I wrote my own network latency monitoring agent in Go

For a while I had used Smokeping to generate pretty graphs of network latency between various hosts on my network. The downside with Smokeping was always getting it working. Did I configure my webserver just right? Did I remember to save the webserver configs so that the next time I set this up, things just worked? Did I install all the right Perl modules (and the right versions of each) so that Smokeping’s binary worked? Then there were the differences in operation depending on if I ran it on Linux, OpenBSD, or FreeBSD. There had to be a simpler solution.

I’ve been dabbling in Go and Graphite as side projects at home for a while. Go was a language I’d been wanting to use more given its popularity where I work. Graphite was always this itch I scratched whenever I wanted to visualize machine and network statistics for the various machines on my network. I knew I could come up with a simple solution using these two pieces of tech.

I wanted to start small. Smokeping provides graphs of minimum, maximium, average, and std deviation for round trip times, as well as packet loss. These are all statistics provided by the ping command line tool. Why couldn’t I just wrap ping in a Go binary, and send those data points off to Carbon for graphing in Graphite?

I present the resultant Go binary and library.

parallelping is a Go binary used to ping remote hosts, in parallel. If provided with a Carbon host and port, the data is shipped off to Carbon/Graphite.

carbon-golang is a Go library used to take Carbon metrics and send them off to a Carbon Cache over TCP. I do admit I borrowed a lot of the logic from marpaia/graphite-golang, both because I couldn’t quite get that library to integrate as documented, but also because I wanted the learning experience of building my own Go-based TCP client.

Both of these are my first non-trivial pieces of Go code. The more I spent time with Go the less I felt it’s barrier to entry was as high as anticipated (I’ve been mainly a Python person for many years). Further usage documentation for each bit of code can be found on their respective Github project pages, eventually.

A screenshot so far: