[pt] Microsserviços é uma técnica industrial para promover melhor escalabilidade e manutenibilidade de pequenos e autônomos serviços. Estudos prévios sugerem que a arquitetura de microsserviços vem sendo amplamente usada para reduzir limitações encontradas em sistemas monolíticos legados tais como melhoria de inovação, uso de diferentes tecnologias, entre outras. O processo de migração para a arquitetura de microsserviços não é trivial. Este é particularmente o caso da tarefa de identificar candidatos a microsserviço e o código fonte associado com cada candidato que é dispendiosa e propensa a erro. Consequentemente, abordagens automatizadas têm sido propostas para reduzir o esforço relacionado a essa atividade. Essas abordagens comumente adotam um ou dois critérios para suportar a identificação de microsserviços com base no sistema monolítico legado. Contudo, existe uma falta de compreensão da utilidade desses critérios adotados na prática. Além disso, há limitado conhecimento em quais são os critérios que profissionais consideram relevantes. Levando em consideração esses limitantes existentes, nós conduzimos um survey e entrevista para melhor compreender a utilidade de critérios relatados em estudos empíricos (e.g, estudos de caso e relatos) do ponto de vista dos profissionais. Os resultados do survey e da entrevista mostram que as abordagens automatizadas e ferramentas existentes não são totalmente alinhadas com necessidades práticas. Para atender às necessidades deles, este trabalho define uma abordagem automatizada chamada toMicroservices. A abordagem baseia-se em uma combinação de análise estática e dinâmica do código legado. A abordagem visa indicar os candidatos a microsserviço e a fonte correspondente extraído do sistema legado. toMicroservices faz uso da engenharia de software baseada em busca para otimizar e balancear os cinco critérios comumente adotados por profisionais, nomeados de modularização de funcionalidade, redução de sobrecarga de rede, reúso, acoplamento e coesão. Além disso, um estudo de caso e grupo focal foram conduzidos a posteriori para avaliar e melhorar toMicroservices. / [en] Microservices is an industrial technique to promote better scalability and maintainability of small and autonomous services. Previous studies suggested that microservice architectures have been widely used to reduce limitations found in legacy monolithic systems such as the inclusion of innovation, use of a different stack of technologies, among others. The process of migrating to a microservices architecture is far from trivial. This is particularly the case for the task of identifying candidate microservices and the source code associated with each candidate, which is recognizably time-consuming and error-prone. Thus, automated approaches have been proposed to reduce the effort related to that task. These approaches commonly adopt one or two criteria to support the identification of microservices from a legacy monolithic system. However, there is a lack of understanding on the usefulness of these criteria in practical settings. Moreover, there is limited knowledge on what are the criteria that practitioners consider relevant. Taking into account these existing limitations, we conducted a survey and interviews to better understand the usefulness of criteria reported in empirical studies (e.g, case studies and reports) from the point of view of practitioners. The results of the survey and interviews revealed that existing automated approaches and tools are far from being aligned with practical needs. To fulfill these needs, this work defines a automated approach named toMicroservices. The approach relies on a combination of static and dynamic analysis of the legacy code. The approach aims at indicating the microservice candidates and the corresponding source extracted from the legacy system. toMicroservices makes use of search-based software engineering (SBSE) to optimize and balance the five criteria commonly adopted by practitioners, namely feature modularization, network overhead reduction, reuse, coupling and cohesion. Additionally, an industrial case study and a focus group were conducted a posteriori to support the evaluation and improvements of toMicroservices.

Smart City technologies emerge as a potential solution to tackle common problems in large urban centers by using city resources efficiently and providing quality services for citizens. Despite the various advances in middleware technologies to support future smart cities, there are yet no widely accepted platforms. Most of the existing solutions do not provide the required flexibility to be shared across cities. Moreover, the extensive use and development of non-open-source software leads to interoperability issues and limits the collaboration among R&D groups. Our research explores the use of a microservices architecture to address key practical challenges in smart city platforms. More specifically, we are concerned with the impact of microservices on addressing the key non-functional requirements to enable the development of smart cities such as supporting different scalability demands and providing a flexible architecture which can easily evolve over time. To this end, we are developing InterSCity, a microservice-based open source smart city platform that aims at supporting the development of sophisticated, cross- domain applications and services. Our early experience shows that microservices can be properly used as building blocks to achieve a loosely coupled, flexible architecture. Experimental results point towards the applicability of our approach in the context of smart cities since the platform can support multiple scalability demands. We expect to enable collaborative, novel smart city research, development, and deployment initiatives through the InterSCity platform. The full validation of the platform will be conducted using different smart city scenarios and workloads. Future work comprises the ongoing design and development effort on data processing services as well as more comprehensive evaluation of the proposed platform through scalability experiments. / As tecnologias de Cidades Inteligentes surgem como uma potencial solução para lidar com problemas comuns em grandes centros urbanos, utilizando os recursos da cidade de maneira eficiente e fornecendo serviços de qualidade para os cidadãos. Apesar dos vários avanços nas tecnologias de middleware para suporte às cidades inteligentes do futuro, ainda não existem plataformas amplamente aceitas. A maioria das soluções existentes não oferece a flexibilidade necessária para ser compartilhada entre as cidades. Além disso, o vasto uso e desenvolvimento de software proprietário levam a problemas de interoperabilidade e limitam a colaboração entre grupos de P&D. Nesta dissertação, exploramos uso de uma arquitetura de microsserviços para abordar os principais desafios práticos em plataformas de cidades inteligentes. Mais especificamente, estamos preocupados com o impacto dos microsserviços sobre requisitos não-funcionais para permitir o desenvolvimento de cidades inteligentes, tais como o suporte a diferentes demandas de escalabilidade e o fornecimento de uma arquitetura flexível que pode evoluir facilmente. Para esse fim, criamos a InterSCity, uma plataforma para cidades inteligentes de código aberto baseada em microsserviços que visa apoiar o desenvolvimento de aplicativos e serviços sofisticados em múltiplos domínios. Nossa experiência inicial mostra que os microsserviços podem ser usados adequadamente como blocos de construção para obter uma arquitetura flexível e fracamente acoplada. Resultados experimentais apontam para a aplicabilidade de nossa abordagem no contexto de cidades inteligentes, já que a plataforma pode suportar diferentes demandas de escalabilidade. Esperamos permitir pesquisas colaborativas e inovadoras em cidades inteligentes, assim como o desenvolvimento e iniciativas de implantações reais através da plataforma InterSCity. A validação completa da plataforma será realizada usando diferentes cenários de cidades inteligentes e cargas de trabalho. Os trabalhos futuros compreendem o esforço contínuo de projetar e desenvolver novos serviços de processamento de dados, bem como a realização de avaliações mais abrangentes da plataforma proposta por meio de experimentos de escalabilidade.

As a system grows in size, it is common that it is transformed into a microservice architecture. In order to be able monitor this new architecture there is a need to collect information from the microservices. The software company IDA Infront is transitioning their product iipax to a microservice architecture and is faced with this problem. In order to solve this, they propose the use of a Message-oriented Middleware (MOM). There exists many different MOMs that are suitable to execute this task. The aim of this thesis is to determine, in terms of latency, throughput and scalability, which MOM is best suitable for this. Out of four suitable MOMs Apache Kafka and RabbitMQ are chosen for further testing and benchmarking. The tests display that RabbitMQ is able to send single infrequent messages (latency) faster than Kafka. But it is also shown that Kafka is faster at sending a lot of messages rapidly and with an increased number of producers sending messages (throughput and scalability). However, the scalability test suggests that RabbitMQ possibly scales better with a larger amount of microservices, thus more testing is needed to get a definite conclusion.

There are limited tools to evaluate a microservice architecture and no common definition of how the architecture should be designed. Moreover, developing systems with microservices introduces additional complexity to the software architecture. That, together with the fact the systems are becoming more complex has led to a desire for architecture evaluation methods. In this thesis a set of quality attributes measured by structural metrics are used to evaluate Scania's IoT Offboard platform. By implementing a metrics evaluation program the quality of the software architecture can be improved. Also, metrics can assist developers and architects while they are becoming more efficient since they better understand how performance is measured, i.e. which quality attributes are the most important and how these are measured. For Scania's IoT Offboard platform the studied quality attributes are listed in decreasing importance: flexibility, reusability and understandability. All the microservices are loosely coupled in the platform, which results in a loosely coupled architecture. This indicates a flexible, reusable and understandable system, in terms of coupling. Furthermore, the architecture is decentralized, i.e. the system is unflexible and difficult to change. The other metrics were lacking a reference scale, hence they will act as a point of reference for future measurements as the architecture evolves. To improve the flexibility, reusability and understandability of the architecture the large microservices should be divided into several smaller microservices. Also aggregators should be utilized more to make the system more flexible.

本研究之重點是在金融科技上提供一個平台，平台的服務流程以理財機器人為例，使用雲端技術，以微服務的概念實作各服務的功能，並使用MQTT訊息佇列作為服務之間的溝通，打造一個能分散運算R語言的環境，讓投資人可以透過前端的瀏覽器去選擇適當的基金，並計算適當的投資比例，提供投資人作為投資基金的參考。 平台中基金篩選的方式是透過4433法則來篩選，選出過去長、中、短期績效優良之基金，下一步再將基金篩選的結果透過效率前緣、切線投資組合、平均權重不同的演算法計算資金分配，依不同演算法算出共三組不同比例的投資權重，提供投資人作為投資基金之參考，本研究使用2010年到2014年共五年的基金資料去做基金篩選及資金分配計算，再用2015年一整年的資料計算效益。透過切線投資組合演算法所算出的投資權重，在2015年1月到2015年6月投資六個月時得到最佳的報酬率為22%。

Smart City technologies emerge as a potential solution to tackle common problems in large urban centers by using city resources efficiently and providing quality services for citizens. Despite the various advances in middleware technologies to support future smart cities, there are yet no widely accepted platforms. Most of the existing solutions do not provide the required flexibility to be shared across cities. Moreover, the extensive use and development of non-open-source software leads to interoperability issues and limits the collaboration among R&D groups. Our research explores the use of a microservices architecture to address key practical challenges in smart city platforms. More specifically, we are concerned with the impact of microservices on addressing the key non-functional requirements to enable the development of smart cities such as supporting different scalability demands and providing a flexible architecture which can easily evolve over time. To this end, we are developing InterSCity, a microservice-based open source smart city platform that aims at supporting the development of sophisticated, cross- domain applications and services. Our early experience shows that microservices can be properly used as building blocks to achieve a loosely coupled, flexible architecture. Experimental results point towards the applicability of our approach in the context of smart cities since the platform can support multiple scalability demands. We expect to enable collaborative, novel smart city research, development, and deployment initiatives through the InterSCity platform. The full validation of the platform will be conducted using different smart city scenarios and workloads. Future work comprises the ongoing design and development effort on data processing services as well as more comprehensive evaluation of the proposed platform through scalability experiments. / As tecnologias de Cidades Inteligentes surgem como uma potencial solução para lidar com problemas comuns em grandes centros urbanos, utilizando os recursos da cidade de maneira eficiente e fornecendo serviços de qualidade para os cidadãos. Apesar dos vários avanços nas tecnologias de middleware para suporte às cidades inteligentes do futuro, ainda não existem plataformas amplamente aceitas. A maioria das soluções existentes não oferece a flexibilidade necessária para ser compartilhada entre as cidades. Além disso, o vasto uso e desenvolvimento de software proprietário levam a problemas de interoperabilidade e limitam a colaboração entre grupos de P&D. Nesta dissertação, exploramos uso de uma arquitetura de microsserviços para abordar os principais desafios práticos em plataformas de cidades inteligentes. Mais especificamente, estamos preocupados com o impacto dos microsserviços sobre requisitos não-funcionais para permitir o desenvolvimento de cidades inteligentes, tais como o suporte a diferentes demandas de escalabilidade e o fornecimento de uma arquitetura flexível que pode evoluir facilmente. Para esse fim, criamos a InterSCity, uma plataforma para cidades inteligentes de código aberto baseada em microsserviços que visa apoiar o desenvolvimento de aplicativos e serviços sofisticados em múltiplos domínios. Nossa experiência inicial mostra que os microsserviços podem ser usados adequadamente como blocos de construção para obter uma arquitetura flexível e fracamente acoplada. Resultados experimentais apontam para a aplicabilidade de nossa abordagem no contexto de cidades inteligentes, já que a plataforma pode suportar diferentes demandas de escalabilidade. Esperamos permitir pesquisas colaborativas e inovadoras em cidades inteligentes, assim como o desenvolvimento e iniciativas de implantações reais através da plataforma InterSCity. A validação completa da plataforma será realizada usando diferentes cenários de cidades inteligentes e cargas de trabalho. Os trabalhos futuros compreendem o esforço contínuo de projetar e desenvolver novos serviços de processamento de dados, bem como a realização de avaliações mais abrangentes da plataforma proposta por meio de experimentos de escalabilidade.

The microservice architecture is a new architectural style that structures an application into a set of small, independently deployable microservices, as opposed to the traditional monolith approach with a single executable. The microservice architecture is a distributed system that results in new challenges and increased complexity. This study expands the previous related research and investigates the implications of using the one-database-per-service pattern and a solution to the introduced need of queries spanning multiple microservices. In this thesis, two applications are presented, one with the microservice architecture and one monolithic counterpart, which are compared in terms of response time and throughput. As a solution for the distributed queries, the API Composition pattern was chosen. The results of the experiments conclude in a greater understanding of the difficulty in distributed queries as well as the benefits and limitations of the API composition pattern. It shows that the API composition pattern is a valid solution for distributed queries. However, it does perform worse in terms of response time and throughput than the monolith prototype. This results in the insights that one must carefully choose, with respect to the requirements of the system, when to apply it.

Serverless or Function-as-a-Service (FaaS) is a recent architectural style that is based on the principles of abstracting infrastructure management and scaling to zero, meaning application instances are dynamically started and shut down to accommodate load. This concept of no idling servers and inherent autoscaling comes with benefits but also drawbacks. This study presents an evaluation of the performance and implications of the serverless architecture and contrasts it with the so-called monolith architectures. Three distinct architectures are implemented and deployed on the FaaS platform Microsoft Azure Functions as well as the PaaS platform Azure Web App. Results were produced through experiments measuring cold starts, response times, and scaling for the tested architectures as well as observations of traits such as cost and vendor lock-in. The results indicate that serverless architectures, while it is subjected to drawbacks such as vendor lock-in and cold starts, provides several benefits to a system such as reliability and cost reduction.

Microservice-Architekturen haben sich mittlerweile etabliert und werden von immer mehr Firmen übernommen. Die erhöhte Komplexität der Microservice-Architektur aufgrund der Verteilung des Systems hat jedoch zur Folge, dass die effiziente und erfolgreiche Administration des Systems erschwert wird. Ziel der Arbeit ist es, alle notwendigen Metriken für ein effizientes und erfolgreiches Microservice-Monitoring zu identifizieren und auf Basis dieser Erkenntnisse das Linkerd-Dashboard prototypisch weiterzuentwickeln. Hierfür wurde eine Literaturrecherche durchgeführt. Darüber hinaus wurden Praktiker mittels eines Online-Fragebogens befragt. Abschließend wurde die prototypische Weiterentwicklung mithilfe eines halbstrukturierten Interviews evaluiert. Die Literaturrecherche ergab, dass Central-Processing-Unit (CPU)- und Random-Access-Memory (RAM)-Nutzung, Antwortzeit, Workload, Fehlerrate und Service-Interaktion eine Metrik-Menge sind, mit der Microservice-Architekturen effektiv überwacht werden können. Außerdem konnte konstatiert werden, dass die Darstellung der Metriken hauptsächlich mit Visualisierungen realisiert wird. CPU- und RAM-Auslastung sind eine sinnvolle Erweiterung des Linkerd-Dashboards, da diese in der Literatur sowie im Fragebogen als wichtige Kennzahlen deklariert und alle anderen als essenziell eingestuften Metriken bereits vom Linkerd-Dashboard abgedeckt werden. Der Prototyp wurde als gelungen eingestuft, benötigt aber einige kleinere Verbesserungen der Visualisierung, bevor er in der Produktion eingesetzt werden kann.

This study aims to examine the effects of transforming a monolithic server system into a microservice architecture, focusing on the increased latency introduced by using a microservice orchestrator. The microservice orchestrator was implemented using an OpenFlow switch controlled by the Beacon and Ryu OpenFlow controllers. These controllers, along with the round robin, random assign and a server-aware load balancing algorithm, were all compared in order to find the combination resulting in the lowest latency and highest achieved server balance in varying network environments. We show that the OpenFlow switch enforces a client-aware load balancing policy and that only the initial request is handled by the controller, effectively reducing the importance of choosing the optimal OpenFlow controller. In addition, the round robin load balancer was preferred when dealing with homogeneous requests, and a server-aware load balancer was required for heterogeneous requests. For most requests, the system would only slow down by a few microseconds using the proposed architecture. However, for 0.001\% of all requests, the slowdown was much more significant, with each of those requests being at least 100 times slower than when using a monolithic server architecture.