Microservice Transition and its Granularity Problem: A Systematic Mapping Study

Microservices have gained wide recognition and acceptance in software industries as an emerging architectural style for autonomic, scalable, and more reliable computing. The transition to microservices has been highly motivated by the need for better alignment of technical design decisions with improving value potentials of architectures. Despite microservices' popularity, research still lacks disciplined understanding of transition and consensus on the principles and activities underlying "micro-ing" architectures. In this paper, we report on a systematic mapping study that consolidates various views, approaches and activities that commonly assist in the transition to microservices. The study aims to provide a better understanding of the transition; it also contributes a working definition of the transition and technical activities underlying it. We term the transition and technical activities leading to microservice architectures as microservitization. We then shed light on a fundamental problem of microservitization: microservice granularity and reasoning about its adaptation as first-class entities. This study reviews state-of-the-art and -practice related to reasoning about microservice granularity; it reviews modelling approaches, aspects considered, guidelines and processes used to reason about microservice granularity. This study identifies opportunities for future research and development related to reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table

Verifying big data topologies by-design: a semi-automated approach

Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topics. However, architectures that process big data involve many different components interconnected via semantically different connectors. Such complex architectures make possible refactoring of the applications a difficult task for software architects, as applications might be very different with respect to the initial designs. As an aid to designers and developers, we developed OSTIA (Ordinary Static Topology Inference Analysis) that allows detecting the occurrence of common anti-patterns across big data architectures and exploiting software verification techniques on the elicited architectural models. This paper illustrates OSTIA and evaluates its uses and benefits on three industrial-scale case-studies

Contribución a la estimulación del uso de soluciones Cloud Computing: Diseño de un intermediador de servicios Cloud para fomentar el uso de ecosistemas distribuidos digitales confiables, interoperables y de acuerdo a la legalidad. Aplicación en entornos multi-cloud.

184 p.El objetivo del trabajo de investigación presentado en esta tesis es facilitar a los desarrolladores y operadores de aplicaciones desplegadas en múltiples Nubes el descubrimiento y la gestión de los diferentes servicios de Computación, soportando su reutilización y combinación, para generar una red de servicios interoperables, que cumplen con las leyes y cuyos acuerdos de nivel de servicio pueden ser evaluados de manera continua. Una de las contribuciones de esta tesis es el diseño y desarrollo de un bróker de servicios de Computación llamado ACSmI (Advanced Cloud Services meta-Intermediator). ACSmI permite evaluar el cumplimiento de los acuerdos de nivel de servicio incluyendo la legislación. ACSmI también proporciona una capa de abstracción intermedia para los servicios de Computación donde los desarrolladores pueden acceder fácilmente a un catálogo de servicios acreditados y compatibles con los requisitos no funcionales establecidos.Además, este trabajo de investigación propone la caracterización de las aplicaciones nativas multiNube y el concepto de "DevOps extendido" especialmente pensado para este tipo de aplicaciones. El concepto "DevOps extendido" pretende resolver algunos de los problemas actuales del diseño, desarrollo, implementación y adaptación de aplicaciones multiNube, proporcionando un enfoque DevOps novedoso y extendido para la adaptación de las prácticas actuales de DevOps al paradigma multiNube

Towards Digital Twin-enabled DevOps for CPS providing Architecture-Based Service Adaptation & Verification at Runtime

Industrial Product-Service Systems (IPSS) denote a service-oriented (SO) way of providing access to CPS capabilities. The design of such systems bears high risk due to uncertainty in requirements related to service function and behavior, operation environments, and evolving customer needs. Such risks and uncertainties are well known in the IT sector, where DevOps principles ensure continuous system improvement through reliable and frequent delivery processes. A modular and SO system architecture complements these processes to facilitate IT system adaptation and evolution. This work proposes a method to use and extend the Digital Twins (DTs) of IPSS assets for enabling the continuous optimization of CPS service delivery and the latter's adaptation to changing needs and environments. This reduces uncertainty during design and operations by assuring IPSS integrity and availability, especially for design and service adaptations at CPS runtime. The method builds on transferring IT DevOps principles to DT-enabled CPS IPSS. The chosen design approach integrates, reuses, and aligns the DT processing and communication resources with DevOps requirements derived from literature. We use these requirements to propose a DT-enabled self-adaptive CPS model, which guides the realization of DT-enabled DevOps in CPS IPSS. We further propose detailed design models for operation-critical DTs that integrate CPS closed-loop control and architecture-based CPS adaptation. This integrated approach enables the implementation of A/B testing as a use case and central concept to enable CPS IPSS service adaptation and reconfiguration. The self-adaptive CPS model and DT design concept have been validated in an evaluation environment for operation-critical CPS IPSS. The demonstrator achieved sub-millisecond cycle times during service A/B testing at runtime without causing CPS operation interferences and downtime.Comment: Final published version appearing in 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2022

On the Modularization of ExplorViz towards Collaborative Open Source Development

Software systems evolve over their lifetime. Changing conditions such as requirements or customer requests make it inevitable for developers to perform adjustments to the underlying code base. Especially in the context of open source software where everybody can contribute, demands can change over time and new user groups may be addressed. In particular, research software is often not structured with a maintainable and extensible architecture. In combination with obsolescent technologies, this is a challenging task for developers, especially, when students are involved. In this paper, we report on the modularization process and architecture of our open source research project ExplorViz towards a microservice architecture, which facilitates a collaborative development process for both researchers and students. We describe the modularization measures and present how we solved occurring issues and enhanced our development process. Afterwards, we illustrate our modularization approach with our modernized, extensible software system architecture and highlight the improved collaborative development process. Finally, we present a proof-of-concept implementation featuring several developed extensions in terms of architecture and extensibility

A lingualization strategy for knowledge sharing in large-scale DevOps

DevOps has become a generally accepted practice for software projects in the last decade and approaches certain shortcomings of the agile software development and the steadily gaining popularity of cloud infrastructure. While it shifts more and more responsibilities towards software engineering teams, the prevailing opinion is to keep DevOps teams small to reduce the complexity of inter-team communication. In circumstances where products outgrow the performance capability of a single team, microservice architecture enables multiple DevOps teams to contribute to the same application and meet the increased requirements. Since DevOps teams operate typically self-sufficiently and more or less independently inside an organization, such large-scale DevOps environments are prone to knowledge-sharing barriers. Textual Domain-Specific Languages (DSLs) are one of the cornerstones of DevOps and enable key features like automation and infrastructure provisioning. Nonetheless, most commonly accepted DSLs in the context of DevOps are cumbersome and have a steep learning curve. Thus, they fall short of their potential to truly enable cross-functional collaboration and knowledge sharing, not only between development and operation, but to the whole organization. DevOps teams require tools and DSLs, that treat knowledge sharing and reuse as a first-class citizen, in order to operate sufficiently on a large scale. However, developing DSLs is still presumed as an expensive task which can easily offset the resulting benefits. This dissertation presents a lingualization strategy for addressing the challenge of knowledge sharing in large-scale DevOps. The basic idea is to provide custom-tailored Domain-Specific Modeling Languages (DSMLs) that target single phases of the DevOps lifecycle and ease the DevOps adoption for newly formed teams. The paradigm of Language-Driven Engineering (LDE) bridges the semantic gap between stakeholders by custom-tailored DSMLs and thus is a natural fit for knowledge sharing. Key to a successful practice of LDE is as a new class of stakeholders. In the context of large-scale DevOps, language development can be realized by so-called Meta DevOps teams. Those teams, which themselves practice DevOps internally, manage a centralized repository of small DSMLs and offer them as a service. DevOps teams act as the customers of the Meta DevOps teams and can request new features or complete new DSMLs and provide feedback to already existing DSMLs. The presented Rig modeling environment serves as an exemplary DSML that targets the purpose of Continuous Integration and Deployment (CI/CD), one of the most important building blocks of DevOps. Rig comes with an associated code generator to fully-generate CI/CD workflows from graphical models. Those graphical models provide an executable documentation and assist knowledge-sharing between stakeholders. The fundamental modeling concepts of the lingualization strategy are evaluated against previously published requirements by Bordeleau et al. on a DevOps modeling framework in an industrial context. In addition to that, Rig is evaluated based on results of a workshop during the 6th International School on Tool-Based Rigorous Engineering of Software Systems. Both evaluations yield encouraging results and demonstrate the potential of the lingualization strategy to break down knowledge-sharing barriers in large-scale DevOps environments