This thesis examines the applicability of cloud computing systems in project management. The main objective is the definition of the requirements on a project management software tool and their subsequent application in the specific area of cloud software providers. The theoretical part of the thesis studies the essential aspects of the principle of software provision services. The first part is dedicated to the history and general definition of the concept of cloud computing. The second theoretical part describes the basic principles of project management. Project management is not examined as a whole but instead, the emphasis is put on a specific area of human resources management. The theoretical part also contains the definition of the requirements, which are used as assessment standards for the practical part of the thesis. The practical part introduces an overview of 10 selected providers of cloud-based applications. The previously defined assessment standards are applied subsequently on each subject. The generated evaluation data are used to verify the defined hypotheses supporting the concept of cloud computing applications in project management.

Les organisations adoptent de plus en plus les Systèmes (PAIS) pour gérer leurs processus métiers basés sur les services en utilisant les modèles de processus appelés «modèles de processus métiers». Motivés par l’adaptation aux exigences commerciales et par la réduction des coûts de maintenance, les organisations externalisent leurs processus dans le Cloud Computing. Selon l'Institut NIST, Cloud Computing est un modèle qui permet aux fournisseurs de partager leurs ressources et aux utilisateurs d’y accéder de manière pratique et à la demande. Dans un tel environnement multi-tenant, l'utilisation de modèles de processus configurables permet aux fournisseurs de processus Cloud de fournir un processus personnalisable qui peut être configuré par différents tenants en fonction de leurs besoins.Un processus métier peut être spécifié par plusieurs perspectives tel que la perspective de flux de contrôle, la perspective des ressources, etc. Plusieurs approches ont été proposées au niveau des premières perspectives, notamment le flux de contrôle. Cependant, la perspective ressource, qui est d'une importance égale, était négligée et pas explicitement définie. D’un côté, la gestion de la perspective ressource spécifiquement l’allocation des ressources Cloud est un thème d’actualité qui implique plusieurs recherches. La modélisation et la configuration des ressources sont une tâche sensible nécessitant un travail intensif. Malgré l’existence de différentes approches, elles traitent principalement les ressources humaines plutôt que des ressources Cloud. D’un autre côté, malgré le fait que le concept des modèles de processus configurables est très complémentaire au Cloud, la manière dont comment les ressources sont configurées et intégrées est à peine manipulée. Les approches proposées travaillant sur l’extension de la configuration de ressources, ne couvrent pas les propriétés Cloud notamment l’élasticité et le partage.Pour répondre à ces lacunes, nous proposons une approche pour supporter la modélisation et la configuration de l’allocation des ressources Cloud dans les modèles de processus configurables. Nous visons à (1) définir une description unifiée et formelle pour la perspective ressource, (2) assurer une allocation de ressource correcte, sans conflits et optimisée, (3) Aider les fournisseurs de processus à concevoir leur allocation de ressources configurable de manière fine afin d'éviter des résultats complexes et importants, et (4) Optimiser la sélection des ressources Cloud par rapport aux exigences liées aux propriétés Cloud (élasticité et partage) et propriétés QoS.Pour ce faire, nous proposons d'abord un cadre sémantique pour une description de ressources sémantiquement enrichies dans les processus métiers visant à formaliser les ressources Cloud consommées à l'aide d'une base de connaissances partagée. Ensuite, nous nous basons sur les processus métiers sociales pour fournir des stratégies afin d'assurer une allocation de ressources contrôlée sans conflits en termes de ressources. Par la suite, nous proposons une nouvelle approche qui étend les modèles de processus configurables pour permettre une allocation de ressources Cloud configurable. Notre objectif est de déplacer l'allocation de ressources Cloud du côté des tenants vers le côté du fournisseur de processus Cloud pour une gestion centralisée des ressources. Après, nous proposons des approches génétiques qui visent à choisir une configuration optimale des ressources d'une manière efficace sur le plan énergétique en améliorant les propriétés QoS.Afin de montrer l'efficacité de nos propositions, nous avons développé concrètement (1) une série de preuves de concepts, en tant que partie de validation, pour aider à concevoir des modèles de processus et remplir une base de connaissances de modèles de processus hétérogènes avec des ressources Cloud et (2) ont effectué des expériences sur des modèles de processus réels à partir de grands ensembles de données / Organizations are recently more and more adopting Process-Aware Information Systems (PAIS) for managing their service-based processes using process models referred to as business process models. Motivated by adapting to the rapid changing business requirements and reducing maintenance costs, organizations are outsourcing their processes in an important infrastructure which is Cloud Computing. According to the NIST Institute, Cloud Computing is a model that enables providers sharing their computing resources (e.g., networks, applications, and storage) and users accessing them in convenient and on-demand way with a minimal management effort. In such a multi-tenant environment, using configurable process models allows a Cloud process provider to deliver a customizable process that can be configured by different tenants according to their needs.A business process could be specified from various perspectives such as the control-flow perspective, the organizational perspective, the resource perspective, etc. Several approaches have been correctly proposed at the level of the first perspectives, in particular the control-flow, i.e., the temporal ordering of the process activities. Nevertheless, the resource perspective, which is of equal importance, has been neglected and poorly operated. The management of the resource perspective especially the Cloud resource allocation in business processes is a current interesting topic that increasingly involves many researches in both academics and industry. The design and configuration of resources are undoubtedly sensitive and labor-intensive task. On the one hand, the resource perspective in process models is not explicitly defined. Although many proposals exist in the literature, they all targeted human resources rather than Cloud resources. On the other hand, despite of the fact that the concept of configurable process models is highly complementary to Cloud Computing, the way in how resources can be configured and integrated is hardly handled. The few proposals, which have been suggested on extending configuration to resources, do not cover required Cloud properties such as elasticity or multi-tenancy.To address these limitations, we propose an approach for supporting the design and configuration of Cloud resource Allocation in configurable business process models. We target to (1) define a unified and formal description for the resource perspective, (2) ensure a correct, free-of-conflict and optimized use of Cloud resource consumption, (3) assist process providers to design their configurable resource allocation in a fine-grained way to avoid complex and large results, and (4) optimize the selection of Cloud resources with respect to the requirements related to Cloud properties (elasticity and shareability) and QoS properties.To do so, we first suggest a semantic framework for a semantically-enriched resource description in business processes aiming at formalizing the consumed Cloud resources using a shared knowledge base. Then, we build upon social business processes to provide strategies in order to ensure a controlled resource allocation without conflicts in terms of resources. Next, we propose a novel approach that extends configurable process models to permit a configurable Cloud resource allocation. Our purpose is to shift the Cloud resource allocation from the tenant side to the Cloud process provider side for a centralized resource management. Afterwards, we propose genetic-based approaches that aim at selecting optimal resource configuration in an energy efficient manner and to improve non-functional properties.In order to show the effectiveness of our proposals, we concretely developed (i) a set of proof of concepts, as a validation part, to assist the design of process models and populate a knowledge base of heterogeneous process models with Cloud resources, and (ii) performed experiments on real process models from large datasets

Cloud computing has a significant impact on information and communication technology (ICT) and is one of the most important technological drivers of the digitalization of enterprises. However, due to the increasing dissemination of cloud services and the growing number of cloud service providers (CSPs), the uncertainty and risks for user companies in adopting cloud services have also increased. In this paper, we address those aspects from the perspective of the CSPs. We identified relevant literature and studies and conducted interviews with business experts from 16 German CSPs. In our results, we present current customer requirements and barriers to using cloud services from a provider’s viewpoint and identify the actions of and obstacles for CSPs in meeting the needs and constraints of the customers. Finally, we identify current and future challenges for CSPs in dealing with customer requirements and barriers by addressing their root causes. One of the main challenges from the CSPs’ perspective is addressing customers appropriately and building relationships of trust. This also “forces” changes in the sales processes. In this process, the essential challenges can be identified as an increase in complexity and a simultaneous simplification of specific sales activities. Therefore, the necessity arises for the continuous support of business relationships through value-adding and additional services. However, this results in another challenge for the CSPs – Namely, to find the right balance between standardization and meeting customer-specific requirements. In our paper, we show that the perspective of the CSPs is rarely discussed in the literature. Nevertheless, understanding the perceptions of the providers and their actions and measures is essential for future research activities in the field of cloud service selection. Comparing the customers’ perspectives and viewpoints with the CSPs’ actions will enhance the development of a holistic selection approach for future cloud projects. Therefore, our paper’s contribution to research is also the identification of this missing integration.

<p>Transitioning to cloud computing is a complex and major effort for large multinational corporations (MNCs). Automated cloud migration tools (ACMTs) have been developed and are evolving to streamline this process. The potential benefits of their use are reported to be significant in terms of cost, time, and business innovation. Academic research on ACMTs and the best leadership practices for their use has been limited. </p><p> </p><p>The purpose of the research was to identify the best leadership practices of MNCs in the use of automated migration tools for the adoption of commercial cloud computing platforms. Adoption of cloud computing is a major technological shift occurring globally, and is still in early stages of growth. Major providers of commercial cloud computing platforms include technological giants such as Microsoft, Amazon Web Services, Google, Oracle and IBM.</p><p> </p><p>A meta-analysis designed research approach focusing on the triangulation of case studies, cloud computing industry data and trends from cloud service providers (CSP) revealed that best practices of leaders within MNCs fall under three main categories: awareness, impact and actions. Further, it was determined that the ACMTs with the most advanced capabilities do not necessarily equate to faster realization of cloud value for the MNC. </p><p> </p>With the continued development of ACMTs and their growing adoption, further study on the role of automation in cloud migration solution deployment will be critical, as ACMT capabilities will continue to mature. No longer the sole domain of becoming a market leader alone, organizations that utilize ACMTs are increasingly doing so just to maintain competitive parity, as the true differentiator in organizational excellence is now in cloud optimization and not simply just getting to the cloud.

MCom (Business Information Systems) / Department of Business Information Systems / Although technology is being progressively used in supporting student learning and enhancing business processes within tertiary institutions, certain aspects are hindering the decisions of cloud usage. Among many challenges of utilizing cloud computing, cybersecurity has become a primary concern for the adoption. The main aim of the study was to investigate the effect of cloud cyber-security usage at rural based tertiary institutions in order to compare the usage with an urban-based institution and propose a cybersecurity framework for adoption of cloud computing cybersecurity. The research questions focused on determining the drivers for cloud cybersecurity usage; the current adoption issues; how cybersecurity challenges, benefits, and quality affects cloud usage; the adoption perceptions and awareness of key stakeholders and identifying a cloud cybersecurity adoption framework. A quantitative approach was applied with data collected from a simple random sample of students, lecturers, admin and IT staff within the tertiary institutions through structured questionnaires. The results suggested compliance with legal law as a critical driver for cloud cybersecurity adoption. The study also found a lack of physical control of data and harmful activities executed on the internet as challenges hampering the adoption. Prevention of identity fraud and cheaper security costs were identified as benefits of adoption. Respondents found cloud cybersecurity to be accurate and effective, although most of the students and employees have not used it. However, respondents were aware of the value of cybersecurity adoption and perceive for it to be useful and convenient, hence have shown the intention of adopting it. There were no significant elements identified to differentiate the perceptions of usage at rural and urban-based tertiary institutions. The results of the study are to be used for clarifying the cybersecurity aspects of cloud computing and forecasting the suitability cloud cybersecurity within the tertiary institutions. Recommendations were made on how tertiary institutions and management can promote cloud cybersecurity adoption and how students, lecturers, and staff can effectively use cloud cybersecurity. / NRF

Cloud datacenters comprise hundreds or thousands of disparate application services, each having stringent performance and availability requirements, sharing a finite set of heterogeneous hardware and software resources. The implication of such complex environment is that the occurrence of performance problems, such as slow application response and unplanned downtimes, has become a norm rather than exception resulting in decreased revenue, damaged reputation, and huge human-effort in diagnosis. Though causes can be as varied as application issues (e.g. bugs), machine-level failures (e.g. faulty server), and operator errors (e.g. mis-configurations), recent studies have attributed capacity-related issues, such as resource shortage and contention, as the cause of most performance problems on the Internet today. As cloud datacenters become increasingly autonomous there is need for automated performance diagnosis systems that can adapt their operation to reflect the changing workload and topology in the infrastructure. In particular, such systems should be able to detect anomalous performance events, uncover manifestations of capacity bottlenecks, localize actual root-cause(s), and possibly suggest or actuate corrections. This thesis investigates approaches for diagnosing performance problems in cloud infrastructures. We present the outcome of an extensive survey of existing research contributions addressing performance diagnosis in diverse systems domains. We also present models and algorithms for detecting anomalies in real-time application performance and identification of anomalous datacenter resources based on operational metrics and spatial dependency across datacenter components. Empirical evaluations of our approaches shows how they can be used to improve end-user experience, service assurance and support root-cause analysis. / Cloud Control (C0590801)

Cloud computing is an exciting concept that propels the development of technologies, the creation and expansion of businesses and the rapid prototyping of new ideas. Utilizing the advantages the cloud offers to their fullest potential is not a simple task and thus often users struggle with the technological aspects, lose revenue or do not attempt to benefit from this idea at all. In this dissertation, we identify the lack of standards for performance descriptions as well as the steep learning curve to get familiar with the cloud, which is further amplified by the abundance of available services, as the most prevalent issues that individuals and companies encounter. We further show the relevance of solving these issues by outlining the expected impact, which includes decreased time and financial detriments for individuals and companies as well as a negative effect on the environment. To solve the identified problems we propose the development of a cloud broker with three key components that utilize a performance oriented resource and application model to 1) compare arbitrary resources and applications in a fair manner based on general information, collected with standard benchmark tools 2) select the optimal infrastructure for any application by estimating its resource consumption and execution time and 3) automatically create and manage the selected infrastructure as well as the application deployment. Our contributions to this proposal include the development and test of prototypical proof-of-concept implementations for the three components, the design of the underlying resource and application performance model as well as the selection of appropriate, generic benchmark solutions, which we deployed on two major public clouds using our prototypes. In an extensive objective-based evaluation we assess that we contributed towards solving all the major issues that we identified to increase the usability and efficiency of cloud computing by enabling a better comprehension of resource and application performance in cloud environments and by reducing the necessary time and effort to deploy arbitrary applications in the cloud. We conclude by interpreting the evaluation results and providing an outlook towards future work.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform / Die Dissertation beschäftigt sich mit der effizienten Nutzung von Cloud Ressourcen zur Beschleunigung der Entwicklung neuer Technologien und Geschäftsmodellen sowie des Rapid Prototypings neuer Ideen. Auf Grund der Komplexität von Cloud Plattformen, stellt die Nutzung derer oft eine große Hürde, speziell für kleine und mittlere Unternehmen dar, weshalb oft Ressourcen verschwendet werden, Prozesse mehr Zeit in Anspruch nehmen als nötig oder erst gar kein Versuch unternommen wird, diese Technologie zu nutzen. In der Arbeit werden dazu drei Kernprobleme identifiziert und thematisiert. Dies sind Lücken in Bezug auf Standards zur Beschreibung der Performance von Cloud Ressourcen, die Fülle an existierenden Cloud Diensten, sowie die steile Lernkurze bei der Nutzung dieser Dienste. Zur Lösung der identifizierten Probleme, wird in der Arbeit die Entwicklung einer Cloud Broker Anwendung mit drei Kernkomponenten vorgeschlagen, die ein Performanz-orientiertes Ressourcen- und Anwendungsmodell verwenden, welches es ermöglicht: 1) beliebige Ressourcen und Anwendungen unterschiedlichster Anbieter mit der Hilfe von frei verfügbaren und standardisierten Benchmark Tools zu vergleichen, 2) die passende Infrastruktur für jede auszuführende Anwendung durch Schätzung des Ressourcenbedarfs und der Dauer der Ausführung auszuwählen und 3) die gewählte Infrastruktur automatisch in der Cloud erzeugt und die Anwendung selbstständig ausführt. Im Rahmen der Dissertation wurden dazu alle drei Kernkomponenten prototypisch implementiert, das zugrundeliegende Ressourcen und Anwendungsmodell designt, sowie geeignete Benchmark Lösungen ausgewählt und umfangreiche Benchmarks auf zwei großen, öffentlichen Cloud Plattformen mit Hilfe der entwickelten Prototypen durchgeführt. In einer umfassenden zielorientierten Evaluation, wird der Beitrag zur Lösung der im Vorfeld identifizierten Probleme bewertet und festgestellt, dass mit den entwickelten Komponenten sowohl die Nutzbarkeit als auch Effizienz von Cloud-Computing insgesamt erhöht werden kann. Dies wird ermöglicht durch ein besseres Verständnis der Ressourcen und Anwendungsperformanz, sowie durch Reduzierung der notwendigen Zeit und des Aufwands für eine Anwendungsausführung in der Cloud. Im Vortrag wird abschließend noch ein Ausblick auf weiterführende Arbeiten gegeben.:1 Introduction 2 Challenges 3 Improve Resource Selection and Management in Cloud Environments 4 Cloud Resource Comparison 5 Resource Estimation 6 Cloud Application Execution 7 Overall Evaluation 8 Conclusion A LFA Artifacts B Analysis and Results C PoC Platform

The complex business applications are increasingly offered as services over the Internet, so-called software-as-a-Service (SaaS) applications. The SAP Netweaver Cloud offers an OSGI-based open platform, which enables multi-tenant SaaS applications to run in the cloud. A multi-tenant SaaS application is designed so that an application instance is used by several customers and their users. As different customers have different requirements for functionality and quality of the application, the application instance must be configurable. Therefore, it must be able to add new configurations into a multi-tenant SaaS application at run-time. In this thesis, we proposed concepts of a configuration management, which are used for managing and creating client configurations of cloud applications. The concepts are implemented in a tool that is based on Eclipse and extended feature models. In addition, we evaluate our concepts and the applicability of the developed solution in the SAP Netwaver Cloud by using a cloud application as a concrete case example.:List of Figures i List of Tables iii 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 The Structure of This Document . . . . . . . . . . . . . . . . . 2 2 Background 5 2.1 Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Software Product Line Engineering . . . . . . . . . . . . . . . . 7 2.3 Role Based Access Control . . . . . . . . . . . . . . . . . . . . . 10 2.4 Staged Con guration . . . . . . . . . . . . . . . . . . . . . . . . 12 2.5 Work ow Modeling . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.5.1 Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.5.2 Work ow Modeling Languages . . . . . . . . . . . . . . . 16 2.5.3 Adaptive Work ow . . . . . . . . . . . . . . . . . . . . . 17 2.5.4 Adaptation Patterns . . . . . . . . . . . . . . . . . . . . 17 2.6 Graph Transformation . . . . . . . . . . . . . . . . . . . . . . . 18 2.7 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3 Analysis 23 3.1 Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . 23 3.1.1 Domain and Exiting Platform . . . . . . . . . . . . . . . 24 3.1.2 Yard Management System as a SaaS Application . . . . 28 3.2 Requirements Identi cation . . . . . . . . . . . . . . . . . . . . 28 4 Concept 31 4.1 Con guration Management Speci cation . . . . . . . . . . . . . 31 4.1.1 Variability Modeling . . . . . . . . . . . . . . . . . . . . 32 4.1.2 Stakeholder Views Modeling . . . . . . . . . . . . . . . . 34 4.1.3 Con guration Work ow Modeling . . . . . . . . . . . . . 36 4.2 Con guration Work ow Adaptations . . . . . . . . . . . . . . . 41 4.3 Mapping between Problem Space and Solution Space . . . . . . 47 4.4 Con guration Process Simulation . . . . . . . . . . . . . . . . . 50 5 Implementation 53 5.1 Con guration Speci cation . . . . . . . . . . . . . . . . . . . . . 54 5.1.1 Extended Feature Model Speci cation . . . . . . . . . . 55 5.1.2 View Model Speci cation . . . . . . . . . . . . . . . . . . 56 5.1.3 Con guration Work ow Model Speci cation . . . . . . . 57 5.2 Graph Transformation Rules . . . . . . . . . . . . . . . . . . . . 62 5.3 Mapping Realization . . . . . . . . . . . . . . . . . . . . . . . . 65 5.4 Con guration Management Tooling . . . . . . . . . . . . . . . . 67 5.5 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 6 Conclusions and Future Work 77 6.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Bibliography i

Nowadays, prolonged sitting among office workers is a widespread problem, which is highly related to several health problems. Many proposals have been reported and evaluated to address this issue. However, motivating and engaging workers to change health behavior to a healthier working life is still a challenge. In this project, a specific application has been deployed for real-time monitoring and alerting office workers for prolonged sitting. The proposed system consists of three distinct parts: The first one is an android smartwatch, which was used to collect sensor data e.g., accelerometer and gyro data, with a custom android wear app. The second one is an android application, which was developed to act as a gateway for receiving the smartwatch’s data and sending them to IBM Bluemix cloud with MQTT protocol. The final part is a Node-Red cloud application, which was deployed for storing, analyzing and processing of the sensor data for activity detection i.e., sitting or walking/standing. The main purpose of the last one was to return relevant feedback to the user, while combining elements from gaming contexts (gamification methods), for motivating and engaging office workers to a healthier behavior. The system was firstly tested for defining appropriate accelerometer thresholds to five participants (control group), and then evaluated with five different participants (treatment group), in order to analyze its reliability for prolonged sitting detection. The results showed a good precession for the detection. No confusing between sitting and walking/standing was noticed. Communication, storage and analysis of the data was successfully done, while the push notifications to the participants, for alerting or rewarding them, were always accurate and delivered on time. Every useful information was presented to the user to a web-based dashboard accessed through a smartphone, tablet or a PC.     The proposed system can easily be implemented at a real-life scenario with office workers. Certainly, there is a lot space for improvement, considering mostly the type of data registered at the system, the method for sitting detection, and the user interface for presenting relevant information. / Numera är förlängt sittande bland kontorsarbetare ett utbrett problem som är väldigt relaterat till flera hälsoproblem. Många förslag har rapporterats och utvärderas för att ta itu med denna fråga. Tydligen är det fortfarande en utmaning att motivera och engagera arbetstagare för att förändra deras hälsobeteende till hälsosammare arbetsliv. I detta projekt har en särskild applikation använts för realtidsövervakning och varnar kontorsarbetare för förlängt sittande. Det föreslagna systemet består av tre olika delar: Den första är en android smartwatch, som användes för att samla sensordata t.ex. accelerometer och gyrodata, med en anpassad android wear app. Den andra är en en androidapplikation som fungerade som en gateway för att ta emot smartwatchens data och skickar datan till IBM Bluemix-Cloud med MQTT-protokollet. Den sista delen är en Node-RED Cloud-Applikation som användes för lagring, analysering och behandling av sensordata för aktivitetsdetektering. Detta innebär sittande eller gå/stående med det huvudsakliga ändamålet att returnera relevant återkoppling till användaren, samtidigt som man kombinerar element från spelkontekster (gamification metoder), för att motivera och engagera arbetarna till ett hälsosammare beteende. Systemet testades först för att definiera lämpliga accelerometertrösklar till fem deltagare (kontroll grupp) och utvärderades sedan med fem olika deltagare (behandingsgrupp) för att analysera dess tillförlitlighet för långvarig sittdetektering. Resultaten visade en bra precession för detektionen. Ingen förvirring mellan att sitta och gå / stående märktes. Kommunikation, lagring och analys av data gjordes framgångsrikt, medan push-meddelandena till deltagarna, för att varna eller belöna dem, var alltid korrekta och levererade i tid. All användbar information presenterades för användaren på en webbaserad dashboard som nås via en smartphone surfplatta eller en dator. Det föreslagna systemet kan enkelt implementeras i ett verkligt scenario med kontorsarbetare. Visst finns det mycket utrymme för förbättring om man tänker på majoriteten av data som registrerats i systemet, metoden för sittande detektion och användargränssnittet för presentering av relevant information.

Cyber-attack simulation is a suitable method used for assessing the security ofnetwork systems. An attack simulation advances step-wise from a certain systementry-point to explore the attack paths that lead to dierent weaknesses inthe model. Each step is analyzed, and the time to compromise is calculated.Attack simulations are primarily based on attack graphs. The graphs areemployed to model attack steps where nodes can represent assets in the system,and edges can represent the attack steps. To reduce the computational cost associatedwith building an attack graph for each specic system, domain-specicattack languages, or DSL for short, are used.The nal product of this thesis work is azureLang, a probabilistic modelingand simulation language for modeling Microsoft Azure cloud infrastructure.AzureLang is a DSL which denes a generic attack logic for MicrosoftAzure systems. Using azureLang, system administrators can easily instantiatespecic-system scenarios which emulate their Microsoft Azure cloud system infrastructure.After creating the model, attack simulation can be run to assessthe security of the model. / Cyberattacksimulering är en lämplig metod som används för att bedöma säkerhetenhos nätverkssystem. En angrepsimulering går stegvis från ett visst systeminmatningspunkt för att utforska angreppsbanorna som leder till olika svagheter i modellen. Varje steg analyseras och tiden för kompromettera beräknas.Attack-simuleringar baseras huvudsakligen på attackgrafer. Graferna används för att modellera angreppssteg där noder kan representera tillgångar i systemet, och kanterna kan representera attackenstegen. För att minska kostnaden för att skapa attackgrafer för varje specifikt system används domänspecifika språk eller DSL förkortat.Den slutliga produkten av detta examensarbete är azureLang, ett probabilistisk hotmodelleringsoch attacksimuleringsspråk för analys av Microsoft Azure Cloud Infrastructure. AzureLang är en DSL som definierar en generisk attacklogik för Microsoft Azure-system. Med hjälp av azureLang kan systemadministratörer enkelt ordna specifika systemscenarier som efterliknar deras Microsoft Azure cloudsystem infrastruktur. Efter att ha skapat modellen kan attack simu-lering köras för att bedöma modellens säkerhet.