GPU utilization
See how consistently each device performs useful work and where activity is uneven.
GPU fleet monitoring
See when expensive GPUs are busy, idle, hot, or missing
GPUFlight aligns GPU utilization, memory, temperature, power, host activity, and collection health across the same time window. Investigate one device or scan a fleet without treating a quiet chart as proof that everything is healthy.
- NVIDIA and AMD devices
- Host and GPU context
- Dashboards and alerts
Utilization needs context
Distinguish idle GPUs from missing telemetry
A zero or empty chart can describe several different situations: an intentionally idle GPU, a workload that is waiting on CPU or I/O, a collection gap, an offline host, or a monitoring process that stopped reporting. GPUFlight represents activity states and time breaks explicitly so missing data does not silently look like low utilization.
Bring GPU and host measurements into the same investigation. CPU saturation, host-memory pressure, temperature, power limits, and uneven device activity can explain behavior that a GPU-utilization percentage cannot explain by itself.
Fleet signals
Monitor the measurements operators actually need
Move from a fleet summary into the host, device, metric, and time range behind it.
Capacity and activity
Track memory used and memory-controller activity alongside the workload timeline.
Temperature and power
Find thermal and power behavior that may limit performance or indicate operational risk.
CPU and system memory
Identify upstream resource pressure that can leave an otherwise healthy GPU waiting.
Activity and data gaps
Separate low utilization from no samples, stale devices, and explicit time discontinuities.
Alerts and history
Define threshold rules, route notifications, and retain the event context for investigation.
One timeline
Compare metrics without losing temporal alignment
GPU utilization, CPU load, memory, temperature, and power often tell different parts of the same story. GPUFlight dashboards keep panels on a shared time range so an operator can compare changes without manually lining up separate monitoring tools.
- Fleet-wide and per-device views
- Shared time ranges from recent activity to multi-day trends
- Configurable metric panels and operational dashboards
- Host, device, and workload identifiers for investigation
- Activity history that makes collection gaps visible
From symptom to profile
Connect operational monitoring to kernel investigation
Monitoring shows when a device or workload behaves unexpectedly. Profiling explains the CUDA or ROCm execution behind a specific run. GPUFlight keeps both workflows in one product so a fleet-level symptom can lead into a detailed kernel, memory, source, or timeline investigation instead of ending at a generic utilization chart.
Explore the deeper development workflow in the CUDA profiler.
Common questions
GPU monitoring FAQ
Which GPU vendors can GPUFlight monitor?
GPUFlight supports NVIDIA and AMD monitoring paths. Available fields and deeper profiling capabilities vary with the vendor, driver, and collection environment.
Can I monitor more than one host?
Yes. The fleet views group devices by host and allow investigation across multiple registered systems within plan limits.
How is this different from checking nvidia-smi?
A command-line snapshot is useful for one moment on one host. GPUFlight retains time-series history, aligns related metrics, represents collection gaps, and adds dashboards, alerts, and profiling context.
Does monitoring require application instrumentation?
GPU monitoring is collected by the monitoring service rather than requiring every application to use the profiling SDK. Profiling can be added separately when deeper workload evidence is needed.
Build a trustworthy GPU timeline
Start monitoring your first GPU host
Create a workspace, connect the monitoring service, and see device activity in the browser.
Start monitoring