Per-Second Visibility Into Every Robot, Across Every Site

Each Netdata Agent runs locally on the robot, collecting and storing metrics independently. During network drops, agents buffer data locally and automatically backfill regional Parents when connectivity returns. Your fleet maintains full observability even on intermittent site networks. Learn more on our edge fleet monitoring page.

Netdata auto-discovers and collects per-second CPU, memory, disk I/O, storage, network interfaces, per-process resource usage, systemd services, thermal sensors, GPU metrics where present via NVIDIA and AMD collectors, and battery or power telemetry exposed by the OS. Over 800 integrations work out of the box with zero configuration.

Yes. Netdata provides per-second GPU metrics including utilization, memory, temperature, power consumption, and PCIe bandwidth for NVIDIA and AMD GPUs. See our AI and ML industry page for more on edge AI workload monitoring.

Netdata trains 18 unsupervised ML models locally on every metric for every robot. Each robot learns its own behavioral baseline, so anomalies are detected relative to that specific device’s normal patterns — not a fleet-wide average. This catches per-robot issues like thermal throttling or memory leaks that fleet averages would hide.

The Netdata Agent typically uses less than 5% of a single CPU core and 150-200 MB of RAM, including machine learning. Agents can be further reduced to under 2% CPU and approximately 100 MB RAM in child mode, where ML training and storage are offloaded to Parents.

Netdata uses simple per-node pricing with P90 billing protection — you pay for sustained usage, not temporary spikes. Agents are free and open source. Costs scale linearly with your fleet, not with data volume or metric count. See our pricing page for details.

No. Netdata generates dashboards algorithmically based on the metrics each robot exposes. Different robot types with different hardware automatically get appropriate visualizations. No query languages, no manual dashboard building, no specialized skills required.

Yes. Netdata Functions surface console-grade tools inside the dashboard — process tables, network connections, systemd units, disk usage, and more. Operators get the same per-second precision as SSH debugging, but with full history, ML context, and no direct device access.

Netdata reads systemd-journal files directly on each robot, with no separate log pipeline, ingestion server, or shipping infrastructure. Every field in every log entry is automatically indexed and searchable. This delivers up to 90% cost reduction compared to centralized log management platforms.

The Netdata Agent restarts in 2-3 seconds and resumes collection immediately. Systemd-journal logs capture crash events and core dumps. ML anomaly detection flags the behavioral shift. Parents retain historical data, so operators can compare pre- and post-restart states across the fleet.

Yes. Netdata exports metrics to Prometheus, Grafana, InfluxDB, Graphite, and OpenTSDB. It supports OpenTelemetry for metrics and logs. Alert notifications route to PagerDuty, Slack, Discord, email, webhooks, and 20+ other platforms. Netdata augments existing workflows rather than forcing a rip-and-replace.

The parent-child streaming architecture scales linearly. Deploy regional Parents near each site to aggregate streams from hundreds of robots. Netdata Cloud provides unified fleet dashboards and distributed queries across all Parents. Adding robots never degrades existing performance — there is no central bottleneck.

No. All metrics and logs stay on your robots and regional Parents. Netdata Cloud receives only metadata — node names, chart definitions, alert configurations — for unified dashboards. For air-gapped or fully on-premises deployments, Netdata Cloud can run inside your datacenter.

Visit our edge monitoring academy page for a detailed explanation of edge-native observability, or explore our edge fleet monitoring use case for architecture patterns specific to distributed fleets.