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RUNNING DATABASES IN A KUBERNETES CLUSTERAn evaluation
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

A recent trend in so‰ftware engineering is to build applications composed of a set of small independent services – microservices. Kubernetes has become the common denominator for hosting stateless microservices. It off‚ers foundational features such as deployment and replication of microservices as well as cluster resource management. Whereas stateless microservices are well suited to being hosted in Kubernetes, stateful microservices such as databases are generally hosted outside of Kubernetes and managed by domain experts. It is desirable to run stateful services such as databases in Kubernetes to leverage its features, ease of operation, and to harmonize the environment across the entire application stack. Th‘e purpose of this thesis is to investigate and evaluate the current support for hosting stateful applications in the form of databases in Kubernetes, and to show how di‚fferent databases are able to operate in Kubernets. An experimental setup was used where a set of databases – MySQL, TiDB, and CockroachDB, were deployed in a Kubernetes cluster. For each of these databases, a set of operational tasks were performed that concerned backup, upgrading, and capacity re-scaling. During the operations a number of server-sided and clients idedmetrics related to the performance and resource effciency of the databases were captured. ‘The results showed that Kubernetes has got the native capabilities necessary to deploy and run databases, but not to fully operate them correctly. Furthermore, it was concluded that the operations had a widely di‚fferent performance impact depending on the database solution.

Place, publisher, year, edition, pages
2019. , p. 52
Series
UMNAD ; 1215
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:umu:diva-165164OAI: oai:DiVA.org:umu-165164DiVA, id: diva2:1369598
External cooperation
Elastisys
Educational program
Master of Science Programme in Computing Science and Engineering
Supervisors
Examiners
Available from: 2019-11-12 Created: 2019-11-12 Last updated: 2019-11-12Bibliographically approved

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