The new implementation detects the start and end of a series by
looking at the average sample interval within the range. If the first
(last) sample in the range is more than 1.1*interval distant from the
beginning (end) of the range, it is considered the first (last) sample
of the series as a whole, and extrapolation is limited to half the
interval (rather than all the way to the beginning (end) of the
range). In addition, if the extrapolated starting point of a counter
(where it is zero) is within the range, it is used as the starting
point of the series.
Fixes#581
irate is a rate function that only looks at the most
recent two data points, and calucaltes a per-second value
from that. This produces much more granular graphs for
fast moving data, and works sanely across many scrape intervals.
It doesn't do so well for slowly moving data.
Currently the only way to convert a scalar to a vector is to
use absent(), which isn't very clean. This adds a vector()
function that's the inverse of scalar() and lets your optionally
set labels.
Example usage would be
vector(time() % 86400) < 3600
to filter to only the first hour of the day.
This calculates how much a counter increases over
a given period of time, which is the area under the curve
of it's rate.
increase(x[5m]) is equivilent to rate(x[5m]) * 300.
