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Scalability and Economy of Amazon Lambda, EKS, and ECS

Cloud computing is the current need and the futuristic strategy of many businesses. Economy and scalability are inevitable because they impact the flourishing of all online businesses. The objective of this study is to distinguish the differences between Amazon Lambda versus EKS and ECS using EC2 instances from the Economy and scalability perspectives. The study aims to give programmers without prior knowledge about the services an overall picture of their billing models, scalability,  and the goal each service is meant to deliver. A literature review was used to identify the related studies done earlier in this area of research. The data captured from the literature studies were enriched with an empirical study, namely, survey research  with semi-structured interviews. Snowballing was used to identify more interviewees with the help of the earlier selected respondents. After conducting the semi-structured online interviews with five participants, the recordings were transcribed. Finally, the Thematic Analysis approach was used to analyze the collected qualitative data from the transcripts. It was concluded that Lambda was useful for infrequent and minor workloads without long processing tasks, with a  free automatic and managed scalability. For websites doing massive processing or getting large requests constantly, EKS or ECS would be a better choice. However, ECS and EKS cost more than Lambda when working with smaller workloads. EKS has multi-direction scalability, making it more flexible than Lambda and ECS. However, this comes with additional costs and complexity, but it is cost-effective for bigger businesses. Ultimately, in real-world cloud architecture, it is relatively common to rely on a combination of cloud services to fulfill the economic or auto scalability objectives of a business instead of a single one.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-23197
Date January 2022
CreatorsAltaleb, Bashar, Abo Khalaf, Muhamed kheer
PublisherBlekinge Tekniska Högskola, Fakulteten för datavetenskaper
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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