Building Grafana Dashboards Fueled by Intel Snap

A short while ago I had the pleasure of attending the Intel Cloud Day 2016 event as a storage-focused Tech Field Day delegate. I thought this was pretty groovy of Intel, since I work for a vendor, but they didn’t have an issue with it. And while the event had a laundry list of various announcements across their storage, network, and cloud building practices, I thought the work being done on their open source project named Snap was especially worth sharing here.

Even distribution of Star Trek and Star Wars fans.
Even distribution of Star Trek and Star Wars fans.

Snap is an open telemetry framework that answers the question posed by Nick Weaver in his earlier blog post:

What would an operational framework focused on making the consumption of telemetry much easier look like?

Using a modular design, Snap allows for others to contribute plugins that are focused on collecting, processing, and publishing information elsewhere. Many of the plugins look supremely handy – such as collectors for SMART data from an SSD, Facter, Docker, Ethtool, and publishing to InfluxDB. It’s a slick looking project that I’m definitely planning to deploy into the lab and write about further. For now, I’d suggest reading Matt Brender’s introduction post.

Now that you’re caught up on Snap, let’s dig into the announcements made at Intel Cloud Day. Grafana, an open source dashboard project that I’ve written about here, is making some big moves as Snap’s first GUI with the version 3.0 release. This is a huge deal, and many folks really enjoy using Grafana because it’s lightweight, simple to use, and supports queries to easily add (or remove) data points without having to muck about with ham-fisted tuning.


Grafana Live – which is new to the 3.0 release – allows you to actually push data directly into the dashboard panels, versus having a timed pull. I’d suggest reading the official post from Raintank’s blog for greater details and step-by-step installation instructions. Don’t worry; it’s nerd-a-licious. The short version is that using a telemetry framework that is dynamic and flexible and then coupling the data to a dashboard that is dynamic and flexible results in some data visualization magic that wasn’t possible in the past without some heavy lifting (and certainly not for on-the-fly measurements).

In my next post on this topic, I’ll see about putting together a Snap server and pointing it at my Grafana Home Lab Dashboard. Since all of my lab equipment uses Intel technologies, this should be exciting. 🙂