Let's take a look at Reference Lines available
from your dashboard in 716.
So, here I have two panels, one with a key metric
and one showing a distribution of another metric.
Let's edit this.
Now, if my organization has a target for
a specific value of this metric,
so say we don't ever wanna egress more than 5 MB or something arbitrary,
we've added this ability on the right-hand side
to add a reference layer,
which will let me draw baselines on this visualization.
If I click the static value, I can enter any value I want.
So, let's say I wanna do instead of this number,
I want 5 MB so, that'd be 5, 1, 2 then a bunch of zeros.
See if we get that right?
Aw, man. First try, that's awesome.
It doesn't always work out that way.
You can edit the display name and do things like
show the display name on the side so, that people know what it is.
And maybe if you don't wanna have it be a value,
you can even say 5 MB and that will make it very clear
what this reference line is all about.
This is a static baseline, which is definitely
a way to put those hard and fast rules out there.
But maybe if I take a clone of this panel,
maybe I wanna pull this value dynamically from
a goal data source or from the data itself.
To do that, I can edit this 5 MB value that I just created
and turn it into a quick function.
Here I can actually pick the percentile
of the field that I'm visualizing so,
I'll pick the host network egress.
And I want the percentile, and now I can see a line
representing the 95th percentile of this metric.
So, maybe I wanna rename this to be 95th.
And this is probably a bad thing for egress.
Maybe if we're gonna charge for egress like some cloud providers do so,
maybe I wanna change the color to red and fill above the line.
So, it's really clear like that.
What's nice about this is you can also clone
and pull in multiple reference lines,
change their colors and have them set up a different statistics.
Different parts so, you can see this one is on the 85th
maybe it's a little bit lower and shows up like that.
So, it's pretty nice, pretty easy.
One other way to use this is you can,
in addition to having these reference layers,
you can add another layer.
So, I'm gonna click here,
and here you can pull from any other data source.
So, maybe I have a goals index out there and
I have a value that's dynamic to that index so,
I can update my goals independently of this
visualization and they'll just update.
Here I'm gonna use the last value operation and take
my network egress target, whatever that is.
So, I think I pick 5 MB in my goals data.
But the cool thing here is updating that single data
source will update all of your visualizations,
and you'll also notice I'm able to use multiple reference lines
from multiple different data views or index patterns.
Let me save this.
The last example I wanna show you,
has to do with using non time based references.
So, this visualization is a distribution of API counts and on its own,
you know, you could tell a lot is not happening on the zero mark,
but it's hard to tell how high is this
number relative to the overall data.
So, one thing I can do is add a reference layer.
And rather than showing a line on the metric axis,
I can delete that and put a line on the data axis.
This can be pretty cool for using something like percentiles again,
because I'm able to – if I say API server request –
pick the same field, and now I can see on the visualization
where the 95th percentile is in the distribution.
And this is really powerful to show me statistics,
show me exactly where in the data,
a high value begins and where the tail is on that distribution.