Cloud computing is a constantly developing topic that reaches most of the people in the world on a daily basis. Almost every website and mobile application is hosted through a cloud provider. Two of the most important metrics for customers is performance and availability. Current tools that mea- sure availability are using the Internet Control Message Protocol (ICMP) to monitor availability, which has shown to be unreliable. This thesis suggests a new way of monitoring both availability and response time by using Hypertext Transfer Protocol (HTTP). Through HTTP, we are able to reach both the front-end of the cloud service (just as ICMP), but also deeper, to find failures in the back-end, that ICMP would miss. With our monitoring tool, we have monitored five different cloud data centers during one week. We found that cloud providers are not always keeping their promised SLA and it might be up to the cloud customers to reach a higher availability. We also perform load tests to analyze how vertical and horizontal scaling performs with regards to response time. Our analysis concludes that, at this time, vertical scaling outperforms horizontal scaling when it comes to response time. Even when this is the case, we suggest that developers should build applications that are horizontally scalable. With a horizontally scalable application and our monitoring tool combined, we can reach higher availability than is currently possible.

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Cloud computing’s growing popularity is based on the cloud’s flexibility and the availability of a huge amount of resources. Today, cloud providers offer a wide range of predefined solutions, VM (virtual machine) sizes and customization differing in performance, support and price. In this thesis it is investigated how to achieve cost minimization within specified performance goals for a commercial service with computation occurring in a repetitive pattern. A promising multilevel queue scheduling and a set of auto-scaling rules to fulfil computation deadlines and job prioritization and lower server cost is presented. In addition, an investigation to find an optimal VM size in the sense of cost and performance points out further areas of cloud service optimization.

Smartphones and other Internet of Things devices have become a rapidly growing topic. Along with the growth comes new technologies, likeWeb Real- Time Communication (WebRTC), that enables richer services to be built for the devices. These kind of services are typically consumed on-demand, in shorter periods at a time. Likewise have cloud computing exploded in popularity during the last years. Cloud computing offers compelling advantages, such as rapid elasticity and on-demand usage, that allow servers' resource utilization to be more effcient. The flexibility of allocating and releasing resources swiftly as they are required, enables services that run in the cloud to adopt to ephemeral workloads. The research in this thesis targets a real-time video streaming service that is based on WebRTC. Incoming streams are handled by Multipoint Control Units (MCUs) that have the responsibility to redistribute the incoming streams to the consumers. Scaling horizontally aligns well with the idea of cloud computing. The work in this thesis is based on the extreme case where each of the incoming streams are handled by a separate MCU. The thesis presents the process of finding a exible Cloud Execution Environment (CEE) for the streaming service. The process includes an analysis of the streaming service's requirements, an evaluation of existing solutions, and an implementation. Moreover, the thesis includes a discussion about the capabilities of the implemented system. The result of the thesis is a CEE upon which the streaming service can be deployed and managed. The developed CEE allows any workload that is encapsulated within a Docker container to be orchestrated, not exclusively the streaming service, which makes the implementation viable to other cloud computing projects. / Användandet av smartphones och andra "Internet of Things"-enheter ökar snabbt. I takt med ökningen, så släpps nya tekniker som möjliggör utveckling av mer avancerade tjänster. Ett exampel är Web Real-Time Communication (WebRTC). Den här typen av tjänster konsumeras oftast sporadiskt under kortare tidsintervall. även cloud computing har drastiskt ökat i popularitet under de senaste åren. Hög elasticitet samt möjligheten att allokera datorresurser på begäran har medfört att utnyttjandegraden av datorers kapacitet kan höjas. Flexibiliteten att snabbt kunna allokera och frigöra resurser möjliggör att tjänster kan utvecklas för att utnyttja upp- och nerskalningsm öjligheterna bättre, även för kortvariga lastökningar. Forskningen i rapporten riktar in sig på ett system för videoströmning mellan användare i realtid baserat påa WebRTC. Inkommande strömmar hanteras av Multipoint Control Units (MCUs), som har som uppgift att vidaredistribuera strömmarna till andra användare som vill spela upp strömmen. Horisontell skalning och cloud computing har mycket gemensamt. Det underliggande arbetet till den här rapporten fokuserar på ett extremfall, där varje inkommande videoström hanteras av en enskild MCU. Den här uppsatsen presenterar den process som användes för att ta fram en lämplig molnlösning för strömningssystemet. Processen beståar av en kravanalys av strömningssystemet, en jämförelse av befintliga lösningar samt en implementation av en molnlösning. Slutligen så innehåller uppsatsen en utvärdering av implementationen. Resultatet av uppsatsen är en molnlösning som videoströmningssystemet kan driftsättas och köras på. Molnlösningen är inte begränsad till videoströmningssystemet utan klarar av att hantera alla applikationer som paketerats inuti Docker-kapslar. Molnlösningen är så pass generell att den kan användas till andra projekt inom cloud computing.