Workload Evaluation Tool for Metadata Distribution Method.

In the High Performance Computing field (HPC), metadata server cluster is a critical aspect of a storage system performance and with object storage growth, systems must now be able to distribute metadata across servers thanks to distributed metadata servers. Storage systems reach better performances if the workload remains balanced over time. Indeed, an unbalanced distribution can lead to frequent requests to a subset of servers while other servers are completely idle. To avoid this issue, different metadata distribution methods exist and each one has its best use cases. Moreover, each system has different usages and different workloads, which means that one distribution method could fit to a specific kind of storage system and not to another one. To this end, we propose a tool to evaluate metadata distribution methods with different workloads. In this paper, we describe this tool and we use it to compare state-of-the-art methods and one method we developed. We also show how outputs generated by our tool enable us to deduce distribution weakness and chose the most adapted method.