Blog

We're improving documentation for metrics exposed by metrictank with the metrics2docs tool.

Meta tags are coming soon for Metrictank. Here's how to use them.

Coming Soon: Seamless and Cost-Effective Meta Tags for Metrictank One of the major projects we’re working on for Metrictank – our large scale Graphite solution – is the meta tags feature, which we started last year and are targeting to release in a few months. A lot of people don’t realize this, but Graphite has had tag support for more than a year. Our mission with Metrictank is to provide a more scalable version of Graphite, so introducing meta tags was a logical next step.

This summer I had the opportunity to present my practical fault detection concepts and hands-on approach as conference presentations. First at Velocity and then at SRECon16 Europe. The latter page also contains the recorded video. If you’re interested at all in tackling non-trivial timeseries alerting use cases (e.g. working with seasonal or trending data) this video should be useful to you. It’s basically me trying to convey in a concrete way why I think the big-data and math-centered algorithmic approaches come with a variety of problems making them unrealistic and unfit, whereas the real breakthroughs happen when tools recognize the symbiotic relationship between operators and software, and focus on supporting a collaborative, iterative process to managing alerting over time.

For several years I’ve worked with Graphite, Grafana and statsd on a daily basis and have been participating in the community. All three are fantastic tools and solve very real problems. Hence my continued use and recommendation. However, between colleagues, random folks on irc, and personal experience, I’ve seen a plethora of often subtle issues, gotchas and insights, which today I’d like to share. I hope this will prove useful to users while we, open source monitoring developers, work on ironing out these kinks.

A while back I read coders at work, which is a book of interviews with some great computer scientists who earned their stripes, the questions just as thoughtful as the answers. For one thing, it re-ignited my interest in functional programming, for another I got interested in literate programming but most of all, it struck me how common of a recommendation it was to read other people’s code as a means to become a better programmer.