Know what is happening

Less guesswork.
More useful monitoring.

Define mining and GPU telemetry, spot stale data, plan actionable alerts, and maintain a recoverable hardware configuration with useful operating records.

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Know what is happening concept illustration

Priority / 01

Define the metric

Keep source, units, observation window, and sensor meaning visible. One generic performance number is not enough.

Priority / 02

Show when data is missing

A last-known good value is not evidence of current health. Freshness and collection failures deserve their own states.

Priority / 03

Attach an action

Each alert needs an owner, a first check, and a clear limit on what to change. Start with observation, not aggressive automation.

Make a dashboard earn its place

Monitoring should help somebody decide what to do. Begin with an inventory that connects each machine to its location, model, configuration, documentation, and owner. Keep credentials in a separate secure system rather than in the asset record.

For mining, distinguish local hashrate, accepted work, rejected work, operating mode, and connectivity. For AI, track application completion, quality, latency, throughput, and relevant device metrics. Do not collapse different workloads into a single unexplained performance score.

Establish a read-only baseline

Collect observations before adding automated control. Record the software versions and measurement boundaries. A GPU-reported power value should not silently become the entire site's electricity use, and an unavailable sensor should not silently become zero.

On supported NVIDIA hardware with the driver installed, the read-only command below requests device identification, temperature, power, utilization, and memory information. Support varies by configuration. It does not monitor an ASIC and does not change clocks or power limits.

nvidia-smi --query-gpu=name,temperature.gpu,power.draw,utilization.gpu,memory.used,memory.total --format=csv

Record freshness and context

Show collection timestamps and define a stale-data state. A network issue, monitoring-agent failure, or permission change can break telemetry without proving the appliance itself has failed. Keep those observation failures separate from device-reported faults.

Align output, environmental conditions, software changes, and incidents on a shared timeline. Treat correlation as a starting hypothesis, not a diagnosis. Preserve evidence before permitted restarts when the support procedure allows it.

Make maintenance repeatable

Follow manufacturer guidance for inspection, shutdown, isolation, and cleaning. Use qualified service personnel where necessary. Do not open power supplies, bypass safeguards, or substitute unverified parts based on a generic guide.

Record each change and test the system afterward against its baseline. Store configuration and recovery instructions away from the appliance. The full monitoring article explains how to build actionable alerts and useful incident notes.

Bring operating lessons into the next purchase

Review recurring issues, maintenance effort, interruptions, and whether the machine still suits its job. Use consistent observation periods rather than labeling partial data as a full month.

Carry those findings into your buying checklist and power planning. The objective is a system that remains understandable and recoverable—not a dashboard with the most animated counters.

Further reading: NVIDIA System Management Interface documentation ↗