decompostos. Aquando de uma migração para microsserviços num sistema maturo, existe uma maior preocupação na decomposição da aplicação e definição dos serviços dada a característica dos microsserviços, o que incentiva a uma pesquisa detalhada sobre as técnicas de decomposição. Pela mesma razão, esta arquitetura incentiva ao mapeamento e documentação das dependências entre serviços e componentes e o estudo da aplicação legacy. Para além disto, estes conceitos, e a sua implementação devem ser planeados, justificados e documentados, o que explica a complexidade do processo de migração e implementação, que deve ter em consideração as funcionalidades existentes no Repeat Part Management. Dessa forma, esta tese explora a implementação desta arquitetura numa aplicação matura na área de Garantia de Qualidade

Generic analysis support for understanding, evaluating and comparing enterprise architecture models

Enterprise Architecture Management (EAM) is one mean to deal with the increasing complexity of today’s IT landscapes. Architectural models are used within EAM to describe the business processes, the used applications, the required infrastructure as well as the dependencies between them. The creation of those models is expensive, since the whole organization and therewith a large amount of data has to be considered. It is important to make use of these models and reuse them for planning purposes and decision making. The models are a solid foundation for various kinds of analyses that support the understanding, evaluation and comparisons of them. Analyses can approximate the effects of the retirement of an application or of a server failure. It is also possible to quantify the models using metrics like the IT coverage of business processes or the workload of a server. The generation of views sets the focus on a specific aspect of the model. An example is the limitation to the processes and applications of a specific organization unit. Architectural models can also be used for planning purposes. The development of a target architecture is supported by identifying weak points and evaluating planning scenarios. Current approaches for EAM analysis are typically isolated ones, addressing only a limited subset of the different analysis goals. An integrated approach that covers the different information demands of the stakeholders is missing. Additionally, the analysis approaches are highly dependent on the utilized meta model. This is a serious problem since the EAM domain is characterized by a large variety of frameworks and meta models. In this thesis, we propose a generic framework that supports the different analysis activities during EAM. We develop the required techniques for the specification and execution of analyses, independently from the utilized meta model. An analysis language is implemented for the definition and customization of the analyses according to the current needs of the stakeholder. Thereby, we focus on reuse and a generic definition. We utilize a generic representation format to be able to abstract from the great variety of used meta models in the EAM domain. The execution of the analyses is done with Semantic Web Technologies and data-flow based model analysis. The framework is applied for the identification of weak points as well as the evaluation of planning scenarios regarding consistency of changes and goal fulfillment. Two methods are developed for these tasks, as well as respective analysis support is identified and implemented. These are, for example, a change impact analysis, specific metrics or the scoping of the architectural model according to different aspects. Finally, the coverage of the framework regarding existing EA analysis approaches is determined with a scenario-based evaluation. The applicability and relevance of the language and of the proposed methods is proved within three large case studies

Identifying Requirements in Microservice Architectural Systems

Microservices and microservice architecture has grown popularity and interest steadily since 2014 but many challenges are still faced in a software project when trying to adopt the concept. This work gathers challenges, possible solutions, and requirements related to the use of microservice architecture and therefore support the work of different stakeholders in a software project using microservice architecture, while also providing more information to the research as well. The study was conducted using systematic literature review (SLR). Overall, 63 scientific publications from four different scientific databases were selected and analysed. As a result, rapid evolution, life cycle management, complexity, performance, and a large number of integrations were identified as the most common challenges of microservice architecture. Solutions such as service orchestration, fog computing, decentralized data, and use of patterns were proposed to tackle these challenges. Regarding requirements, scalability, efficiency, flexibility, loose coupling, performance, and security appeared most frequently in the literature. The key finding of this work was the importance of data. How data acts as a base for functionalities and when inaccurate can cause complex challenges and make functionalities worthless. Based on this, we have a better understanding on what challenges may occur and what to focus on while working with microservice architecture in software development

Microservice API Evolution in Practice: A Study on Strategies and Challenges

Nowadays, many companies design and develop their software systems as a set of loosely coupled microservices that communicate via their Application Programming Interfaces (APIs). While the loose coupling improves maintainability, scalability, and fault tolerance, it poses new challenges to the API evolution process. Related works identified communication and integration as major API evolution challenges but did not provide the underlying reasons and research directions to mitigate them. In this paper, we aim to identify microservice API evolution strategies and challenges in practice and gain a broader perspective of their relationships. We conducted 17 semi-structured interviews with developers, architects, and managers in 11 companies and analyzed the interviews with open coding used in grounded theory. In total, we identified six strategies and six challenges for REpresentational State Transfer (REST) and event-driven communication via message brokers. The strategies mainly focus on API backward compatibility, versioning, and close collaboration between teams. The challenges include change impact analysis efforts, ineffective communication of changes, and consumer reliance on outdated versions, leading to API design degradation. We defined two important problems in microservice API evolution resulting from the challenges and their coping strategies: tight organizational coupling and consumer lock-in. To mitigate these two problems, we propose automating the change impact analysis and investigating effective communication of changes as open research directions

QoS-Based Optimization of Runtime Management of Sensing Cloud Applications

Die vorliegende Arbeit präsentiert Ansätze und Techniken zur qualitätsbewussten Verbesserung des Laufzeitmanagements von IoT-Anwendungen. IoT-Anwendungen nehmen über die Sensorik von Smart Devices ihre Umgebung wahr, um diese zu analysieren oder mit ihr zu interagieren. Smart Devices sind in der Rechen- und Speicherleistung begrenzt, weshalb viele IoT-Anwendungen über eine IoT Plattform mit elastischen und skalierbaren Cloud Services verbunden sind. Die Last auf dem Cloud Service entsteht durch die verbundenen Smart Devices, die kontinuierlich Nachrichten transferieren. Die Ressourcenkonfiguration des Cloud Services beeinflusst dessen Kapazität. Ein Service Operator, der eine IoT-Anwendung betreibt, ist mit der Herausforderung konfrontiert, die Smart Devices und den Cloud Service so zu konfigurieren, dass eine hohe Datenqualität bei niedrigen Betriebskosten erreicht wird. Um hierbei den Service Operator zur Design Time zu unterstützen, modellieren wir Kostenfunktionen für Datenqualitäten, die durch das Wechselspiel der Smart Device- und Cloud Service-Konfiguration beeinflusst werden. Mit Hilfe dieser Kostenfunktionen kann ein Service Operator nach einer kostenminimalen Konfiguration für bestimmte Szenarien suchen. Existierende Ansätze zur Optimierung von Anwendungen zur Design Time fokussieren sich auf traditionelle Software-Architekturen und bieten daher nicht die notwendigen Konzepte zur Kostenmodellierung von IoT-Anwendungen an. Des Weiteren unterstützen wir den Service Operator durch Lastkontrollverfahren, die auf Kapazitätsengpässe des Cloud Services durch eine kontrollierte Reduktion der Nachrichtenrate reagieren. Während sich das auf die Genauigkeit der Messungen nachteilig auswirken kann, stabilisieren sich zeitliche Verzögerungen und die IoT-Anwendung bleibt auch in starken Überlastszenarien verfügbar. Existierende Laufzeittechniken fokussieren sich auf die automatische Ressourcenprovisionierung von Cloud Services durch Auto-Scaler. Diese ermöglichen zwar, auf Kapazitätsengpässe und Lastschwankungen zu reagieren, doch die erreichte Quality-of-Service (QoS) kann dadurch mit hohen Betriebskosten verbunden sein. Daher ermöglichen wir durch die Lastkontrollverfahren eine weitere Technik, mit der einerseits dynamisch auf Kapazitätsengpässe reagiert werden und andererseits die zur Verfügung stehende Kapazität eines Cloud Services effizient genutzt werden kann. Außerdem präsentieren wir Kopplungstechniken, die Auto-Scaling und Lastkontrollverfahren kombinieren. Bestehende Ansätze zur Rekonfiguration von Smart Devices konzentrieren sich auf Qualitäten wie Genauigkeit oder Energie-Effizienz und sind daher ungeeignet, um auf Kapazitätsengpässe zu reagieren. Zusammenfassend liefert die Dissertation die folgenden Beiträge: 1. Untersuchung von Performance Metriken für Skalierentscheidungen: Wir haben Infrastuktur- und Anwendungsebenen-Metriken daraufhin evaluiert, wie geeignet sie für Skalierentscheidungen von Microservices sind, die variierende Charakteristiken aufweisen. Auf Basis der Ergebnisse kann ein Service Operator eine fundierte Entscheidung darüber treffen, welche Performance Metrik zur Skalierung eines bestimmten Microservices am geeignesten ist. 2. Design von QoS Kostenfunktionen für IoT-Anwendungen: Wir haben ein QoS Kostenmodell aufgestellt, dass das Wirken von Smart Device- und Cloud Service-Konfiguration auf die Qualitäten einer IoT-Anwendung erfasst. Auf Grundlage dieser Kostenmodelle kann die Konfiguration von IoT-Anwendungen zur Design Time optimiert werden. Des Weiteren können mit den Kostenfunktionen Laufzeitverfahren hinsichtlich ihrem Beitrag zur QoS für verschiedene Szenarien evaluiert werden. 3. Entwicklung von Lastkontrollverfahren für IoT-Anwendungen: Die präsentierten Verfahren bieten einen komplementären Mechanismus zu Auto-Scaling an, um bei Kapazitätsengpässen die QoS aufrechtzuerhalten. Hierbei wird die Gesamtlast auf dem Cloud Service durch Anpassungen der Nachrichtenrate der Smart Devices reduziert. Ein Service Operator hat hiermit die Möglichkeit, Kapazitätsengpässen über eine Degradierung der Datenqualität zu begegnen. 4. Kopplung von Lastkontrollverfahren mit Ressourcen-Provisionierung: Wir präsentieren regelbasierte Kopplungsmechanismen, die reaktiv Lastkontrollverfahren oder Auto-Scaler aktivieren und diese damit koppeln. Das ermöglicht, auf Kapazitätsengpässe über eine Kombination von Datenqualitätsreduzierungen und Ressourcekostenerhöhungen zu reagieren. 5. Design eines Frameworks zur Entwicklung selbst-adaptiver Systeme: Das selbst-adaptive Framework bietet ein Anwendungsmodell für IoT-Anwendungen und Konzepte für die Rekonfiguration von Microservices und Smart Devices an. Es kann in verschiedenen Cloud-Umgebungen aufgesetzt werden und beschleunigt die prototypische Entwicklung von Laufzeitverfahren. Wir validierten die Ansätze anhand zweier Case Study Systeme unterschiedlicher Komplexität. Das erste Case Study System besteht aus einem Cloud Service, welcher über eine IoT Plattform Nachrichten von virtuellen Smart Devices verarbeitet. Mit diesem System haben wir für unterschiedliche Anwendungsszenarien die Charakteristiken der vorgestellten Lastkontrollverfahren analysiert, um diese gegen Auto-Scaling und einer Kopplung der Ansätze zu vergleichen. Hierbei stellte sich heraus, dass die Lastkontrollverfahren ähnlich effizient wie Auto-Scaler Überlastszenarien addressieren können und sich die QoS in einem vergleichbaren Bereich bewegt. Im Schnitt erreichten die Lastkontrollverfahren in den untersuchten Szenarien etwa 50 % geringere QoS Gesamtkosten. Es zeigte sich auch, dass sowohl Auto-Scaling als auch die Lastkontrollverfahren in bestimmten Anwendungsszenarien deutliche Nachteile haben, so z. B. wenn die Datengenauigkeit oder Ressourcenkosten im Vordergrund stehen. Es hat sich gezeigt, dass eine Kopplung hierbei immer vorteilhaft ist, um die QoS beizubehalten. Im zweiten Case Study System haben wir eine intelligente Heizungslösung der Robert Bosch GmbH implementiert, um die Ansätze an einem komplexeren System zu validieren. Auch hier zeigte sich, dass eine Kombination von Lastkontrolle und Auto-Scaling am vorteilhaftesten ist und zu einer hohen Datenqualität bei geringen Ressourcenkosten beiträgt. Die Ergebnisse zeigen, dass die vorgestellten Lastkontrollverfahren geeignet sind, die QoS von IoT Anwendungen zu verbessern. Es bietet einem Service Operator damit ein weiteres Werkzeug für das Laufzeitmanagement von IoT Anwendungen, dass einen zum Auto-Scaling komplementären Mechanismus verwendet. Das hier vorgestellte Framework zur Entwicklung selbst-adaptiver IoT Systeme haben wir zur empirischen Beantwortung der Forschungsfragen instanziiert und damit dessen Eignung demonstriert. Wir zeigen außerdem eine exemplarische Verwendung der vorgestellten Kostenfunktionen für verschiedene Anwendungsszenarien und binden diese im Zuge der Validierung in einem Optimierungs-Framework ein