MTTR (Mean Time to Resolution)
Average 47-minute GPU issue resolution time covering detection, diagnosis, and repair.
What it is
MTTR (Mean Time to Resolution) is the average elapsed time from when a GPU infrastructure issue is first detected to when the affected resources are fully validated and returned to the production scheduling pool. It spans four phases: detection (monitoring lag), diagnosis (root cause identification), remediation (executing the fix), and validation (health checks confirming the repair). Industry data shows traditional GPU cluster MTTR averaging 47 minutes per incident.
Why it matters
The 47-minute average splits heavily toward human-dependent phases: detection averages 5-8 minutes, diagnosis 20-25 minutes of manual Xid-DCGM-NCCL correlation, remediation 8-12 minutes, and validation 3-5 minutes. In a 4,096-GPU cluster experiencing 15 incidents per day, a 47-minute MTTR translates to 94 GPU-hours of lost compute daily -- over 34,000 GPU-hours annually. A single Xid 94 event during a 512-GPU training run can leave all 512 GPUs idle for 40+ minutes during manual triage.
How to monitor
Instrument each incident phase with timestamps: alert fire time, runbook start time, remediation completion time, and validation completion time. Track MTTR by incident category (ECC, NVLink, thermal) to identify which failure modes dominate engineer time. Factryze reduces MTTR from 47 minutes to under 2 minutes by automating all four phases -- detection via streaming telemetry, diagnosis via parallel Xid/DCGM/NCCL correlation, autonomous runbook execution, and targeted health check validation.
Related terms
Executable remediation procedures with conditional logic and approval gates for GPU issues.
AI-driven GPU infrastructure operations moving beyond traditional alerting to autonomous remediation.
DCGM diagnostic tests (Level 1/2/3) validating GPU hardware integrity between jobs.
Monitor this automatically
Factryze correlates GPU signals in real time: errors, clocks, and fabric health.
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