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Cloud bursting is used to offload processing to the cloud when on-premise data centers run out of computing resources. Data in the on-premise data center needs to be copied to the cloud at the start of cloud bursting. Since data capacity and usage of connection between on-premise data center and cloud vary, the time required to build a cloud bursting environment will vary. This made it difficult to determine a configuration that could resume processing within the recovery time objective at a low cost in the event of a failure in the cloud. In this study, we proposed a redundancy determination method based on reliability requirements that estimates the time required to build a cloud bursting environment considering data capacity and the usage of connection between on-premise data centers and the cloud, and determines a configuration that satisfies recovery time objective at low cost. Assuming the case of cloud bursting of data analysis processing, we conducted an experiment in which a system simulating an analysis application was cloud bursted from an AZ simulating an on-premise data center to the main AZ, and the range of the system built in advance in the sub AZ was changed to simulate a sub AZ failure and failover to the sub AZ. As a result, it was confirmed that the time required for failover can be reduced by increasing the extent to which the system is preconstructed in the sub AZ. The proposed method is expected to enable us to determine a configuration that can meet the recovery time objective at a low cost.
Hayashi et al. (Sun,) studied this question.