Case study
FDEHPC/Infra
Agentic GPU fleet remediation
Reduced GPU idle time and incident MTTR via SLURM-aware auto-remediation and observability integrated with agentic ops tooling.
Tier-1 GPU cloud provider · ~6 min read
Anonymized case study. Metrics marked [TBD] pending client validation. Status: draft.
At a glance
MTTR reduction
[TBD: %]
Mean time to restore healthy GPU nodes vs manual baseline
Manual escalations
[TBD: % fewer]
Platform ops tickets requiring on-call intervention
Autonomous remediations
[TBD: N/week]
Safe playbook executions without human approval
Fleet availability
[TBD: %]
GPU schedulable hours recovered
Problem
A large GPU cloud fleet running SLURM for multi-tenant HPC and ML workloads suffered recurring failure patterns tied to DCGM telemetry anomalies, queue stalls, and degraded node health. Operators relied on fragmented Grafana dashboards and manual Jira workflows: an on-call engineer would triage alerts, SSH to nodes, run ad hoc diagnostics, and only then decide whether to drain, reboot, or escalate to hardware vendor support.
That loop delayed tenant workloads, increased idle GPU capacity, and burned senior platform engineering time on repeatable incidents. Existing observability showed what was wrong but lacked closed-loop remediation, structured runbooks agents could execute, and guardrails that kept automation safe at fleet scale.
Approach
- Failure-mode mapping — Catalogued DCGM signals, SLURM node states, and queue behaviors; paired each pattern with a remediation playbook ranked by blast radius.
- Observability alignment — Normalized Grafana panels and alert routes so incidents carried structured context (node ID, job impact, suggested playbook).
- MCP-accessible tooling — Exposed read-only metrics queries, Jira create/update, and approved remediation CLIs to agentic workflows via MCP so operators and agents shared the same tool surface.
- Guardrails & handoff — Defined human-in-the-loop gates for destructive actions; documented runbooks for sustained ops after FDE embed period.
Results
[TBD: Insert validated metrics before publish.]
- Repeatable DCGM/SLURM fault classes moved from ad hoc runbooks to version-controlled playbooks.
- Incident tickets arrived with pre-attached telemetry context, shortening triage.
- Agent-assisted workflows handled read-only investigation and ticket updates autonomously; remediation steps ran in shadow mode before canary rollout.