Performance Evaluation of Virtual Machines Instantiation in a Private Cloud

Elasticity is an outstanding concept of cloud computing, usually deployed through mechanisms such as auto scaling and load balancing. Cloud-based applications are able to adapt themselves dynamically to the workload behavior due to such mechanisms. The efficient instantiation of Virtual Machines (VMs) is one requirement for the elastic behavior of cloud-based applications. This study characterizes the performance of VM instantiation in a private cloud platform, considering distinct factors such as VM type, VM image size, and VM caching. We employed a full factorial design of experiments (DoE) to compute the effect and relevance of the factors as well as their interactions. Our experimental results show that the cache factor has an impact of 45.07 % on the total instantiation time, whereas the machine image (MI) has 26.45 % and the VM type only 1.05 %. The results of these experiments are also used as input parameters in a Markov chain model for sensitivity analysis. The model evaluation showed that for 6 GB and 8 GB MI, the probability of finding the MI on cache must be at least 40 % and 60 % respectively, to achieve an average instantiation time of 300 seconds. For MI with size 2 GB, such time is not exceeded even with the cache disabled. This analysis allows checking the impact of every parameter on the system response time and pointing out effective ways for improvement of performance. Such conclusions may be used as decision support for systems which often instantiate new VMs, including those using elasticity features, such as auto scaling.