See Every Millisecond That Matters
Traditional APM tools sample data and miss critical events. Netdata captures every metric every second with ML-powered anomaly detection that achieves 99% false positive reduction while cutting costs by 90%.

Traditional APM tools sample data and miss critical events. Netdata captures every metric every second with ML-powered anomaly detection that achieves 99% false positive reduction while cutting costs by 90%.

The only monitoring platform that combines per-second visibility, edge-native ML, and zero-configuration deployment
Per-second metrics and ML-powered Anomaly Advisor surface root causes in the top 30-50 results, eliminating hours of manual investigation
18-model ML consensus mechanism achieves 99% false positive reduction in anomaly detection while catching real issues other tools miss
Per-node pricing with unlimited metrics, logs, and users replaces expensive volume-based APM at a fraction of the cost
Zero-configuration deployment with automatic service discovery and algorithmic dashboards delivers immediate value
Per-second granularity captures microbursts and transient issues that 30-second monitoring completely misses
Natural language queries and automated root cause analysis accelerate incident response for teams of any skill level
Trusted by DevOps teams worldwide
10-60× more granular than traditional APM
Learn about real-time monitoring

18-model ML consensus
Explore ML anomaly detection

80% MTTR reduction
See root cause analysis

60 seconds to value
View quick start guide

90% cost savings vs traditional APM
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Console replacement with history
Explore Netdata Functions

How Netdata Compares
See how Netdata’s edge-native architecture delivers superior performance monitoring at a fraction of traditional APM costs
Capability
Netdata
Traditional APM
Data Granularity
✅ Per-Second
Captures every metric every second
⚠️ 15-60 Seconds
Misses 90% of transient issues
Sample Completeness
✅ 100% Fidelity
Zero sampling, no data loss
⚠️ 85-95% Sampled
Critical traces often dropped
Anomaly Detection
✅ 18-Model ML
99% false positive reduction
⚠️ Single Model
High false positive rates
Setup Time
✅ 60 Seconds
Zero configuration required
⚠️ Days to Weeks
Extensive manual setup
Query Language
✅ None Required
Point-and-click NIDL framework
⚠️ PromQL/NRQL/SPL
Steep learning curve
Root Cause Analysis
✅ Automated
Top 30-50 results via ML
⚠️ Manual
Hours of investigation
Data Sovereignty
✅ 100% On-Premises
Zero metric data in cloud
❌ Cloud SaaS
All data centralized
Cost Model
✅ Per-Node Fixed
Predictable, no volume charges
❌ Volume-Based
Surprise bills common
Cost Comparison
✅ 90% Lower
Transparent P90 billing
❌ Premium Pricing
Plus volume charges
Agent Overhead
✅ <5% CPU
150-200MB RAM with ML
⚠️ 10-20% CPU
Higher resource usage
High Cardinality
✅ Unlimited
Edge processing eliminates limits
⚠️ Limited
Backends drop attributes
Kubernetes Support
✅ Native
Per-second container metrics
⚠️ Challenging
40% cite as top issue
Traditional APM centralizes data for analysis, creating bottlenecks and latency. Netdata trains 18 ML models per metric directly on each monitored system, enabling real-time anomaly detection with consensus-based accuracy that achieves 99% false positive reduction.
99% false positive reduction
Learn about ML architecture
Monitor every layer of your application stack with per-second precision
CPU, memory, disk, network with per-second granularity across servers, VMs, and containers
Per-container resource tracking with automatic Kubernetes and Docker discovery
Zero-pipeline log management via systemd-journal with 200× more accurate analysis
Real-time visibility into active connections, bandwidth, and connection states
Per-process CPU, memory, I/O with automatic service grouping and classification
Query performance, connection pools, and resource usage for major databases
Request rates, response times, and error tracking for NGINX, Apache, IIS
18-model consensus on every metric achieving 99% false positive reduction
Automated correlation engine surfaces root causes in top 30-50 results

December 1, 2025
The industry says 'monitor everything' is bad. But the same industry keeps discovering monitoring gaps during outages. What's really going on?

September 23, 2025
Shift from reactive troubleshooting to proactive intelligence. Schedule weekly health checks, monthly optimization reports, and custom analyses to be delivered automatically.

September 2, 2025
Our AI investigations and insights are now out of preview. Every space can scale on-demand with AI Credits.