Hi everyone, I'm Gil Tene.

I'm going to be talking about this subject
that I call "How NOT to Measure Latency".

It's a subject that I've been talking
about for 3 years or so.

I keep the title and change all
the slides every time.

A bunch of this stuff is new.

So if you've seen any of my previous "How NOT to",
you'll see only some things that are common.

A nickname for the subject is this...

Because I often will get that reaction
from some people in the audience.

Ever since I've told people that it's a
nickname,

They feel free to actually exclaim,
"Oh S@%#!".

And feel free to do that here in this talk.

I'll prompt you in a couple of places
where it is natural.

But if just have the urge, go ahead.

So just a tiny bit about me.

I am the co-founder of Azul Systems.

I play around with garbage collection a lot.

Here is some evidence of me playing around
with garbage collection in my kitchen.

That's a trash compactor.

The compaction function wasn't working right,
so I had to fix it.

I thought it'd be funny to take a picture
with a book.

I've also built a lot of things.

I've been playing with computers since
the early 80's.

I've built hardware.

I've helped design chips.

I've built software at many 
different levels.

Operating systems, drivers...
JVM's obviously.

And lots of big systems at the system level.

Built our own app server in the late 90's
because web logic wasn't around yet.

So, I've made a lot of mistakes,
and I've learned from a few of them.

This is actually a combination of a bunch
of those mistakes looking at latency.

I do have this hobby of depressing people
by pulling the wool up from over your eyes,

and this is what this talk is about.

So, I need to give you a choice right here.

There's the door.

You can take the blue pill, 
and you can leave.

Tomorrow you can keep believing whatever
it is you want to believe.

But if you stay here and take the red pill, 
I will show you a glimpse of how

far down the rabbit hole goes, 
and it will never be the same again.

Let's talk about latency.

And when I say latency, I'm talking about
latency response time, any of those things

where you measure time from 'here to here',
and you're interested in how long it took.

We do this all the time, but I see a lot 
of mish-mash in how people

treat the data, or think about it.

Latency is basically the time it took
something to happen once.

That one time, how long did it take.

And when we measure stuff, like we did 
a million operations in the last hour,

we have a million latencies. Not one,
we have a million of them.

Our actual goal is to figure out how to
describe that million.

How did the million behave?

For example, 'they're all really good, and
they're all exactly the same', would be a

behavior that you will never see, 
but that would be a great behavior.

So we need to talk about how things behave,
communicate, think, evaluate,

set requirements for, talk to other people,
but these are all common things around that.

To do that, we have to describe the 
distribution, the set, the behavior,

but not the one.

For example, the behavior that says "the 
the common case was x" is a piece of

information about the behavior,
but it's a tiny sliver.

Usually the least relevant one.

Well, there's some less relevant ones, 
but not a strongly relevant one,

and one that people often focus on.

To take a look at what we actually do 
with this stuff, almost on a daily basis,

this is a snapshot from a monitoring system.

A small dashboard on a big screen 
in a monitoring system.

Where you're watching the response time of
a system over time.

This is a two hour window.

These lines that are 95th percentile, 
90, 75, 50, and 25th percentiles,

you can look at how they behave over time.

We're a small audience here, if you look at
this picture, what draws your eye?

What do you want to go investigate here
or pay attention to ?

It's the big red spike there, right?

So we could look at the red spike,
cause it's different,

and say, "Woah, the 95th percentile shot up
here. And look, the 90th percentile

shot up at about the same time.

The rest of them didn't shoot up, 
so maybe something happened here

that affected that much, I should probably
pay attention to it

because it's a monitoring system, and 
I like things to be calm."

You could go investigate the why.

At this point, I've managed to waste 
about 90 seconds of your life,

looking at a completely meaningless chart,
which unfortunately you do

every day, all the time.

This chart is the chart you want to show 
somebody if you want to

hide the truth from them.

If you want to pull the wool 
over their eyes.

This is the chart of the good stuff.

What's not on this chart?

The 5% worse things that happened during
this two hours.

They're not here.

This is only the good things that happened
during the things.

And to get this spike, that 5% had to be
so bad that it even pulled

the 95th percentile up.