Running GPU workloads at scale requires layers of infrastructure. Each layer has matured significantly. But there's a gap.
The Modern GPU Stack
Hardware: GPUs, networking, storage. Orchestration: Kubernetes, Slurm, custom schedulers. Monitoring: Prometheus, Grafana, custom dashboards. ML Platforms: MLflow, Weights & Biases, custom tooling.
The Missing Layer
You can see GPU utilization. You can see queue length. You can see job status.
But can you answer: "When will my job actually start?"
For most teams, the answer is no.
Where Visibility Fits
Queue prediction sits between the scheduler and the user. It takes signals from across the stack and translates them into actionable expectations.
*Interested in completing your GPU stack? Talk to us.*