A scalable back-end system for web games using a RESTful architecture
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
The objective of this thesis was to design and implement a scalable and load efficient back-end system for web game services. This is of interest since web applications may overnight gain a significant increase in user base, because of viral sharing. Therefore designing the web application to service an increasing amount of users can make or break the application, in regard to keep the user base. Because of this, testing how well the system performs during heavy load can be used as a foundation when making a decision of when and where to scale up the application. The system was to be generically accessible through an Application Programming Interface (API) by the different game services. This was done using a RESTful architecture where emphasise was put on building the system scalable and load efficient. This thesis focuses on designing and implementing such a system, and how load testing can be used to evaluate this systems performance for an increasing amount of simultaneous clients using the web application. The results from load testing the implemented system was above the expectations, considering the hardware used when running the tests and hosting the system. The conclusion of this thesis is that by following REST when designing a web service, scalability becomes a natural part of how one would design the system.
Place, publisher, year, edition, pages
2016. , 50 p.
REST, Representational state transfer, Scalable, Scalability, Load testing, Tsung, Python, Flask, SQLAlchemy
Computer Science Software Engineering Computer and Information Science
IdentifiersURN: urn:nbn:se:liu:diva-131253ISRN: LIU-IDA/LITH-EX-A--16/045--SEOAI: oai:DiVA.org:liu-131253DiVA: diva2:968802
Subject / course
2016-06-22, John von Neumann, Linköpings universitet, Linköping, 10:15 (English)
Berglund, Aseel, Universitetslektor
Eriksson, Henrik, Professor of Computer Science