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

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...

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Vydáno v:Journal of cloud computing : advances, systems and applications Ročník 13; číslo 1; s. 124 - 14
Hlavní autoři: Lee, Jeongmin, Kang, Hyeongbin, Yu, Hyeon-jin, Na, Ji-Hyun, Kim, Jungbin, Shin, Jae-hyuck, Noh, Seo-Young
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2024
Springer Nature B.V
SpringerOpen
Témata:
Big Data
Checkpoint/restore
Checkpointing
Cloud computing
Computer Communication Networks
Computer memory
Computer Science
Computer System Implementation
Computer Systems Organization and Communication Networks
Container
Containers
Data processing
Data recovery
Efficiency
Failure
In-memory database
Information Systems Applications (incl.Internet)
Kubernetes
Software Engineering/Programming and Operating Systems
Special Purpose and Application-Based Systems
Workload
Workloads
Container
Checkpoint/restore
Kubernetes
In-memory database
ISSN:2192-113X, 2192-113X
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Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
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ISSN:2192-113X
2192-113X
DOI:10.1186/s13677-024-00687-9