TY - GEN
T1 - On the performance variation in modern storage stacks
AU - Cao, Zhen
AU - Tarasov, Vasily
AU - Raman, Hari Prasath
AU - Hildebrand, Dean
AU - Zadok, Erez
N1 - Publisher Copyright:
© Proceedings of the 15th USENIX Conference on File and Storage Technologies, FAST 2017. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Ensuring stable performance for storage stacks is important, especially with the growth in popularity of hosted services where customers expect QoS guarantees. The same requirement arises from benchmarking settings as well. One would expect that repeated, carefully controlled experiments might yield nearly identical performance results-but we found otherwise. We therefore undertook a study to characterize the amount of variability in benchmarking modern storage stacks. In this paper we report on the techniques used and the results of this study. We conducted many experiments using several popular workloads, file systems, and storage devices-and varied many parameters across the entire storage stack. In over 25% of the sampled configurations, we uncovered variations higher than 10% in storage performance between runs. We analyzed these variations and found that there was no single root cause: it often changed with the workload, hardware, or software configuration in the storage stack. In several of those cases we were able to fix the cause of variation and reduce it to acceptable levels. We believe our observations in benchmarking will also shed some light on addressing stability issues in production systems.
AB - Ensuring stable performance for storage stacks is important, especially with the growth in popularity of hosted services where customers expect QoS guarantees. The same requirement arises from benchmarking settings as well. One would expect that repeated, carefully controlled experiments might yield nearly identical performance results-but we found otherwise. We therefore undertook a study to characterize the amount of variability in benchmarking modern storage stacks. In this paper we report on the techniques used and the results of this study. We conducted many experiments using several popular workloads, file systems, and storage devices-and varied many parameters across the entire storage stack. In over 25% of the sampled configurations, we uncovered variations higher than 10% in storage performance between runs. We analyzed these variations and found that there was no single root cause: it often changed with the workload, hardware, or software configuration in the storage stack. In several of those cases we were able to fix the cause of variation and reduce it to acceptable levels. We believe our observations in benchmarking will also shed some light on addressing stability issues in production systems.
UR - https://www.scopus.com/pages/publications/85077189995
M3 - Conference contribution
AN - SCOPUS:85077189995
T3 - Proceedings of the 15th USENIX Conference on File and Storage Technologies, FAST 2017
SP - 329
EP - 343
BT - Proceedings of the 15th USENIX Conference on File and Storage Technologies, FAST 2017
PB - USENIX Association
T2 - 15th USENIX Conference on File and Storage Technologies, FAST 2017
Y2 - 27 February 2017 through 2 March 2017
ER -