Performance of Cluster-based High Availability Database in Cloud Containers

被引:1
作者
Shrestha, Raju [1 ]
机构
[1] OsloMet Oslo Metropolitan Univ, Oslo, Norway
来源
PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE (CLOSER) | 2020年
关键词
Performance; High Availability; Database; Cloud; Galera Cluster; Virtual Machine; Container; Docker; REPLICATION TECHNIQUES;
D O I
10.5220/0009387103200327
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Database is an important component in any software application, which enables efficient data management. High availability of databases is critical for an uninterruptible service offered by the application. Virtualization has been a dominant technology behind providing highly available solutions in the cloud including database, where database servers are provisioned and dynamically scaled based on demands. However, containerization technology has gained popularity in recent years because of light-weight and portability, and the technology has seen increased number of enterprises embracing containers as an alternative to heavier and resource-consuming virtual machines for deploying applications and services. A relatively new cluster-based synchronous multi-master database solution has gained popularity recently and has seen increased adoption against the traditional master-slave replication for better data consistency and high availability. This article evaluates the performance of a cluster-based high availability database deployed in containers and compares it to the one deployed in virtual machines. A popular cloud software platform, OpenStack, is used for virtual machines. Docker is used for containers as it is the most popular container technology at the moment. Results show better performance by HA Galera cluster database setup using Docker containers in most of the Sysbench benchmark tests compared to a similar setup using OpenStack virtual machines.
引用
收藏
页码:320 / 327
页数:8
相关论文
共 29 条
  • [1] Containers and Cloud: From LXC to Docker to Kubernetes
    Bernstein, David
    [J]. IEEE CLOUD COMPUTING, 2014, 1 (03): : 81 - 84
  • [2] CAP Twelve Years Later: How the "Rules" Have Changed
    Brewer, Eric
    [J]. COMPUTER, 2012, 45 (02) : 23 - 29
  • [3] Schism: a Workload-Driven Approach to Database Replication and Partitioning
    Curino, Carlo
    Jones, Evan
    Zhang, Yang
    Madden, Sam
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2010, 3 (01): : 48 - 57
  • [4] Earl L., 2003, US Patent App, Patent No. [10/426,467, 10426467]
  • [5] Database replication using generalized snapshot isolation
    Elnikety, S
    Pedone, F
    Zwaenepoel, W
    [J]. 24TH IEEE SYMPOSIUM ON RELIABLE DISTRIBUTED SYSTEMS, PROCEEDINGS, 2005, : 73 - 84
  • [6] Felter W, 2015, INT SYM PERFORM ANAL, P171, DOI 10.1109/ISPASS.2015.7095802
  • [7] Elastic Application Container: A Lightweight Approach for Cloud Resource Provisioning
    He, Sijin
    Guo, Li
    Guo, Yike
    Wu, Chao
    Ghanem, Moustafa
    Han, Rui
    [J]. 2012 IEEE 26TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS (AINA), 2012, : 15 - 22
  • [8] Hvasshovd S.-O., 1995, VLDB '95. Proceedings of the 21st International Conference on Very Large Data Bases, P469
  • [9] IBM Cloud, 2019, LAMP STACK
  • [10] Jacobs M., 2018, WHAT IS T