Deploying Docker Swarm cluster on hybrid clouds using Occopus. (November 2018)

• Record Type: Journal Article
• Authors: Kovács, József; Kacsuk, Péter; Emődi, Márk
• Is Part Of: Advances in engineering software. Volume 125(2018)
• Page Start: 136
• Page End: 145
• Publication Date: 2018-11
• Subjects: Cloud -- Hybrid cloud -- Iaas -- Virtual machines -- Deployment -- Orchestration -- Occopus -- Docker container -- Swarm cluster -- Scalability; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2018.08.001
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: New, cloud independent deployment method and cloud orchestrator. New way of establishing complex virtual infrastructures and docker clusters over hybrid clouds. Investigating the use of VPN technology for hybrid clouds. Performance measurements to find the most optimal encryption method and MTU value for VPNs over hybrid clouds. Abstract: The paper introduces a new method of deploying complex infrastructures in hybrid clouds. The new method is based on a new cloud orchestrator, called Occopus that enables cloud independent infrastructure deployment at user level. Occopus applies a plugin based cloud access architecture. As a result, porting infrastructure among different kind of clouds or deploying an infrastructure on top of a hybrid cloud including private and public (commercial) clouds becomes straightforward. Occopus supports all the major cloud technologies and protocols like OpenStack, OpenNebula, OCCI, Amazon EC2 or CloudSigma. The paper also shows how to apply Occopus in order to deploy a Docker Swarm cluster on the top of hybrid clouds. As a concrete example it shows the deployment on a hybrid cloud system containing OpenStack, Amazon and CloudSigma clouds as components. Using hybrid clouds raises security and communication performance issues that are also covered and investigated in the paper. The technology described in the paper is intensively used in the EU H2020 project COLA for more than 20 commercial applications and on MTA Cloud that is the cloud of the Hungarian Academy of Sciences where more than 40 academic projects run.