obfuscurity.
hidden in plain sight

In the process of setting up some graphs for Status Board, I thought it would be nice to render my GitHub activity (in terms of commits). As I demonstrated in a post last year, you can fire off a metric to Graphite using GitHub's post-commit webhook feature. Rendered with drawAsInfinite, this is nice for getting a rough visualization of your commit activity, but doesn't provide total counts. Alternatively, you could use group with summarize to get totals per interval, but you wouldn't be able to view per-repository numbers.

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I was recently cold-emailed about a new service, Catincan, that offers a Kickstarter-like bounty system for open source software projects or features. Someone representing the company reached out to me (and presumably, many others in the open source community) for feedback, generally about the funding of open source development, and specifically about their own service.

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You say you want to contribute to an Open Source project, but you're not sure where to start? Have an interest in monitoring, trending or logging software? Hop on over to the Monitorama Hackathon issues list and take a look around. In the weeks leading up to the event we seeded the repo with a bunch of tasks/feature requests/bug reports that are easily digestible over the course of a day or two. These are a great place to get started on a new project, or nail out some quick issues that have an immediate impact.

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Last year I gave examples for using drawAsInfinite to help visualize the frequency of particular events (deploys, commits, etc). One of the side effects that I failed to mention is that these will quickly fill up your legend with labels, making it impossible to view the legend at all. It's likely that you've seen this sort of thing at least once (assuming you forced hideLegend=false):

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I was looking at some internal data for @jnunemaker and @jfryman today when I stumbled across the Data Filters group of functions inside the Graphite composer. These functions are handy for those times when you want to exclude a subset of a particular series of data, for whatever reason. In our case, we were looking at some metrics where we had spikes of data that were interesting, and a lot of uninteresting data reported as zeroes.

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