Log-Gap Charts for Time Series

Sometimes you want to visualize your time-series data in a chart. Traditionally, this is done by slicing your time-scale into equal-sized bins and counting the events that fall into each one. The big players—Grafana, Datadog, CloudWatch—all do this, handing you a nice, neat histogram of events over time. But binning the data destroys resolution. Choose too large a bin, and you lose time resolution. You completely miss high-density burst events and long idle gaps; it all just averages out into a meaningless block. Choose too small a bin, and you lose aggregate resolution. You end up with hundreds of atomized bins containing zero, one, or two events each, flattening your chart into a needle-bed of noise. If you're lucky, you might find an intermediate bin size that still shows you something marginally interesting on both the count and time axes. But more often than not, there is no reasonable sweet spot. If you're particularly unlucky, a bin boundary will arbitrarily divide a burst…