HPC Monitoring & ObservabilityTraditional monitoring misses 90% of HPC incidents because they happen in seconds, not minutes. Netdata’s per-second granularity captures GPU throttling, memory bursts, and network microbursts as they occur - giving your team the visibility to prevent cascading failures before they impact research outcomes.
Six capabilities that transform HPC operations
Sub-2-second latency from event to insight. Capture GPU throttling, memory spikes, and network bursts that 30-second monitoring completely misses.
18 models per metric achieve 99% false positive reduction. Automatically correlate anomalies across thousands of metrics to surface root causes in seconds.
Zero configuration required. Auto-discovers GPUs, InfiniBand, containers, and jobs. Algorithmic dashboards generate instantly - no PromQL, no manual setup.
Process data where it’s generated. Linear scalability to 100,000+ nodes with <5% CPU overhead. No centralized bottlenecks, no data egress costs.
Predictable per-node pricing with unlimited metrics, logs, and users. Industry-leading 0.6 bytes/sample compression delivers 15× longer retention than alternatives.
SOC 2 Type 2 certified with data sovereignty by design. NIST-aligned multi-zone architecture keeps sensitive research data on-premises.
Trusted by research institutions and HPC centers worldwide
16× faster queries than Prometheus
See Real-Time Performance
99% false positive reduction in anomaly detection
Explore ML Capabilities
Multi-vendor GPU support
View GPU Monitoring
Native RoCE/RDMA monitoring
Learn About Network Monitoring
Per-second job-level metrics
See Job Monitoring
Console replacement
Explore Netdata Functions
Why HPC Teams Choose Netdata
Traditional monitoring tools were designed for enterprise IT - not the microsecond-level precision and extreme scale of HPC environments. See how Netdata’s purpose-built architecture delivers what research computing demands.
Capability
Netdata
Traditional Monitoring
Data Granularity
Time resolution for metric collection
✅ Per-Second
Captures transient GPU throttling and memory spikes
⚠️ Per-Minute
Misses 90% of HPC incidents under 10 seconds
Total Latency
Event to insight visibility
✅ Sub-2 Seconds
Interactive troubleshooting during live incidents
❌ 30-120 Seconds
Delayed visibility prevents rapid response
GPU Monitoring
Multi-vendor accelerator support
✅ DCGM-Free
Avoids production failures via nvidia-smi direct
⚠️ DCGM-Dependent
Inherits connection failures and MIG issues
InfiniBand Visibility
High-speed interconnect monitoring
✅ Native RoCE/RDMA
Hardware counters for congestion and errors
❌ Limited or None
Kernel bypass prevents standard monitoring
Job-Level Metrics
Per-job resource tracking
✅ Native Cgroups
Automatic per-second CPU, memory, I/O, network
⚠️ Manual Integration
Requires separate exporters and correlation
ML Anomaly Detection
Automated issue identification
✅ 18-Model Consensus
99% false positive reduction in anomaly detection
⚠️ Basic or None
Manual threshold tuning or external ML required
Configuration Required
Time to operational monitoring
✅ Zero Config
Auto-discovery, algorithmic dashboards, 60 seconds
❌ Extensive Setup
Manual exporters, dashboard building, days to weeks
Storage Efficiency
Bytes per metric sample
✅ 0.6 Bytes/Sample
15× longer retention on same disk
⚠️ 2-16 Bytes/Sample
Higher storage costs, shorter retention
Scalability Model
Performance at 10,000+ nodes
✅ Linear Scaling
Proven 100,000+ nodes, distributed architecture
⚠️ Federation Required
Complex clustering, performance degradation
Pricing Model
Cost structure and predictability
✅ Predictable Per-Node
Flat rate, unlimited metrics, logs, users
❌ Volume-Based
Per-metric charges, unpredictable bills
Monitor NVIDIA, AMD, and Intel GPUs with per-second granularity. Capture utilization, memory, temperature, power, PCIe bandwidth, and thermal throttling events - without DCGM connection failures or MIG incompatibility issues.
DCGM-free reliability
Explore GPU MonitoringPurpose-built capabilities that transform HPC operations
Per-second granularity reveals GPU throttling, memory spikes, and network bursts that minute-based monitoring completely misses - critical for understanding cascading failures.
18-model ML consensus achieves 99% false positive reduction in anomaly detection. Anomaly Advisor automatically correlates anomalies across thousands of metrics to surface root causes.
Zero configuration required. Auto-discovers infrastructure, generates algorithmic dashboards, and starts ML training automatically - operational visibility in one minute.
Distributed edge-native architecture scales linearly to 100,000+ nodes with <5% CPU overhead. No centralized bottlenecks, no architectural rewrites as you grow.
Predictable per-node pricing with unlimited metrics, logs, and users. Industry-leading compression delivers 15× longer retention - 90% cost reduction versus commercial alternatives.
SOC 2 Type 2 certified with data sovereignty by design. NIST-aligned multi-zone architecture keeps sensitive research data on-premises where it belongs.
Native monitoring of RoCE/RDMA operations, congestion notifications, and hardware errors - visibility that kernel bypass prevents standard tools from capturing.
Automatic anomaly correlation across infrastructure and jobs. Reveals cascading failure sequences and blast radius - 80% MTTR reduction through rapid root cause identification.
Browser-based access to processes, network connections, logs, and I/O - all with history and ML anomaly detection. Secure troubleshooting without SSH access.
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