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How to optimize the Netdata Agent's performance

We designed the Netdata Agent to be incredibly lightweight, even when it's collecting a few thousand dimensions every second and visualizing that data into hundreds of charts. However, the default settings of the Netdata Agent are not optimized for performance, but for a simple, standalone setup. We want the first install to give you something you can run without any configuration. Most of the settings and options are enabled, since we want you to experience the full thing.

By default, Netdata will automatically detect applications running on the node it is installed to start collecting metrics in real-time, has health monitoring enabled to evaluate alerts and trains Machine Learning (ML) models for each metric, to detect anomalies.

This document describes the resources required for the various default capabilities and the strategies to optimize Netdata for production use.

Summary of performance optimizations

The following table summarizes the effect of each optimization on the CPU, RAM and Disk IO utilization in production.

OptimizationCPURAMDisk IO
Use streaming and replication✔️✔️✔️
Disable unneeded plugins or collectors✔️✔️✔️
Reduce data collection frequency✔️✔️
Change how long Netdata stores metrics✔️✔️
Use a different metric storage database✔️✔️
Disable machine learning✔️
Use a reverse proxy✔️
Disable/lower gzip compression for the agent dashboard✔️

Resources required by a default Netdata installation

Netdata's performance is primarily affected by data collection/retention and clients accessing data.

You can configure almost all aspects of data collection/retention, and certain aspects of clients accessing data.

CPU consumption

Expect about:

  • 1-3% of a single core for the netdata core
  • 1-3% of a single core for the various collectors (e.g. go.d.plugin, apps.plugin)
  • 5-10% of a single core, when ML training runs

Your experience may vary depending on the number of metrics collected, the collectors enabled and the specific environment they run on, i.e. the work they have to do to collect these metrics.

As a general rule, for modern hardware and VMs, the total CPU consumption of a standalone Netdata installation, including all its components, should be below 5 - 15% of a single core. For example, on 8 core server it will use only 0.6% - 1.8% of a total CPU capacity, depending on the CPU characteristics.

The Netdata Agent runs with the lowest possible process scheduling policy, which is nice 19, and uses the idle process scheduler. Together, these settings ensure that the Agent only gets CPU resources when the node has CPU resources to space. If the node reaches 100% CPU utilization, the Agent is stopped first to ensure your applications get any available resources.

To reduce CPU usage you can (either one or a combination of the following actions):

  1. Disable machine learning,
  2. Use streaming and replication,
  3. Reduce the data collection frequency
  4. Disable unneeded plugins or collectors
  5. Use a reverse proxy,
  6. Disable/lower gzip compression for the agent dashboard.

Memory consumption

The memory footprint of Netdata is mainly influenced by the number of metrics concurrently being collected. Expect about 150MB of RAM for a typical 64-bit server collecting about 2000 to 3000 metrics.

To estimate and control memory consumption, you can (either one or a combination of the following actions):

  1. Disable unneeded plugins or collectors
  2. Change how long Netdata stores metrics
  3. Use a different metric storage database.

Disk footprint and I/O

By default, Netdata should not use more than 1GB of disk space, most of which is dedicated for storing metric data and metadata. For typical installations collecting 2000 - 3000 metrics, this storage should provide a few days of high-resolution retention (per second), about a month of mid-resolution retention (per minute) and more than a year of low-resolution retention (per hour).

Netdata spreads I/O operations across time. For typical standalone installations there should be a few write operations every 5-10 seconds of a few kilobytes each, occasionally up to 1MB. In addition, under heavy load, collectors that require disk I/O may stop and show gaps in charts.

To optimize your disk footprint in any aspect described below you can:

To configure retention, you can:

  1. Change how long Netdata stores metrics.

To control disk I/O:

  1. Use a different metric storage database,

Minimize deployment impact on the production system by optimizing disk footprint:

  1. Using streaming and replication
  2. Reduce the data collection frequency
  3. Disable unneeded plugins or collectors.

Use streaming and replication

For all production environments, parent Netdata nodes outside the production infrastructure should be receiving all collected data from children Netdata nodes running on the production infrastructure, using streaming and replication.

Disable health checks on the child nodes

When you set up streaming, we recommend you run your health checks on the parent. This saves resources on the children and makes it easier to configure or disable alerts and agent notifications.

The parents by default run health checks for each child, as long as the child is connected (the details are in stream.conf). On the child nodes you should add to netdata.conf the following:

enabled = no

Use memory mode ram for the child nodes

See using a different metric storage database.

Disable unneeded plugins or collectors

If you know that you don't need an entire plugin or a specific collector, you can disable any of them. Keep in mind that if a plugin/collector has nothing to do, it simply shuts down and does not consume system resources. You will only improve the Agent's performance by disabling plugins/collectors that are actively collecting metrics.

Open netdata.conf and scroll down to the [plugins] section. To disable any plugin, uncomment it and set the value to no. For example, to explicitly keep the proc and go.d plugins enabled while disabling python.d and charts.d.

proc = yes
python.d = no
charts.d = no
go.d = yes

Disable specific collectors by opening their respective plugin configuration files, uncommenting the line for the collector, and setting its value to no.

sudo ./edit-config go.d.conf
sudo ./edit-config python.d.conf
sudo ./edit-config charts.d.conf

For example, to disable a few Python collectors:

apache: no
dockerd: no
fail2ban: no

Reduce collection frequency

The fastest way to improve the Agent's resource utilization is to reduce how often it collects metrics.


If you don't need per-second metrics, or if the Netdata Agent uses a lot of CPU even when no one is viewing that node's dashboard, configure the Agent to collect metrics less often.

Open netdata.conf and edit the update every setting. The default is 1, meaning that the Agent collects metrics every second.

If you change this to 2, Netdata enforces a minimum update every setting of 2 seconds, and collects metrics every other second, which will effectively halve CPU utilization. Set this to 5 or 10 to collect metrics every 5 or 10 seconds, respectively.

update every = 5

Specific plugin or collector

Every collector and plugin has its own update every setting, which you can also change in the go.d.conf, python.d.conf, or charts.d.conf files, or in individual collector configuration files. If the update every for an individual collector is less than the global, the Netdata Agent uses the global setting. See the collectors configuration reference for details.

To reduce the frequency of an internal_plugin/collector, open netdata.conf and find the appropriate section. For example, to reduce the frequency of the apps plugin, which collects and visualizes metrics on application resource utilization:

update every = 5

To configure an individual collector, open its specific configuration file with edit-config and look for the update_every setting. For example, to reduce the frequency of the nginx collector, run sudo ./edit-config go.d/nginx.conf:

# [ GLOBAL ]
update_every: 10

Lower memory usage for metrics retention

See how to change how long Netdata stores metrics.

Use a different metric storage database

Consider using a different metric storage database when running Netdata on IoT devices, and for children in a parent-child set up based on streaming and replication.

Disable machine learning

Automated anomaly detection may be a powerful tool, but we recommend it to only be enabled on Netdata parents that sit outside your production infrastructure, or if you have cpu and memory to spare. You can disable ML with the following:

enabled = no

Run Netdata behind a proxy

A dedicated web server like nginx provides more robustness than the Agent's internal web server. Nginx can handle more concurrent connections, reuse idle connections, and use fast gzip compression to reduce payloads.

For details on installing another web server as a proxy for the local Agent dashboard, see reverse proxies.

Disable/lower gzip compression for the dashboard

If you choose not to run the Agent behind Nginx, you can disable or lower the Agent's web server's gzip compression. While gzip compression does reduce the size of the HTML/CSS/JS payload, it does use additional CPU while a user is looking at the local Agent dashboard.

To disable gzip compression, open netdata.conf and find the [web] section:

enable gzip compression = no

Or to lower the default compression level:

enable gzip compression = yes
gzip compression level = 1

Do you have any feedback for this page? If so, you can open a new issue on our netdata/learn repository.