The Internet of Things (IoT) is rapidly gaining ground in our daily life. There is a trend that the number of devices and data increases rapidly in the future. Meanwhile, IoT platforms are emerging to enable people conveniently deal with the IoT and these huge amount of data and devices. Therefore, the goal in this paper is to perform a quantitative evaluation on Microsoft Azure, one of the IoT platform, about its advantages and disadvantages under press to determine if Azure IoT is fit for future IoT. In order to reach this goal, Azure IoT Hub is used as a bridge to connect and manage lots of IoT devices which send and receive huge amount of data. .NET is used to simulate devices and connect them to the IoT Hub. The two-way communication from sensor to cloud and from cloud to actuator is implemented through MQTT protocol. This paper makes measurements on three metrics including response time from sensor sending messages to actuator receiving messages, scalability and cost and analyzes them in detail. Besides, the analysis is also made in a specific scenario which has high demand on sensor update to see how Azure IoT performs. Finally, conclusion is made on Microsoft Azure IoT's advantages and disadvantages under stress.

This thesis deals with the design of the corporate network infrastructure to improve its security against potential threats and attacks from both internal and external part of the network and to prevent leak of the sensitive information, so that, to accomplished the requirements of the current GDPR legislation. The proposal includes simplifying identity and access management of the users to the corporate resources and unified, well-arranged management from the side of the network administrators using modern and advanced tools to alert in the real time on unexpected events and anomalies on the network. Solution is implemented in the Microsoft Azure service environment and its funcionality has been verified based on the relevant penetration tests.

In dieser Thesis werden unterschiedliche Wege erläutert, Webanwendungen mit einem Cloud‐agnostischen Ansatz bereitzustellen. Ein Cloud‐agnostischer Ansatz zielt auf die Unabhängigkeit von einem bestimmten Cloud Service Provider (CSP) und dessen Technologien ab. Um dies zu ermöglichen, werden verschiedene Tools unter anderem hinsichtlich ihrer unterstützten Sprachen und Technologien, ihrer Modularität, ihres State und Secret Managements, ihres Bekanntheitsgrades und des Community Supports verglichen. Die Einführung erfolgt entlang der theoretischen Grundlagen, der Erläuterungen und Vorteile des Konzepts der Infrastructure‐as‐Code (IaC), anhand der Grundlagen zur imperativen und deklarativen Programmierung und mittels der Unterscheidung zwischen Domain‐Specific Languages und General‐Purpose Languages. In den folgenden Kapiteln folgt, bezogen auf die in dieser Thesis behandelten Beispiele Microsoft Azure (Azure) und Open Telekom Cloud (OTC), ein Vergleich der unterschiedlichen Möglichkeiten, Webanwendungen auf diesen Plattformen bereitzustellen. Dieser Ansatz soll anschließend durch eine Automatisierung mittels eines ausgewählten Frameworks als Prototyp anhand einer bestehenden Webanwendung implementiert werden. Zur Implementierung werden vorher die bekanntesten Frameworks auf Grundlage dieser Problemstellung verglichen und das passendste ausgewählt. Als Abschluss der Thesis folgt eine Zusammenfassung, in welcher die gelernten Kenntnisse und Erfahrungen im Umgang mit der Bereitstellung von Infrastruktur für Webanwendungen mittels IaC in einem Cloud‐agnostischen Einsatz dargelegt werden.:Abkürzungsverzeichnis Abbildungsverzeichnis Tabellenverzeichnis Quellcodeverzeichnis 1 Einleitung 1.1 Problemstellung 1.2 Zielstellung 1.3 Aufbau der Arbeit 2 Theoretische Grundlagen 2.1 Prozess der Infrastrukturbereitstellung 2.2 Einführung Infrastructure‐as‐Code 2.3 Deklarativer und imperativer Ansatz 2.4 Domain‐Specific Languages 2.5 Abstraktionsebene 2.6 Stand der Technik 3 Analyse 3.1 Methodik und Umsetzung 3.2 Kriterien für einen Vergleich verschiedener IaC‐Werkzeuge 3.3 Kriterien für einen funktionalen Vergleich von Tools zur Orchestrierung 3.4 Detaillierterer Vergleich von Terraform und Pulumi 3.5 Docker zur Bereitstellung von Webanwendungen 4 Konzeption 4.1 Modellierung der Abstraktion 4.2 Betrachtung der Konzepte 4.3 Bewertung der Konzepte 5 Prototyp 5.1 Vorstellung der Voraussetzungen 5.2 Implementierung des Prototyps 5.3 Analyse des Prototyps 6 Fazit 6.1 Ausblick 6.2 Zusammenfassung Literaturverzeichnis Glossar

In recent years, the interest and utilization of VPNs and cloud computing have surged, which has led to the development of Cloud VPNs. Cloud VPNs are often used to give employers access to company resources over a secured and trusted network, but individuals can also use them. Cloud computing offers numerous advantages, including cost efficiency, scalability, security, and reliability. Companies and individuals widely use it to streamline operations, reduce expenditures, and leverage technologies without the need to maintain on-premise infrastructure. Cloud-based solutions impose specific requirements on technologies designed to operate in the cloud, which include security, efficient resource management, and high network availability and performance. In this thesis, we will analyze and evaluate the network performance impact that Amazon Web Services (AWS) and Microsoft Azure, two of the market-leading cloud platforms, have on the VPN services OpenVPN and WireGuard while considering associated operational costs and user complexity. The network performance impact is evaluated through measuring the throughput, latency, jitter, and packet loss. We have performed experiments divided into three setups, each simulating different traffic patterns, and VPN usage scenarios. Throughout these experiments, we observed and documented the user complexity related to setup, installation, and configuration processes. Our findings indicate that Azure has the best overall network throughput across all setups, fewer retransmissions, and fewer packet losses. Conversely, AWS exhibits lower latency and jitter. Additionally, our assessment of operational costs and user complexity reveals that Azure offers lower associated costs but a higher user complexity. Furthermore, our experiments identified that WireGuard, when paired with Azure, offers the best VPN solution.

[pt] A computação em nuvem, com sua promessa de redução de custos de manutenção e facilidades de configuração, está despertando cada vez mais o interesse da comunidade científica que depende de muitas máquinas para executar seus programas. Neste trabalho implementamos uma nova integração para o sistema CSGrid, do Tecgraf/PUC-Rio, que o torna apto a submeter programas para execução no ambiente de nuvem pública Microsoft Azure, usufruindo assim dos benefícios da elasticidade de recursos computacionais. Para tal, apresentamos algumas medidas de desempenho para o caso de uso da nuvem pública Microsoft Azure pelo sistema CSGrid, no que se refere a custos de transferência de dados e provisionamento de máquinas virtuais. O objetivo com essa integração é avaliar os benefícios e as dificuldades que envolvem o uso de um modelo de execução em nuvem por um sistema tipicamente voltado a execução de aplicações de alto desempenho em clusters. / [en] Cloud computing appeals to those who need many machines to run their programs, attracted by low maintenance costs and easy configuration. In this work we implemented a new integration for the CSGrid system, from Tecgraf/PUC-Rio, enabling it to submit workloads to Microsoft Azure public cloud, thus enjoying the benefits of elastic computing resources. For this purpose, we present related works and some performance measures in the case of CSGrid s use of Microsoft Azure public cloud, with regard to costs on data transfers and provisioning of virtual machines. With this integration, we could evaluate the benefits and difficulties involved in using cloud resources in a system designed for the submission of HPC applications to clusters.

Cloud computing is still in an early stage of development and Microsoft is now investing considerable amount of resources in the cloud. Microsoft Azure is a cloud platform developed by Microsoft and it is continuously evolving, new features are constantly being added and old features are being updated. Integration Software, which is a company that focuses on products for system integration strongly believes that cloud­-based solutions will have a significant impact on their future. This is why selling and developing solutions and services for the cloud are strategically important for them. The objective of this dissertation is to investigate Microsoft Azure in general and Azure Marketplace in particular. This investigation consisted of an implementation of a Microsoft Azure application and integrating this application with Azure Marketplace and evaluating the expenses for running the application. The purpose for this project is to gain practical experience and to work with new techniques and help Integration Software better understand Azure Marketplace. The application is a Log Agent which fetches data from an external source and resends the data to an external party (Integration Manager). Our first intention was to package and deploy the application to a newly updated Azure Marketplace. The new Azure Marketplace was never released during this dissertation so we decided to deploy the application to the existing version of Azure Marketplace. This was however not fully successful. We encountered some problems in successfully deploying the application to Azure Marketplace. The evaluations for the cost of running an Azure application were not carried out due to lack of time.

Cloud Computing is becoming increasingly popular, with large amounts of corporations revenue coming in from various cloud solutions offered to customers. When it comes to choosing a solution, multiple options exist for the same problem from many competitors. This report focuses on the ones offered by Microsoft in their Azure platform, and compares the architectures in terms of performance and scalability.In order to determine the most suitable architecture, three offered by Azure are considered: Cloud Services (CS), Service Fabric Mesh (SFM) and Virtual Machines (VM). By developing and deploying a REST Web API to each service and performing a load test, average response times in milliseconds are measured and compared. To determine scalability, the point at which each service starts timing out requests is identified. The services are tested both by scaling up, by increasing the power of a single instance of a machine, and by scaling out, if possible, by duplicating instances of machines running in parallel.The results show that VMs fall considerably behind both CS and SFM in both performance and scalability, for a regular use case. For low amounts of requests, all services perform about the same, but as soon as the requests increase, it is clear that both SFM and CS outperform VMs. In the end, CS comes ahead both in terms of scalability and performance.Further research may be done into other platforms which offer the same service solutions, such as Amazon Web Services (AWS) and Google Cloud, or other architectures within Azure. / Molntjänster blir alltmer populära i dagens industri, där stora mängder av företagens omsättning består av tjänster erbjudna i form av molnlösningar. När det kommer till att välja en lösning finns många för samma problem, där det är upp till kunden att välja vilken som passar bäst. Denna rapport fokuserar på tjänster erbjudna av Microsofts Azure plattform, i en jämförelse av arkitekturer som belastningstestas för att mäta prestanda och skalbarhet.För att avgöra vilken arkitektur som är optimalast mäts tre olika tjänster erbjudna i Azure: Cloud Services (CS), Service Fabric Mesh (SFM) och Virtual Machines (VM). Detta görs genom att utveckla och deploya ett REST Web API som är simulerat med användare, där prestanda mäts genom att ta medelresponstiden i millisekunder per anrop. För att avgöra skalbarhet identifieras en punkt där tjänsten inte längre klarar av antalet inkommande anrop och börjar returnera felkoder. Maskinerna för varje tjänst testas både genom att skala upp, genom att förstärka en maskin, men även genom att skala ut, där det skapas flera instanser av samma maskin.Resultatet visar att Virtual Machines hamnar betydligt efter både CS och SFM i både prestanda och skalbarhet för ett vanligt användarfall. För låga mängder anrop ligger samtliga tjänster väldigt lika, men så fort anropen börjar öka så märks det tydligt att SFM och CS presterar bättre än Virtual Machines. I slutändan ligger CS i framkant, både i form av prestanda och skalbarhet.Vidare undersökning kan göras för de olika plattformarna erbjudna av konkurrenter, så som Amazon Web Services (AWS) och Google Cloud, samt andra arkitekturer från Azure.

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.

At Halmstad University a project was developed to provide recommendations forupgrading and downgrading the cloud resource app service plan based on the customersusage over the last 30 days. In today’s day and age, cloud resources and services are oftenquite expensive and offers a variety of different plans which can make it overwhelmingfor the customer to easily choose which tier they need for their plan. The result of thisscript indicate that the cloud users should consider changing subscription tier based onhow the historical data of their usage of the plan has looked like during the last 30 days.The proposed algorithm suggests an upgrade of a tier if the plan is overutilized andsuggest a downgrade of a tier if the plan is underutilized. The developed PowerShell codeuses the First-Fit and the Rule-based algorithmic approach from the related workresearched in the paper. The result found was that the code was able to give suitablerecommendations to scale up and down tiers for plans which were under and overutilizedbased on the percentual utilization rules set up and Legacy/DEV SKU mapping. Theresults obtained showed that the suggested plan can reduce costs by up to 30% and giveroughly 438.2% more performance per $USD spent. / Vid Högskolan i Halmstad utvecklades ett projekt för att ge förslag på uppgraderingaroch nedgraderingar av molnresursern app service plan baserat på användarens senaste 30dagars användning. Då dagens molnresurser och tjänster ofta är dyra och erbjuder ettöverflöd av planer, kan det vara förvirrande för användare att välja rätt nivå för sinabehov. Projektet föreslår att användarna ska överväga att byta plan beroende på hur denhistoriska datan har sett ut för planens användning, där en uppgradering rekommenderasom tjänsten är överanvänd och en nedgradering om planen är underanvänd. Denutvecklade PowerShell koden använder sig av First-fit och det regelbaserade algoritmtypen som utvecklades med inspiration från litteraturstudien. Resultatet av projektetindikerar att koden kunde ge optimala upp och ned skalnings rekommendationer beroendepå de olika procentuella trösklarna satta samt mappningen av Legacy och utvecklingstiers. Analyseringen av resultatet pekar på att det går att spara runt 30% på app serviceplan kostnaderna samt att app service planerna får 438,2% mer prestanda per spenderad$USD i jämförelse med nuvarande planen.

The field of Artificial Intelligence (AI) has seen much development in recent years. This is mostly because of new technologies and computers becoming faster. With actors like Microsoft releasing software to reduce the complexity of the development of AI, the barrier to entry is now lower than ever. Due to this lower barrier, one area that has gained much traction is chat bots, being able to act as first line support for companies. While the technology is evolving fast and updates to Microsoft’s tools are released at an impressive rate, it appears to be difficult for other areas like documentation and ease of use to keep up with this pace. This thesis will explore some tools from Microsoft used in AI development. Areas covered are the Cognitive Services with a focus on speech, the Microsoft Azure Bot Service, the QnA Maker and the bot framework’s web-based client. These tools will be evaluated in the context of a chat bot, taking into account their functionality and development. The result is a chat bot that uses a knowledge base for data storage & answer logic, and a web interface for chat functionalities using the bot framework web-client.