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Publication D source code Elastic Build Service
Linux-based operating systems such as MeeGo consist of thousands of modular software packages. Compiling and packaging source code is an automated but computationally heavy task. As the load on a build farm can vary greatly, a local infrastructure is difficult to provision efficiently. In this paper we present the elastic acquisition of cloud resources as a means to ensure sufficient computing capacity for a software build system. This system is Open Build Service, a centrally managed distributed build system capable of building packages for several distributions and architectures. Main concerns were the technical feasibility, security and cost-efficiency of the proposed solution. A script was implemented to autonomously manage the elastic cloudbursting, monitoring resource usage and demand and making decisions whether new machines should be requested or idle ones terminated. The latencies incurred by the physical distance to the cloud were not insurmountable and the system scaled up in a matter of minutes. The main advantage achieved with cloud usage in this work was the advent of seemingly infinite number of resources on-demand, ideal for building taking care of sudden bursts of packages that can be built in parallel.
Located in Issues / … / Volume 1 / 1
Publication D source code Elastic Build Service
Linux-based operating systems such as MeeGo consist of thousands of modular software packages. Compiling and packaging source code is an automated but computationally heavy task. As the load on a build farm can vary greatly, a local infrastructure is difficult to provision efficiently. In this paper we present the elastic acquisition of cloud resources as a means to ensure sufficient computing capacity for a software build system. This system is Open Build Service, a centrally managed distributed build system capable of building packages for several distributions and architectures. Main concerns were the technical feasibility, security and cost-efficiency of the proposed solution. A script was implemented to autonomously manage the elastic cloudbursting, monitoring resource usage and demand and making decisions whether new machines should be requested or idle ones terminated. The latencies incurred by the physical distance to the cloud were not insurmountable and the system scaled up in a matter of minutes. The main advantage achieved with cloud usage in this work was the advent of seemingly infinite number of resources on-demand, ideal for building taking care of sudden bursts of packages that can be built in parallel.
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