Scale Infrastructure and Insights Simultaneously

Netdata distributes the code, instead of centralizing the data. Each agent is a complete monitoring system (collection, storage, ML, alerts, dashboards) operating autonomously. Adding 1,000 nodes means adding 1,000 independent monitoring systems working in parallel—not 1,000 data streams overwhelming a central database. This architectural inversion eliminates bottlenecks that plague centralized platforms.

Through distributed processing and storage efficiency. Each agent collects and stores its own metrics locally using industry-leading compression (0.6 bytes/sample). Queries distribute in parallel across agents/parents—adding nodes increases aggregate query power. Our benchmark at 4.6M metrics/sec proved 36% less CPU, 88% less RAM, 16× faster queries versus Prometheus while maintaining 100% sample completeness.

Deploy more parent clusters horizontally. Each cluster handles ~500 nodes (2M metrics/sec) with 20 cores and 80GB RAM. For 5,000 nodes, deploy 10 independent clusters. Netdata Cloud provides unified interface—queries distribute in parallel, dashboards aggregate results. No complex sharding, no cross-cluster coordination, no practical limit to horizontal scaling.

Three mechanisms: (1) Automated protection triggers during database rotation when contexts exceed thresholds—intelligently cleans up stale time series, (2) Distributed processing means each agent handles its own cardinality independently—explosions can’t cascade, (3) Three-tier storage with automatic downsampling happens in parallel during collection—no manual recording rules required.

The opposite is true. Netdata delivers 90% cost reduction compared to traditional platforms through predictable per-node pricing with unlimited metrics, logs, and users. Edge-native processing means compute/storage happens on infrastructure you already own. Storage efficiency (0.6 bytes/sample) enables years of retention in gigabytes.

Days, not months. Zero-config discovery automatically detects infrastructure. Algorithmic dashboards generate based on collected data. ML trains automatically within 15 minutes. Over 400 pre-configured alerts work out-of-the-box. Complete enterprise deployment achievable in days using standard provisioning tools (Ansible, Terraform, Helm).

Minimal—agents are self-maintaining. Updates via kickstart script or provisioning tools. Configuration management via standard DevOps practices. Unlike traditional systems requiring dedicated operations teams, Netdata designed for set-and-forget operation. Write-once storage eliminates compaction, ML trains automatically, dashboards generate algorithmically.

Yes. Common patterns: (1) Parallel operation—run Netdata alongside current tools for comparison, export Netdata data to existing systems, (2) Progressive migration—start with non-critical systems, expand as confidence grows, (3) Complementary deployment—use Netdata for infrastructure metrics, keep existing APM for application traces. Supports OpenTelemetry, Prometheus exporters, StatsD, 800+ integrations.

Architecture eliminates sampling need: (1) Local collection—each agent collects/stores its own metrics, no central ingestion pipeline to overwhelm, (2) Local buffering—agents retain data during parent downtime, automatically replay when reconnected, (3) Active-active clustering—multiple parents receive same data for redundancy, (4) Compression efficiency—0.6 bytes/sample means storage costs don’t force sampling decisions.

Minimal. Design philosophy: automation over administration. Zero-config dashboards, automated ML training, intelligent cardinality protection, no query languages required. Configuration: set retention preferences, provide credentials for protected endpoints, configure parent-child relationships. Maintenance: monitor parent resource usage, scale horizontally when approaching limits.

Linearly with volume discounts. Predictable per-node pricing with discounts as you scale. Annual commitment provides additional savings. No per-metric charges, no per-GB log charges, no surprise bills. Contact sales for enterprise pricing beyond 500 nodes.

Architecture proven to 100,000+ nodes. Deployments range from hundreds to thousands of nodes across diverse organizations. Key point: distributed design means 100,000 nodes isn’t fundamentally different from 1,000 nodes—just more parent clusters. Linear scalability by design.

Four mechanisms: (1) Distributed queries—Cloud distributes to all agents/parents in parallel, each processes locally and returns results, (2) Edge processing—aggregations happen where data lives, only results travel network, (3) Multi-tier caching—accelerates repeated queries, (4) Columnar storage—specialized DBENGINE maintains consistent performance regardless of cardinality. Benchmark: 0.11s average at 4.6M metrics/sec.

No architectural limit. Current proven scale: 100,000+ nodes. Theoretical: millions possible through horizontal parent scaling. Each parent cluster handles ~500 nodes—just add more clusters. Netdata Cloud provides unified interface regardless of parent count. Practical limits are organizational, not technological.

Netdata requires no migration as you scale—same architecture from 1 to 100,000+ nodes. Prometheus users hit limits requiring Thanos/Cortex/Mimir migration (multi-month projects). Our benchmark at 4.6M metrics/sec: 36% less CPU, 88% less RAM, 97% less disk I/O, 16× faster queries versus Prometheus. No manual recording rules, no federation complexity. Deploy in days, scale for years.