Impact of Running Netdata on Cloud Provided VMs

Overview

Netdata provides real-time performance monitoring and troubleshooting capabilities for your systems, offering unparalleled insights with minimal resource consumption. This document highlights the baseline impact of running Netdata on an empty cloud provider (AWS, GCP, Azure, etc.) Virtual Machine (VM), which serves as a reference for understanding the performance and resource usage of Netdata in a production environment.

The resources used by Netdata depend primarily on the number of metrics collected (which may vary significantly among servers) and the features enabled (e.g., streaming to Netdata Parents, Machine Learning). However, Netdata has been designed to be significantly more efficient compared to other observability agents. Despite collecting, storing, and visualizing data in real-time with per-second granularity, Netdata is lighter and more efficient than many commercial and open-source alternatives.

Baseline Configuration on an Empty VM

When deployed on an empty VM, Netdata collects and visualizes critical system metrics with exceptional granularity and efficiency. Below is an overview of its capabilities and resource consumption:

Features and Capabilities

Comprehensive Monitoring

• Over 2,000 unique time-series, including metrics for:
  • CPU, memory, disks, mount points, and filesystems.
  • Network interfaces and the entire networking stack (all protocols, firewall).
  • Containers, processes, users, user groups, and systemd units.
  • All kernel technologies utilized.
• Data is collected and visualized with 1-second granularity, ensuring no performance detail is missed.

Health Alerts

• 350 Unique Alerts ready to run, with about 50+ actively monitoring system components for common errors, misconfigurations, and issues across all monitored components.

Logs Explorer

• Systemd-Journal Integration: Query and visualize system and application logs without requiring an external logs database server.

Network Explorer

• Analyze and visualize TCP and UDP network connections, including connections from individual processes and containers.

Machine Learning and Unsupervised Anomaly Detection

• Real-Time Anomaly Detection: 18 machine learning models trained per time-series to identify and flag outliers based on behavioral trends over the last few days.

Resource Consumption

Netdata operates with an exceptionally low footprint, even under demanding conditions. On an empty VM, the resource usage is as follows:

• CPU Usage: 1%-5% of a single core with default settings, depending on machine learning and streaming to a Parent — see CPU Utilization for details. Rare spikes up to 20% during data flushes (once every 15–20 minutes).
• Memory Usage: 100MB-200MB of RAM, depending on the number of metrics collected and machine learning — see RAM Utilization for details.
• Disk I/O:
  • Reads: ~2 KiB/s without machine learning, ~9 KiB/s with machine learning.
  • Writes: ~5 KiB/s.
• Storage: ~4 GiB total (3 GiB metrics + metadata), within configurable per-tier size and time limits. See Disk Requirements & Retention for defaults and sizing guidance.

Typical Netdata Resources Usage on Production Systems

In production systems with more data sources and features enabled, users can expect:

• CPU Usage: 5%-20% of a single core.
• Memory Usage: 250–350 MB RAM.
• Disk I/O: ~10 KiB/s reads and writes.
• Storage: Same as baseline, ~4 GiB total — see Storage above; storage scales with retention settings, not workload.

Key Takeaways

The baseline impact of running Netdata on an empty VM can be summarized as follows:

1. Minimal Resource Utilization:

   • The CPU, memory, and disk I/O impact is negligible compared to the resources typically provisioned on cloud VMs.

2. Scalable Retention:

   • Netdata efficiently uses disk space to retain high-resolution and long-term data without requiring additional storage or databases.

Recommended VM Sizing

When choosing a VM size for Netdata on a cloud provider, what you need to provision depends on how you use it:

• A single Agent monitoring the instance it runs on has the small footprint described in Resource Consumption and Typical Netdata Resources Usage on Production Systems above. Most general-purpose VM sizes are more than enough.
• A Netdata Parent that receives streams from many Child nodes needs more. Its resource use scales with the number of metrics collected and how long you keep them, so size the VM for your expected metric volume rather than for a single Agent.

For detailed sizing guidance, see:

• Resource utilization: CPU, RAM, disk, and bandwidth requirements for a standalone Agent.
• Parent Configuration Best Practices: sizing and configuration guidance for Parent nodes receiving streams.

Recommendations

To ensure optimal performance and scalability, consider the following when deploying Netdata on cloud VMs:

• Retention Policies: Adjust retention settings to match your specific needs and storage availability.
• Alert Fine-Tuning: Customize alerts based on the workload and environment to reduce noise and increase actionable insights.
• Scaling: For high-workload environments or fleets of many nodes, see Recommended VM Sizing above for Parent sizing guidance, and consider Netdata Cloud to aggregate and analyze data across multiple Parents.

Independent Reviews

In December 2023, the University of Amsterdam published a study on the impact of monitoring tools for Docker-based systems, focusing on:

• The impact of monitoring tools on the energy efficiency of Docker-based systems.
• The impact of monitoring tools on the performance of Docker-based systems.

Key findings include:

• Netdata is the most efficient agent, requiring significantly fewer system resources than others.
• Netdata has minimal performance impact, allowing containers and applications to run without measurable degradation due to observability.

Full analysis here: Twitter Link

Comparisons with Other Commercial Observability Agents

Resource	Dynatrace	Datadog	Instana	Grafana	Netdata
Resolution	1-minute	15-sec	1-sec	1-minute	1-sec
CPU Usage (100% = 1 core)	12%	14%	6.7%	3.3%	3.6%
Memory Usage	1400 MB	972 MB	588 MB	414 MB	181 MB
Disk Space	2 GB	1.2 GB	0.2 GB	-	3 GB
Disk Read Rate	-	0.2 KB/s	-	-	0.3 KB/s
Disk Write Rate	38.6 KB/s	8.3 KB/s	-	1.6 KB/s	4.8 KB/s
Egress Bandwidth	11.4 GB/mo	11.1 GB/mo	5.4 GB/mo	4.8 GB/mo	0.01 GB/mo

Note: Netdata does not stream metric samples to Netdata Cloud. Egress bandwidth for Netdata reflects only user-driven queries. When streaming metrics to a Netdata Parent, bandwidth requirements are similar to other tools, but this traffic typically remains within the local network.

Conclusion

Netdata's resource footprint on cloud VMs is small enough that sizing for it is rarely the deciding factor when choosing an instance type — see Recommended VM Sizing above for what to provision. For workload-specific figures, see CPU, RAM, and Disk Requirements & Retention.

For additional information, please visit Netdata Documentation.