Measuring the Scalability of Cloud-based Software Services

Measuring and testing the performance of cloud-based software services is critically important in the context of rapid growth of cloud computing. Scalability, elasticity and efficiency are interrelated aspects of performance of cloud-based software services. Here we present a work that is focused on measuring the scalability of cloud-based software services in technical terms. We introduce technical scalability metrics inspired by earlier technical metrics of elasticity

Quantifying cloud performance and dependability:Taxonomy, metric design, and emerging challenges

In only a decade, cloud computing has emerged from a pursuit for a service-driven information and communication technology (ICT), becoming a significant fraction of the ICT market. Responding to the growth of the market, many alternative cloud services and their underlying systems are currently vying for the attention of cloud users and providers. To make informed choices between competing cloud service providers, permit the cost-benefit analysis of cloud-based systems, and enable system DevOps to evaluate and tune the performance of these complex ecosystems, appropriate performance metrics, benchmarks, tools, and methodologies are necessary. This requires re-examining old system properties and considering new system properties, possibly leading to the re-design of classic benchmarking metrics such as expressing performance as throughput and latency (response time). In this work, we address these requirements by focusing on four system properties: (i) elasticity of the cloud service, to accommodate large variations in the amount of service requested, (ii) performance isolation between the tenants of shared cloud systems and resulting performance variability, (iii) availability of cloud services and systems, and (iv) the operational risk of running a production system in a cloud environment. Focusing on key metrics for each of these properties, we review the state-of-the-art, then select or propose new metrics together with measurement approaches. We see the presented metrics as a foundation toward upcoming, future industry-standard cloud benchmarks

Digitalization of the individual : consequences, design, and behavior

In the past decades, digitalization has increasingly influenced our daily lives and habits in almost all areas and has even become indispensable for individuals, organizations, and society. The interactions between individuals and organizations have changed significantly as digitalization extends the boundaries of organizations to the point at which it affects individuals. Consequently, new research efforts and better understanding are essential to understand how the behavior of individuals is affected by the use of digital technologies, how customers demands change, and how the purchasing process of organizations needs to be adapted. Currently, the literature on digital transformation is mainly treating the organizational perspective. Nevertheless, organizations should not neglect the individual perspective as it is essential to understand customer needs and their consequences affected by digital technologies. Matt et al. (2019)1 present a holistic research framework with three research perspectives for the digitalization of the individual. This framework encompasses the behavior of individuals, the design of information systems, and the consequences that digitalization entails. Additionally, this research framework suggests that a digitized individual can take on different roles. The dissertation uses this framework of Matt et al. (2019)1 to structure and classify the covered contents and research objectives. The aim of this dissertation is to contribute to a comprehensive overview for organizations to understand their customers concerns regarding digital technologies, which design options they have to address these concerns, and how it influences their behavior to realize the potential of the technologies or reduce their harms. Therefore, this work applies pluralistic methodological approaches (qualitative methods, e.g., semi-structured interviews and qualitative content analysis, and quantitative methods, e.g., quantitative decision models and data collection from online questionnaires). With that, the dissertation provides novel insights for organizations to better implement digital technologies by regarding the consequences for individuals and the behavior of individuals. First, to contribute to an understanding of the negative consequences digitalization can bring along for individuals, part A of this dissertation presents two research articles that focus on the concerns of individuals. The research papers P1 and P2 show in two different domains what individuals are concerned about when using digital technologies and what prevents individuals from using them. Therefore, this dissertation presents knowledge about the fears and concerns of the individuals have and offers starting points to develop responsible and transparent digital technologies that address the concerns of the individuals. Second, to contribute to design approaches for information systems that enable organizations to increase customer satisfaction with digital products and services, part B presents design approaches that organizations can use to address individuals perceived consequences and change their behavior using digital technologies. Both research papers in part B present quantitative decision models as decision support for organizations. This dissertation offers two design approaches that provide organizations with information on designing technologies to serve digitized individuals and foster them better to make well-founded decisions when introducing digital technologies. Third, to contribute to the understanding of why and how individuals behave in certain ways and how this behavior can be influenced, Part C examines the behavior of individuals when using digital technologies. Research paper P5 develops a metric to better explore the privacy paradox. With that, this dissertation offers a basis, especially to researchers and individuals, to prevent unwanted behavior when using digital technologies. To sum up, this dissertation contributes to scientific knowledge in research on the digitalization of the individual and thus addresses a subject of fundamental importance in this digital age. The models and approaches developed in this dissertation explore ways to improve conditions for the digitized individual at all three research perspectives with equal regard for the individual as itself and the individual as a customer.In den vergangenen Jahrzehnten hat die Digitalisierung zunehmend unseren Alltag und unsere Gewohnheiten in nahezu Bereichen des Lebens beeinflusst und ist damit für Individuen, Organisationen und die Gesellschaft unverzichtbar geworden. So hat sich die Beziehung zwischen Individuen und Organisationen erheblich verändert, da die Digitalisierung die Organisationsgrenzen aufweicht und ihre Kund:innen mehr integriert. Folglich sind neue Forschungsanstrengungen und ein besseres Verständnis erforderlich, um nachvollziehen zu können, wie das Verhalten von Individuen durch den Einsatz digitaler Technologien beeinflusst wird, wie sich die Anforderungen von Kund:innen ändern und wie der Kaufprozess von Organisationen angepasst werden muss. Derzeit wird in der Literatur zum Themengebiet der digitalen Transformation hauptsächlich die organisationale Perspektive behandelt. Nichtsdestotrotz sollten Organisationen die individuelle Perspektive nicht vernachlässigen. Sie ist grundlegend, um die Kund:innenbedürfnisse, die durch digitale Technologien beeinflusst werden, und deren Folgen zu verstehen. Matt et al. (2019) stellen einen ganzheitlichen Forschungsrahmen mit drei Forschungsperspektiven für die Digitalisierung des Individuums vor. Dieser umfasst das Verhalten der Individuen, die Gestaltung von Informationssystemen und die Konsequenzen, die die Digitalisierung für Individuen mit sich bringen kann. Zusätzlich zeigt dieser, dass ein digitalisiertes Individuum verschiedene Rollen einnehmen kann. Die Dissertation nutzt das Framework von Matt et al. (2019), um die Inhalte und Forschungsziele zu strukturieren und einzuordnen. Ziel dieser Dissertation ist es, einen Beitrag zu einem umfassenden Überblick für Organisationen zu leisten, um die Individuen im Zuge der Digitalisierung zu verstehen. Dabei wird untersucht, welche Bedenken ihre Kund:innen in Bezug auf digitale Technologien haben, welche Gestaltungsmöglichkeiten sie haben, um diese Bedenken zu adressieren, und wie es das Verhalten von Kund:innen beeinflusst. Dadurch können sie das Potenzial dieser Technologien realisieren oder ihre Schäden reduzieren. Diese Arbeit wendet eine Vielzahl an methodischen Ansätzen an (qualitative Methoden, z.B. halbstrukturierte Interviews und qualitative Inhaltsanalyse, und quantitative Methoden, z.B. quantitative Entscheidungsmodelle und Datenerhebung aus Online-Fragebögen). Damit liefert die Dissertation neue Erkenntnisse für Organisationen, um digitale Technologien besser zu implementieren, indem sie die Konsequenzen für Individuen und das Verhalten von Individuen betrachtet. Um erstens einen Beitrag zum besseren Verständnis der negativen Folgen, die die Digitalisierung für den Einzelnen mit sich bringen kann, zu leisten, umfasst Teil A dieser Dissertation zwei Forschungsartikel, die sich mit den Bedenken des Einzelnen beschäftigen. Die Forschungsartikel P1 und P2 zeigen in zwei unterschiedlichen Bereichen, welche Bedenken Individuen bei der Nutzung digitaler Technologien haben und was Individuen davon abhält, diese zu nutzen. Daher präsentiert diese Dissertation Wissen über die Ängste und Bedenken der Individuen und bietet Ansatzpunkte, um verantwortungsvolle und transparente digitale Technologien zu entwickeln. Um zweitens einen Beitrag zu Gestaltungsansätzen für Informationssysteme zu leisten, werden in Teil B Gestaltungsansätze vorgestellt, mit denen Organisationen die wahrgenommenen Konsequenzen für Individuen adressieren und das Verhalten im Umgang mit digitalen Technologien ändern können. Diese ermöglichen es Organisationen die Kund:innenzufriedenheit bei der Nutzung von digitalen Produkten und Dienstleistungen zu erhöhen. Beide Forschungsarbeiten in Teil B stellen quantitative Entscheidungsmodelle als Entscheidungshilfe für Organisationen vor. Diese Dissertation bietet zwei Gestaltungsansätze, die Organisationen Informationen zur Gestaltung von Informationssystemen liefern und sie dabei unterstützen, fundierte Entscheidungen bei der Einführung digitaler Technologien zu treffen. Drittens, um zum Verständnis beizutragen, warum und wie sich Individuen auf bestimmte Weise verhalten und wie dieses Verhalten beeinflusst werden kann, wird in Teil C das Verhalten von Individuen bei der Nutzung digitaler Technologien untersucht. P5 entwickelt eine Metrik, um das Privacy-Paradoxon besser zu erforschen. Damit bietet diese Dissertation eine Grundlage, insbesondere für Forscherinnen und Forscher sowie Individuen, um unerwünschtes Verhalten bei der Nutzung digitaler Technologien zu verhindern. Zusammenfassend lässt sich sagen, dass diese Dissertation wissenschaftliche Erkenntnisse zur Erforschung der Digitalisierung des Individuums leistet und damit ein Thema von grundlegender Bedeutung im digitalen Zeitalter behandelt. Die in dieser Dissertation entwickelten Modelle und Ansätze zeigen Wege auf, wie die Bedingungen für das digitalisierte Individuum auf allen drei Forschungsperspektiven verbessert werden können

Scalability performance measurement and testing of cloud-based software services

Cloud-based software services have become more popular and dependable and are ideal for businesses with growing or changing workload demands. These services are increasing rapidly due to the reduced hosting costs and the increased availability and efficiency of computing resources. The delivery of cloud-based software services is based on the underlying cloud infrastructure supported by cloud providers, which delivers the potential for scalability that follows the pay-as-you-go model. Performance and scalability testing and measurements of those services are necessary for future optimisations and growth of cloud computing to support the Service Level Agreement (SLA) compliant quality of cloud services, especially in the context of rapidly expanding quantity of service delivery. This thesis addresses an important issue, understanding the scalability of cloud-based software services from a technical perspective, which is very important as more software solutions are migrated to the cloud. A novel testing and quantifying approach for the scalability performance of cloud-based software services is described. Two technical scalability metrics for software services that have been deployed and distributed in cloud environments, have been formulated: volume and quality scalability metrics based on the number of software instances and the average response time. The experimental analysis comprises three stages. The first stage involves demonstrating the approach and the metrics using real-world could-based software service running on Amazon EC2 cloud using three demand scenarios. The second stage aims to extend the practicality of the metrics with experiments on two public cloud environments (Amazon EC2 and Microsoft Azure) with two cloud-based software serices to demonstrate the use of these metrics. The experimental analysis considers three sets of comparisons to provide the platform to construct the metrics as a basis that can be used effectively to compare the scalability of software on cloud environments, consequently supporting deployment decisions with technical arguments. Moreover, the work integrates the technical scalability metrics with an earlier utility-oriented scalability metric. The third stage is a case study of application-level fault inection using real-world cloud-based software services running on Amazon EC2 cloud to demonstrate the effect of fault scenarios on the scalability behaviour. The results show that the technical metrics quantify explicitly the technical scalability performance of the cloud-based software services, and that they allow clear assessment of the impact of demand scenarios, cloud platform and fault injection on the software services’ scalability behaviour. The studies undertaken in this thesis have provided a valuable insight into the scalability of cloud-based software services delivery