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Conference Papers Year : 2018

IOscope: A Flexible I/O Tracer for Workloads' I/O Pattern Characterization


Storage systems are getting complex to handle HPC and Big Data requirements. This complexity triggers performing in-depth evaluations to ensure the absence of issues in all systems' layers. However, the current performance evaluation activity is performed around high-level metrics for simplicity reasons. It is therefore impossible to catch potential I/O issues in lower layers along the Linux I/O stack. In this paper, we introduce IOscope tracer for uncovering I/O patterns of storage systems' workloads. It performs filtering-based profiling over fine-grained criteria inside Linux kernel. IOscope has near-zero overhead and verified behaviours inside the kernel thanks to relying on the extended Berkeley Packet Filter (eBPF) technology. We demonstrate the capabilities of IO-scope to discover patterns-related issues through a performance study on MongoDB and Cassandra. Results show that clustered MongoDB suffers from a noisy I/O pattern regardless of the used storage support (HDDs or SSDs). Hence, IOscope helps to have better troubleshooting process and contributes to have in-depth understanding of I/O performance.
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hal-01828249 , version 1 (03-07-2018)


  • HAL Id : hal-01828249 , version 1


Abdulqawi Saif, Lucas Nussbaum, Ye-Qiong Song. IOscope: A Flexible I/O Tracer for Workloads' I/O Pattern Characterization. ISC High Performance 2018 International Workshops - WOPSSS'18, Jun 2018, Frankfurt, Germany. ⟨hal-01828249⟩
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