Article: Introducing netdata

Costa Tsaousis edited this page Jan 26, 2016 · 9 revisions


Running Netdata



Netdata Registry

Monitoring Info

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Introducing netdata

Linux, real-time performance monitoring, in the greatest possible detail!

Click here for a live demo of netdata.

The following is an animated GIF showing netdata's ability to monitor QoS. The timings of this animation have not been altered, this is the real thing:


Check the details on this animation:

  1. At the beginning the charts auto-refresh, in real-time
  2. Charts can be dragged and zoomed (either mouse or touch)
  3. You pan or zoom one, the others follow
  4. Mouse over on one, selects the same timestamp on all
  5. Dimensions can be enabled or disabled
  6. All refreshes are instant (and I used an 8 year old core-2 duo computer to record this)

Why another monitoring tool?

There are a lot of excellent open source tools for collecting and visualizing performance metrics. Check for example collectd, OpenTSDB, influxdb, Grafana, etc.

So, why netdata?

Well, netdata has a quite different approach:

The end of console for performance monitoring

Take any performance monitoring solution and try to troubleshoot a performance problem. At the end of the day you will have to ssh to the server to understand what exactly is happening. You will have to use iostat, iotop, vmstat, top, iperf, ethtool and probably a few dozen more console tools to figure it out.

With netdata, this need is eliminated significantly. Of course you will ssh. Just not for monitoring performance.

If you install netdata you will prefer it over the console tools. Netdata visualizes the data, while the console tools just show their values. The detail is the same - I have spent pretty much time reading the source code of the console tools, to figure out what needs to do done in netdata, so that the data, the values, will be the same. Actually, netdata is more precise than most console tools, it will interpolate all collected values to second boundary, so that even if something took a few microseconds more to be collected, netdata will correctly estimate the per second value.

Netdata visualizes data in ways you cannot even imagine on a console. It allows you to see the present in real-time, much like the console tools, but also the recent past, compare different metrics with each other, zoom in to see the recent past in detail, or zoom out to have a helicopter view of what is happening in longer durations, build custom dashboards with just the charts you need for a specific purpose.

Most engineers that install netdata, ssh to the server to tweak system or application settings and at the same time they monitor the result of the new settings in netdata on their browser.

Real-time detail

Any performance monitoring solution that does not go down to per second collection and visualization of the data, is useless. It will make you happy to have it, but it will not help you more than that.

Visualizing the present in real-time and in great detail, is the most important value a performance monitoring solution should provide. The next most important is the last hour, again per second. The next is the last 8 hours and so on, up to a week, or at most a month. In my 20+ years in IT, I needed just once or twice to look a year back. And this was mainly out of curiosity.

Of course real-time monitoring requires resources. netdata is designed to be very efficient:

  1. collecting performance data is a repeating process - you do the same thing again and again. Netdata has been designed to learn from each iteration, so that the next one will be faster. It learns the sizes of files (it even keeps them open when it can), the number of lines and words per line they contain, the sizes of the buffers it needs to process them, etc. It adapts, so that everything will be as ready as possible for the next iteration.
  2. internally, it uses hashes and indexes (b-trees), to speed up lookups of metrics, charts, dimensions, settings.
  3. it has an in-memory round robin database based on a custom floating point number that allows it to pack values and flags together, in 32 bits, to lower its memory footprint.
  4. its internal web server is capable of generating JSON responses from live performance data with speeds comparable to static content delivery (it does not use printf, it is actually 11 times faster than in generating JSON compared to printf).

Netdata will use some CPU and memory, but it will not produce any disk I/O at all, apart its logs (which you can disable if you like).

Most servers should have plenty of CPU resources (I consider a hardware upgrade or application split when a server averages around 40% CPU utilization at the peak hour). Even if a server has limited CPU resources available, you can just lower the data collection frequency of netdata. Going from per second to every 2 seconds data collection, will cut the netdata CPU requirements in half and you will still get charts that are just 2 seconds behind.

The same goes for memory. If you just keep an hour of data (which is perfect for performance troubleshooting), you will most probably need 15-20MB. You can also enable the kernel de-duper (Kernel Same-Page Merging) and netdata will offer to it all its round robin database. KSM can free 20-60% of the memory used by netdata (guess why: there are a lot of metrics that are always zero or just constant).


Most monitoring solutions require endless configuration of whatever imaginable. Well, this is a linux box. Why do we need to configure every single metric we need to monitor. Of course it has a CPU and RAM and a few disks, and ethernet ports, it might run a firewall, a web server, or a database server and so on. Why do we need to configure all these metrics?

Netdata has been designed to auto-detect everything. Of course you can enable, tweak or disable things. But by default, if netdata can retrieve /server-status from an web server you run on your linux box, it will automatically collect all performance metrics. This happens for apache, squid, nginx, mysql, opensips, etc. It will also automatically collect all available system values for CPU, memory, disks, network interfaces, QoS (with labels if you also use FireQOS), etc. Even for applications that do not offer performance metrics, it will automatically group the whole process tree and provide metrics like CPU usage, memory allocated, opened files, sockets, disk activity, swap activity, etc per application group.

Monitoring console

Most solutions require dedicated servers to actually use the monitoring console. To my perspective, this is totally unneeded for performance monitoring. All of us have a spectacular tool on our desktops, that allows us to connect in real time to any server in the world: the web browser. It shouldn't be so hard to use the same tool to connect in real-time to all our servers.

With netdata, there is no need to centralize anything for performance monitoring. You view everything directly from their source.

Still, with netdata you can build dashboards with charts from any number of servers. And these charts will be connected to each other much like the ones that come from the same server. You will hover on one and all of them will show the relative value for the selected timestamp. You will zoom or pan one and all of them will follow. Netdata achieves that because the logic that connects the charts together is at the browser, not the server, so that all charts presented on the same page are connected, no matter where they come from.

The charting libraries netdata uses, are the fastest possible (Dygraphs do make the difference!) and netdata respects browser resources. Data are just rendered on a canvas. No processing in javascript at all.

Server side, chart data generation scales pretty well. You can expect 400+ chart refreshes per second per core on modern hardware. For a page with 10 charts visible (the page may have hundreds, but only the visible are refreshed), just a tiny fraction of a single CPU core will be used for servicing them. Even these refreshes stop when you switch tabs on your browser, you focus on another window, scroll to a part of the page without charts, zoom or pan a chart. And of course the netdata server runs with the lowest possible process priority, so that your production environment, your applications, will not be slowed down by the netdata server.

Is it ready?

Netdata is stable and usable.

There are more things we are willing to add to it, like these:

  • Custom dashboards are now written in HTML (no javascript is required for this, but still you need to know HTML). It would be nice if custom dashboards could be created from the netdata UI itself.
  • The default dashboard should allow us to search for charts, even on multiple servers.
  • Documentation is still a work in progress.
  • Netdata supports data collection plugins in any language, including shell scripting. Shell scripting is inefficient for per second updates, but it is excellent if you want to visualize something immediately and you don't care about the overheads. Netdata shell plugin (called charts.d) uses several techniques to eliminate these overheads, but still shell plugins shipped with netdata should be re-written in a more efficient language (personally, I like a lot node.js - it is perfect for async operations, fast enough for repeating operations where the program is already loaded, it will eliminate a lot of installation dependencies and node.js programs are just javascript source files easy to edit and adapt).
  • Now, the chart data are sent from the netdata server to the client on every refresh. This wastes network resources. It would be perfect if the browser and the server could communicate with a websocket and transfer the data incrementally.
  • Today it is not practical to use netdata with a database longer than 24 hours. It will need a lot of RAM. Its round robin database could be split in 2 parts, one having the last 30-60 minutes and the rest could be compressed with LZ4 (which is amazingly fast). This would allow netdata to lower its memory requirements significantly and possibly be practical to have a week or a month of data in compressed memory mapped files.