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PARLON GPU FLEET MONITORING SOLUTION
GPUs are the most expensive thing in your data center, and the hardest to see clearly.
The Parlon GPU Fleet Solution gives capacity planners and on-call engineers a live, fleet-wide view of GPU health, utilization, and waste, down to a single device.
THE PROBLEM
A GPU fleet averaging a healthy-looking 45% utilization can still be half maxed out and half sitting idle. The average hides the split, and the idle half is capacity you already paid for.
Most infrastructure monitoring wasn’t built to separate a GPU that’s healthy from one that’s actually doing work, or to catch a device quietly throttling under heat before it costs a training job real time. The Parlon GPU Fleet Solution reads the standard NVIDIA Data Center GPU Manager (DCGM) telemetry your GPUs already emit, so there’s nothing new to instrument. It turns that raw telemetry into a single, fleet-wide view your team can act on.
WHAT IT DOES
What the Parlon GPU Fleet Solution does
Fleet-wide health & thermal visibility
Real-time fleet size, utilization, power, errors, and hottest GPU, with Throttle Watch correlating clock frequency against temperature to catch thermal throttling as it happens.
Utilization & waste detection
A distribution histogram and idle GPU-hours expose stranded capacity a single average would hide, reported in percent, hours, and watts, never currency.
Per-GPU drill-down
Click any GPU for its full identity, a plain-language health reason, and sparklines for utilization, memory, temperature, power, and clock speed.
Expert Mode hardware deep-dive
Six collapsible subsystem views, thermal, power, compute, memory, interconnect, and errors, for GPU engineers who need to go deeper without cluttering the primary page.
SEE IT IN ACTION
Watch GPU Fleet live on a running data center
FREE DOWNLOAD
The GPU Fleet Solution Guide
Every KPI card, threshold, and URL parameter, plus three end-to-end scenarios: the morning fleet check, chasing a thermal event, and proving the fleet is actually busy.
WORKING SCENARIOS
How teams actually use it
The morning fleet check
Did anything change overnight, and is capacity being used?
- Open the 24h view — the KPI row is the whole story in six numbers
- Scan the histogram for a growing idle band that wasn’t there yesterday
- Check devices-with-errors, then filter per cluster if one owns the idle GPUs
Chasing a thermal event
The hottest-GPU KPI is red at 87°C. What’s happening?
- Sort the inventory by temperature — the hot GPU surfaces to the top
- Open the drill-down for the plain-language health reason
- Check Throttle Watch: if clocks dip as temperature peaks, heat is already costing performance
Is the fleet actually busy?
Leadership wants to know if the GPUs are earning their power draw.
- Trend panel, grouped by cluster, over 7 days — steady load, bursts, or dead nights?
- Histogram: the split between busy buckets and the idle band right now
- “Most idle” preset — idle hours accumulating on the same devices is reclaimable capacity
47.7%
WHY IT MATTERS
of enterprises already have AI training or inference workloads deployed today. Every idle GPU behind a healthy-looking average is capacity you already paid for.
DEPLOYMENT & COVERAGE
One fabric, one inventory.
GPU telemetry flows through the same Normalization Engine as every other infrastructure source. Every reporting GPU also appears in Parlon’s unified asset inventory, alongside the rest of your monitored estate.
Reads standard NVIDIA DCGM telemetry, so any DCGM-instrumented data-center GPU is supported out of the box.
SOLUTION
The Overview tab, at a glance
