~/talk

Perseus: A Fail-Slow Detection Framework for Cloud Storage Systems

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name:Erci Xu
linkedin:ercixu
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name:Jiwu Shu
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name:Minglu Li
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slides:none on file

Perseus detects fail-slow drives non‑intrusively by modeling latency versus throughput with a light regression model, using outlier removal, an adaptive upper bound, sliding‑window event aggregation and a risk score. Deployed across 248K drives during 10 months, it flags 304 fail-slow cases, isolates them to cut node‑level 99.99th tail latency by 48%, and ships a public benchmark drawn from 41K normal and 315 verified fail‑slow drives for root‑cause analysis.

AI-written summary · about

  1. 0:00Start
  2. 0:1421st USENIX Conference on File and Storage Technologi
  3. 4:39FAST? Failed Attempt: Threshold Filtering
  4. 11:56Outlier Detection
  5. 12:14Building Regression Model
  6. 12:39Identifying Fail-Slow Event
  7. 13:16Evaluating Risk
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