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Dimensioning, Performance and Optimization of Cloud-native Applications

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Appuswamy, Raja
dc.contributor.author Henschel, Jack
dc.date.accessioned 2021-08-29T17:09:19Z
dc.date.available 2021-08-29T17:09:19Z
dc.date.issued 2021-08-23
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/109318
dc.description.abstract Cloud computing and software containers have seen major adoption over the last decade. Due to this, several container orchestration platforms were developed, with Kubernetes gaining a majority of the market share. Applications running on Kubernetes are often developed according to the microservice architecture. This means that applications are split into loosely coupled services that are distributed across many servers. The distributed nature of this architecture poses significant challenges for the observability of application performance. We investigate how such a cloud-native application can be monitored and dimensioned to ensure smooth operation. Specifically, we demonstrate this work based on the concrete example of an enterprise-grade application in the telecommunications context. Finally, we explore autoscaling for performance and cost optimization in Kubernetes i.e., automatically adjusting the amount of allocated resources based on the application load. Our results show that the elasticity obtained through autoscaling improves performance and reduces costs compared to static dimensioning. Moreover, we perform a survey of research proposals for novel Kubernetes autoscalers. The evaluation of these autoscalers shows that there is a significant gap between the available research and usage in the industry. We propose a modular autoscaling component for Kubernetes to bridge this gap. en
dc.format.extent 67+7
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Dimensioning, Performance and Optimization of Cloud-native Applications en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Perustieteiden korkeakoulu fi
dc.subject.keyword kubernetes en
dc.subject.keyword autoscaling en
dc.subject.keyword cloud-native en
dc.subject.keyword monitoring en
dc.subject.keyword performance en
dc.identifier.urn URN:NBN:fi:aalto-202108298554
dc.programme.major Security and Cloud Computing fi
dc.programme.mcode SCI3113 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Di Francesco, Mario
dc.programme Master’s Progamme in Security and Cloud Computing (SECCLO) fi
local.aalto.electroniconly yes
local.aalto.openaccess yes

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