Your GPU cluster's 3am page.
Handled.

Monitors GPU clusters. Diagnoses failures in seconds. Remediates autonomously.

Currently onboarding design partners

AI SRE for GPU Infrastructure

The status quo

GPU failures are exotic.

NCCL timeouts. NVLink degradation. ECC errors. Silent data corruption. Your observability stack wasn't built for this.

MTTR is measured in hours.

An engineer SSHs into nodes one by one, tails logs, checks nvidia-smi. Meanwhile your training run is dead and GPUs are burning money idle.

Your best people are burning out.

Senior GPU SREs are impossible to hire and easy to lose. On-call fatigue is the #1 reason they leave.

How it works

Three steps. Seconds, not hours.

Detect

Ingests telemetry from DCGM, nvidia-smi, NCCL logs, IPMI/BMC, kernel logs, and your existing observability stack. Catches failures before they cascade.

Diagnose

Correlates signals across the cluster. Identifies root cause in seconds — not "a GPU is unhealthy" but "Node 47, GPU 3, NVLink 2 has degraded bandwidth causing NCCL all-reduce timeouts."

Remediate

Fences bad nodes, triggers failover, restarts workloads, or escalates with full context. Graduated autonomy: starts as copilot, earns trust, acts autonomously.

Why Trustplane

Kubernetes & bare metal.

Most tools assume K8s. Trustplane works on bare metal clusters, SLURM, custom orchestration — wherever GPUs run.

GPU-native intelligence.

Built by engineers who've operated GPU clusters at scale. Understands failure modes that general-purpose monitoring misses.

Integrates, doesn't replace.

Works with Datadog, Grafana, PagerDuty, Prometheus, your existing stack. Adds intelligence on top.

Mean time to resolution

47 min<5 min

The average GPU cluster incident takes 47 minutes to resolve. Trustplane resolves it in under 5.

Your GPUs are too expensive to babysit.

Stop paying for idle GPUs while your team debugs NCCL timeouts at 3am.

Request Early Access

No credit card. No sales call. Just tell us about your cluster.