RUS  ENG
Full version
JOURNALS // Proceedings of the Institute for System Programming of the RAS // Archive

Proceedings of ISP RAS, 2019 Volume 31, Issue 6, Pages 125–144 (Mi tisp473)

Data caching in multi-container systems

D. A. Grushina, D. O. Lazarevba, S. A. Fominba

a Ivannikov Institute for System Programming of the Russian Academy of Sciences
b Moscow Institute of Physics and Technology (State University)

Abstract: Today, virtualization is a key technology for cloud computing and modern data centers, providing scalability and security, managing the global IT infrastructure and reducing costs. Among the methods of virtualization, the most popular was containerization, that is the isolation of related groups of linux processes that share a common Linux kernel. Containerization is more profitable that classical hardware virtualization because of compactness of containers and lower overhead costs of memory, disk, CPU. However, in comparison with classical architectures without process isolation containers can cost more, and in any case, the industry is waiting for additional optimization – the speed of launch, saving memory and disk space and other resources. Different caching techniques can help in this, because Caching is the oldest mechanism of increasing software productivity without radical modification of algorithms and hardware. However, there are a lot of architectural and engineering tradeoffs. Here we will consider modern scientific and technical approaches to their solution in different aspects – acceleration of launch, optimization of shared usage, acceleration of building container images, as well as some security problems caused by aggressive caching in modern processor architectures. And in some use cases for multi-container systems performance and latency are not important, but we have to ensure the maximum load of physical servers. In these cases, the algorithms of planning and placement of containers are relevant, and we give an overview of theoretical work on this topic.

Keywords: containers, caching, cloud computing.

DOI: 10.15514/ISPRAS-2019-31(6)-7



© Steklov Math. Inst. of RAS, 2024