MDB-KCP: persistence framework of in-memory database with CRIU-based container checkpoint in Kubernetes

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Titel: MDB-KCP: persistence framework of in-memory database with CRIU-based container checkpoint in Kubernetes
Autoren: Jeongmin Lee, Hyeongbin Kang, Hyeon-jin Yu, Ji-Hyun Na, Jungbin Kim, Jae-hyuck Shin, Seo-Young Noh
Quelle: Journal of Cloud Computing: Advances, Systems and Applications, Vol 13, Iss 1, Pp 1-14 (2024)
Verlagsinformationen: SpringerOpen, 2024.
Publikationsjahr: 2024
Bestand: LCC:Computer engineering. Computer hardware
LCC:Electronic computers. Computer science
Schlagwörter: Container, Kubernetes, In-memory database, Checkpoint/restore, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95
Beschreibung: Abstract As the demand for container technology and platforms increases due to the efficiency of IT resources, various workloads are being containerized. Although there are efforts to integrate various workloads into Kubernetes, the most widely used container platform today, the nature of containers makes it challenging to support persistence for memory-centric workloads like in-memory databases. In this paper, we discuss the drawbacks of one of the persistence support methods used for in-memory databases in a Kubernetes environment, namely, the data snapshot. To address these issues, we propose a compromise solution of using container checkpoints. Through this approach, we can perform checkpointing without incurring additional memory usage due to CoW, which is a problem in fork-based data snapshots during snapshot creation. Additionally, container checkpointing induces up to 7.1 times less downtime compared to the main process-based data snapshot. Furthermore, during database recovery, it is possible to achieve up to 11.3 times faster recovery compared to the data snapshot method.
Publikationsart: article
Dateibeschreibung: electronic resource
Sprache: English
ISSN: 2192-113X
Relation: https://doaj.org/toc/2192-113X
DOI: 10.1186/s13677-024-00687-9
Zugangs-URL: https://doaj.org/article/52f9c1f5e7e74c8795def90b9a77e412
Dokumentencode: edsdoj.52f9c1f5e7e74c8795def90b9a77e412
Datenbank: Directory of Open Access Journals