iGen: A Realistic Request Generator for Cloud File Systems Benchmarking
Zujie Ren, Biao Xu, Weisong Shi, Yongjian Ren, Feng Cao, Jiangbin Lin, Zheng Ye · 2016
Benchmarking is a traditional approach for system performance evaluation and optimization. Over the past decades, a variety of file systems, e.g., GFS, HDFS and Ceph, have been designed and implemented, serving as the key components in cloud infrastructures. With the mature of those cloud file systems, the demands for performance evaluation and comparison are also rising. However, due to the complexity and heterogeneity of I/O workloads in cloud infrastructures, it is still challenging to generate realistic I/O workloads. System developers often use traditional file system benchmarks and make inaccurate assumptions on workload generation, yielding to misleading results. To address this problem, we investigate the characteristics of I/O requests in a production cloud infrastructure at Alibaba Cloud Computing, which is one of the biggest cloud providers in Asia. We proposed a flexible framework iGen to mimic I/O request arrivals. One of the salient features of the iGen is that the request arrival process is modeled by three statistics properties, request arrival rate, inter-arrival time distribution, and request periodicity. According to these properties, the iGen can determine the sequence of requests and the inter-arrival time between two subsequent requests. We use the iGen to emulate a real workload that collected from Alibaba cloud platform. Experimental results show that high accuracy and flexibility of the iGen.