See What Matters, Ignore the Noise

ML anomaly detection and alerts are separate but complementary signals in Netdata. Alerts evaluate conditions you define (thresholds, expressions), while ML anomaly detection identifies unusual behavior based on learned patterns. The 18-model consensus achieves 99% false positive reduction in anomaly detection specifically. During investigation, both signals help - alerts tell you what threshold was crossed, anomalies show unusual patterns that may not have triggered alerts yet. They work together but are evaluated independently.

Traditional monitoring provides infrastructure-level alerts like “Disk space low on server-prod-01” without specifying which disk. Netdata provides component-level precision like “Disk /data at 95% on server-prod-01, will fill in 4 hours” - exact mount point, exact server, clear timeline. This applies to all resources - per-disk, per-interface, per-container, per-database instance - eliminating investigation guesswork during incidents.

No. Netdata’s 400+ alert templates auto-apply to discovered services instantly. Install Netdata, and within 60 seconds you have production-ready alerts for CPU, memory, disks, network, databases, web services, containers, and Kubernetes components. Configuration is only needed for services requiring authentication (database credentials) or custom application-specific thresholds - typically 5% of use cases.

Netdata’s edge-native architecture evaluates alerts on each monitored node, not a central server. Alerts work during network partitions, cloud outages, or connectivity problems. Local notifications (email, scripts) execute without network dependency. When connectivity returns, alert transitions stream to Cloud for deduplication and centralized routing - but local alerting never stops working.

Yes. Netdata supports 29 native integrations including PagerDuty, Opsgenie, Slack, Teams, Discord, SMS (Twilio, MessageBird), email, webhooks, and custom scripts. Configure severity-based routing (critical→PagerDuty, warning→Slack), role-based distribution (DBA team, web team), and multi-channel fanout. Cloud provides additional deduplication across 100+ agents reporting the same issue.

Component-level alerts eliminate the “which one?” question during incidents. Instead of “high disk usage on server-prod-01” requiring you to SSH in and check each mount point, you get “disk /var/log at 92% on server-prod-01.” This precision enables parallel triage - different team members can investigate different components simultaneously, and you know exactly where to look first.

Prometheus requires manual PromQL alert rules (limited out-of-box), centralized evaluation on Prometheus server, and external Alertmanager for routing. Netdata provides 400+ pre-configured alerts, edge-native evaluation (distributed, no central bottleneck), and integrated notification routing - all working in 60 seconds without query language expertise. Many teams use both - Netdata for infrastructure basics, Prometheus for custom application metrics.

Netdata collects metrics every 1 second and evaluates alerts in real-time at the source. Total latency from issue occurrence to notification is sub-2-seconds (worst case). This is 10-60× faster than traditional minute-based monitoring, enabling detection of transient issues, microbursts, and cascading failures that averaged data hides completely.

Yes. Netdata’s template system allows customization without starting from scratch. Adjust thresholds, evaluation windows, hysteresis values, and notification delays via simple YAML/INI configuration. Configure role-based routing (different teams, different channels), severity-based escalation (warning→Slack, critical→PagerDuty), and maintenance window silencing. Changes sync via Cloud or configuration management tools (Ansible, Terraform).

Cloud-level deduplication consolidates alerts across multiple agents. If 100 agents report the same issue (e.g., parent failure affecting children), Cloud identifies same alert name + instance + node, selects highest severity, and sends 1 notification instead of 100. Flood protection detects alert storms (>100 transitions/hour) and sends single summary notification. This prevents notification overload during infrastructure-wide incidents.

Netdata’s auto-discovery automatically applies alert templates to new instances. Add a disk - disk space alert applies automatically. Launch 10 containers - 10 container memory alerts appear instantly. Deploy Kubernetes - K8s component alerts activate immediately. No manual per-host configuration required. Alert coverage scales automatically as infrastructure grows, eliminating blind spots during expansion.

When an alert fires, Anomaly Advisor correlates metrics across your infrastructure, ranking thousands of metrics by how much they deviated during the alert timeframe. Root cause typically appears in the top 30-50 results. It reveals cascading failure sequences (which component failed first), blast radius (what else was affected), and time-synchronized correlation - transforming investigation from hours of manual correlation to seconds of guided analysis.

Yes. Netdata supports custom script execution when alerts fire, enabling automated remediation at the edge. Examples - restart service when API endpoint fails, scale containers when memory threshold reached, rotate logs when disk fills. Scripts execute locally without network dependency, providing immediate response during incidents. Combine with webhooks for integration with external automation platforms (Ansible Tower, Jenkins, custom orchestration).