Better Stack (Log Management)
Cloud-based log management solution for aggregating, searching, and analyzing application logs at scale
Netdata
Instant, per‑second visibility into every infrastructure component.
Netdata delivers per‑second metrics, zero‑config deployment, edge‑based processing, and built‑in ML anomaly detection, giving teams instant insight across servers, containers, and cloud services.
Overview
Overview
Netdata is a real‑time monitoring platform that captures every metric every second, providing developers, SREs, and operations teams with immediate visibility into system health. Its zero‑configuration agent auto‑discovers services, containers, and cloud resources, while edge‑resident ML models continuously learn normal behavior and flag anomalies without external dependencies.
Deployment & Scalability
The agent runs on Linux, Windows, macOS, and embedded devices with minimal CPU and RAM impact, storing data locally using a highly efficient tiered format (~0.5 bytes per sample). Horizontal scaling is achieved through a parent‑child architecture, allowing seamless expansion from a single node to multi‑cloud or IoT fleets. Visualization is available via an interactive UI, and optional Cloud features add centralized alerting and role‑based access without moving raw metrics.
Netdata’s design emphasizes low overhead, instant insights, and extensibility, making it suitable for both small‑scale environments and large, distributed infrastructures.
Highlights
Per‑second data collection with instant visualizations
Zero‑configuration auto‑discovery of services and containers
Edge‑based ML models for unsupervised anomaly detection
Native horizontal scaling for multi‑cloud and IoT environments
Pros
- Provides per‑second granularity for rapid troubleshooting
- Zero‑config setup reduces onboarding time
- Low resource footprint enables deployment on edge devices
- Built‑in ML detects anomalies without manual thresholds
Considerations
- High‑frequency data can increase storage requirements if long‑term retention is needed
- Advanced alerting and centralization may require additional components
- Learning curve for customizing ML models and dashboards
- Limited native query language compared to some alternatives
Managed products teams compare with
When teams consider Netdata, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- DevOps teams that need immediate insight during incidents
- Containerized and Kubernetes environments with dynamic workloads
- Edge or IoT deployments where local processing is essential
- Organizations seeking a low‑overhead, scalable monitoring solution
Not ideal when
- Environments that require a single, centralized time‑series database
- Teams heavily invested in Prometheus‑compatible query languages
- Regulated industries needing strict data residency and audit trails
- Use cases where only static, low‑frequency metrics are sufficient
How teams use it
Production outage investigation
Engineers pinpoint the exact second a resource spike occurred, reducing mean time to resolution.
Capacity planning for microservices
Per‑second usage trends reveal scaling patterns, informing right‑sizing of compute resources.
Anomaly detection in IoT fleets
Edge‑resident ML models automatically alert on sensor drift or hardware failures without central analysis.
Multi‑cloud cost optimization
Unified dashboards compare resource consumption across AWS, GCP, and Azure, highlighting inefficiencies.
Tech snapshot
C66%
Go20%
JavaScript3%
Shell2%
Jupyter Notebook2%
Python2%
Frequently asked questions
What types of metrics does Netdata collect?
It gathers system resources, storage, network, hardware sensors, processes, containers, VMs, logs, synthetic checks, and many packaged applications.
How is Netdata installed?
A single binary or package can be run on the target host; the agent starts automatically and begins monitoring without further configuration.
Does Netdata store data centrally?
By default data is stored locally on each node; optional Cloud or external exporters can forward metrics for centralized alerting.
What is the resource impact of the agent?
The agent is designed for minimal CPU and RAM usage, typically consuming less than 1 % of a modern server’s resources.
Can Netdata integrate with existing monitoring stacks?
Yes, it can export data via Prometheus, OpenMetrics, StatsD, and other protocols for downstream consumption.
Project at a glance
Active- Stars
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LicenseGPL-3.0
Repo age12 years old
Last commit3 hours ago
Primary languageC
Last synced 2 hours ago