2026-04-19T19:19:18Zhttps://recercat.cat/oai/requestoai:recercat.cat:2117/1076992025-07-17T15:35:53Zcom_2072_1033col_2072_452951
Big data analytics on container-orchestrated systems
Casas Sáez, Gerard
University of Colorado Boulder
Anderson, Kenneth M.
Àrees temàtiques de la UPC::Informàtica
Big data
Software engineering
contenidors
analisis de dades
arquitectura de software
enginyeria del software
Kubernetes
Kafka
Cassandra
Twitter data
Projecte EPIC
escalabilitat
manteniment
container-orchestrated systems
Data analytics
infrastructure
software architecture
Project EPIC
scalability
maintenance
infraestructura
Macrodades
Enginyeria de programari
Container-orchestration systems offer new possibilites to software architects seeking
to make their software systems more scalable and reliable. In the past, these systems
have been used to implement transactional software systems but, more recently, they
have been applied to other areas including big data analytics. To understand the advantages
and limitations such systems impose on software architects, I migrated an
existing big data analytics infrastructure from a software architecture that required
lots of work from its developers to deploy and maintain to the new software architecture
provided by container-orchestration systems. My results show that scalability
is increased, maintenance costs are reduced, and reliability is easier to achieve.
2017-07-13
Bachelor thesis
https://hdl.handle.net/2117/107699
126670
eng
Open Access
application/pdf
Universitat Politècnica de Catalunya