Black-Box Problem Diagnosis in Parallel File Systems

Michael P. Kasick, Jiaqi Tan, Rajeev Gandhi, Priya Narasimhan
2010 USENIX Conference on File and Storage Technologies  
We focus on automatically diagnosing different performance problems in parallel file systems by identifying, gathering and analyzing OS-level, black-box performance metrics on every node in the cluster. Our peercomparison diagnosis approach compares the statistical attributes of these metrics across I/O servers, to identify the faulty node. We develop a root-cause analysis procedure that further analyzes the affected metrics to pinpoint the faulty resource (storage or network), and demonstrate
more » ... hat this approach works commonly across stripe-based parallel file systems. We demonstrate our approach for realistic storage and network problems injected into three different file-system benchmarks (dd, IOzone, and Post-Mark), in both PVFS and Lustre clusters.
dblp:conf/fast/KasickTGN10 fatcat:udm56zouhraozlmhzxr52ew52e