What is O11Y? Observability Demystified - Chris Riley - Splunk
S1 #12

What is O11Y? Observability Demystified - Chris Riley - Splunk

In this episode of ShipTalk, we are joined by Chris Riley who is a Senior Developer Advocate at Splunk. Chris's background spans years of professional services and being an advocate. Chris is part of the Observability Panel at {unscripted} 2021 and gives us a background in O11Y, aka Observability. With any new technology, there is an internal need to advocate for change. Chris also talks about tips and tricks for those bringing in new technology how to advocate for change and to leave ...

Ravi Lachhman: Well, Hey,
everybody. Welcome back to

another episode of ShipTalk very
excited today to be talking to

my buddy Chris Riley is a
Developer Advocate at Splunk.

Chris, why don't you introduce
yourself to the listeners if

they don't know you?

Chris Riley: Oh, there's people
on here that don't know me. I'm

just kidding. That was like the
most arrogant intro you could

think of. Yeah, my name is Chris
Riley. I'm a Senior Tech

Advocate at Splunk, which I
usually say that means that my

career as a developer was not
very successful. But I could not

let go, the the process and the
activity that happens in in

application development. So I
actually started out my career

in managed services, pure IT,
turning servers off and on every

other week, and moved into
application development, and had

a lot of fun, there working on
some really cool stuff wasn't my

forte. And now I spend most of
my time speaking at events, and

also helping tech enabled
enterprises, reconcile

technology capabilities with
reality, because as you know,

there's a lot of people who
think tools solve everything.

Ravi Lachhman: Oh, absolutely.

And it's the funny thing, right?

Like, tools by themselves, don't
do anything. It's all about the

culture. It's all about your
opinion, or how opinionated your

team members are. And that
journey is not a science. It's

certainly certainly an art, art
forum. So fun fact, Chris is

actually going to be speaking at
our conference {unscripted}. So

depending on when you listen to
this podcast, Chris is going to

speak or has already spoken at
the conference. But if you're

watching this video on YouTube,
there's something behind Chris

there's this "O11Y", I can't
even say it out loud. But Chris,

why don't you tell us a little
bit about what is that acronym

stand for?

Chris Riley: You know, I
shouldn't be embarrassed about

this. I plastered all over the
place. I actually did a Twitch

Stream on earlier this week. And
I got the same question is like,

what are you doing? What is this
thing? So first of all, say our

industry weaponizes terminology
I am I am not gonna, you know,

debate that it It happens when
it when it gets to the point,

the way I embrace new
terminology is this is the term

represent a problem space? And
is that problem space unique

enough? That when you're having
a conversation with somebody,

you need to label it, right? So
a lot of these terms fizzle away

because they just become second
nature. Like we don't really

think about DevOps so much.

That's kind of just the standard
practice. So "O11Y", if you're

really cool, you call it Ollie,
all these stands for

observability. And this
particular awesome graphic is

related to a little game that we
built the quest for

observability. But "O11Y" if
you've queued into this

standard, you take a long word,
take the first letter, the last

letter, and then you count the
characters in between. There's

your industry term. And I've
told people that if you ever

catch me in public, where I'm
not solicited, because you're

you're asking me saying Ollie,
or typing it out or anything

like call me out and in the
reason why is because it it

alienates the people who can
benefit from modern

observability practices. Because
they don't, they don't they

won't even enter the
conversation after they, they

see that. But they they stand to
benefit from it. So I don't like

that it makes a members only
club where it is become very

useful in my day to day active
activities is with those people

who are very familiar with the
term. It creates a an amount of

efficiency, I'll say in
conversation, because you know

what, Ravi, I always miss the V.

Every time I type observability.

I always miss the V. So O11Y or
Oliie, I will never miss a V.

Ravi Lachhman: Now I know how
they create those acronyms. I've

been so bad, like those
particular acronyms. But there's

some for like
internationalization or

Kubernetes. It's like I have to
like pray that Google like

understands what I'm like
searching for. And it's so funny

because I constantly misspell
observability. It's not even in

my Chrome spellcheck. It's like
oh, I hope I spelled that right

the first time when I right
clicked add to dictionary. But

yeah, a little bit about
observability. Why don't you

give us a little bit of a cras
course? In your words, Ch

is, like, What on earth is
bservability? So I'll take a s

ep back. If you were to Googl
observability, it

would be coming from a man
facturing term. So like the

Wikipedia definition of it,
it's looking at the output of

system to determine how wel
the system performed. For ex

mple, if you look at a car aft
r the car has been manufactured,

well, if there's a lot of panel
gaps, and you're missing a door,

you can infer that the manufac
uring process is not good, b

t not putting words in Chris
s mouth here. Chris, will you

ell us a little bit of journey
nd story and like, for those wh

don't know what it means and
what is observability?

Chris Riley: Yeah, so I think
your your definition is better

than mine. It comes from
manufacturing, it comes from

networking, it was more of the
technical input, implementations

of this come from the networking
world prior to how we use it

today, which is largely
associated with cloud native

development and cloud
applications. It doesn't need to

be but that's where the
association has come from. And

so I think a lot of people have
slightly differing definitions

that they are extremely
passionate about. And hopefully

you all can come and join the
panel, because those might come

out.

So my perspective on
observability is very similar to

DevOps is very similar to
DevSecOps is very similar to

SRE, Site Reliability
Engineering, which is the

strategy component is absolutely
critical of this, with this. So

understanding that the product
of your software delivery is

representative of the process
that built it is kind of the

foundation. But how you get
there, mostly in terms of the

data that you look at to get
there is where some of the

debate comes from. And the
reason that matters is if you

assume that observability is
this new set of data traces and

spans. So this is a new approach
to getting data out of your

application, surfacing issues
and doing discovery, then you

have a limited, you have limited
the practice of observability to

a handful. It's not, I mean,
it's not a handful, but a

limited set of companies who can
do it, which is largely cloud

native companies running in
Kubernetes. And microservices.

Is it fair to say that those are
the only ones that can benefit

from a practice of
observability? I would say no, I

would say No, it isn't fair,
because traditional monitoring

had a completely different
approach you didn't look at the

output but you focused on your
immutable infrastructure, that

one server you gave a name. And
if anything went wrong with that

server, you went to the log
directly, or you looked at

events, and you got a flood of
information. And you were kind

of able to figure out what was
going on. In any distributed

system. It doesn't have to be
microservices, in any

distributed complex system,
you're wasting a lot of time, if

you do that, if you go
immediately to the log as your

source of information, you could
be on the wrong path. And

burning cycles when something is
down is bad news, especially if

you have a e commerce
application or so forth. So in

the world of observability, we
have this expectation that the

system tells us what's wrong and
gives us the context, we need to

troubleshoot it. So we look at
observability as a collection of

practices, which includes
incident response, APM,

infrastructure monitoring, real
user monitoring, synthetics,

whatever you want to call it,
basically monitoring at every

layer of your tech stack. And
that is relevant for everybody.

And it's in what I like about
using the terminology again,

does it address a problem space?

Yes. The problem space is
distributed, supporting

distributed systems is complex.

Is that problem space big enough
that it's worthwhile to have a

label? Yes. Because when we talk
about traditional monitoring,

we're usually talking about
logs. And observability goes

beyond the log. And so that's
where I kind of embraced the

term as a modern form of
monitoring.

Ravi Lachhman: Yeah, that makes
that makes perfect sense. Just

going back to like my
engineering days, like we had

built a lot of distributed
systems and like a big challenge

would be following the user
journey because a particular

user can transverse a dozen
endpoints over a dozen different

pieces of infrastructure because
how we built it to be robust,

you know, so we have multiple
nodes each endpoint, in case

there's a failure or for scaling
reasons, and then your

particular user, and just
tracing that user was almost

impossible. I know, there was
some early tracing stuff we

looked at from like Jaeger. And
that Jaeger Meister, to get be

confused. When I first heard the
term I thought about the drink.

I was like, maybe that will help
us maybe we're not learning more

about it's not the drink. It's
just it is it's as systems grow

more complex, the firepower to
just to even observe, it becomes

significant. And also just under
that firefight situation, right.

If you had infinite time, of
course, you can figure something

out, you can kind of look at a
GUID, kind of log into like 30

different boxes and see, or
these days and ages, Kubernetes,

but potentially, the node could
go away, or the pod can go away.

So you're SOL, at some point,
then, so really having that to

be to be really quick to
respond, right? Because I'm just

digging into some other points
here. Can we talk about maybe

some modern challenges of
observability? So let's say I'm

a brand new engineer, that I
just, you know, I played the

quest for observability. I'm
like, Yes, I need the

observability. Like, where can I
start? Like, how? How can I

observe? Observe, Chris?

Chris Riley: Yeah, it this is a
great question. And I think that

it in this is kind of why I
gravitated so much to supporting

the tech enabled enterprise, I
use the term tech enabled

enterprise versus tech company,
very deliberately, because

everybody's building software.

But the enterprise is not used
to building software, like,

they're not Facebook, they're
not Google, they will not be

Facebook, or Google. So this the
set of challenges they are

trying to solve, and the
technology they're trying to

embrace to do that is, is
completely different. But I

think one thing is true for
everybody, which seems a

colossal mistake, and it's
rather boring, which is data,

GDI, getting data in. So most
companies under value, how

important it is to get your
ingest strategy correct. And

there's a lot of new approaches
to this one that we really like

and I love is Open Telemetry,
which is an open source project,

for ingesting data into your
management plane or your

monitoring tools. And what I
like about is unshackled your

infrastructure because what
happens to a lot of enterprises

is that agents, proprietary
agents, or auto instrumentation

or whatever it is, can actually
be the determining factor on the

monitoring tool that you decide
to use or the observability

tool. The other aspect, besides
the instrumentation side of it,

is just the quality of data. If
you're mixing metaphors in terms

of how one service reports,
something, and another service

reports, something and how you
get the data, one gives you

logs. The other one is web
hooks. And you don't take that

into consideration when you
build your dashboards, which is

what's 10 people tend to only
think about is their dashboards,

then it it can be the source of
a lot of problems. So that's the

first thing is just all the way
on the left. How do we make sure

that we get the right data in?

And then if you think about the
dashboarding process, thinking

about the outcome, how are you
going to use the data? Everybody

wants, not everybody, but a lot
of people want the vendors to

come to them and say, Hey, if
you just pick these metrics,

you're good, you're solid, I
mean, we have golden signals, we

have RED, etc. They're useful.

They're all useful to start the
conversation and get you

started. But it may not be the
metrics that are best for your

organization. And it's certainly
in a microservices environment

is not the end all. For the wide
variation of stacks, you're

dealing with all of your
microservices. So RED is great

from a global perspective. But
at the service level, it might

be extremely limiting and won't
help the service owners as well.

So determining what you're going
to do with the metric instead of

just throwing some metrics out
there is also something that I

see organizations neglect. And
then finally, the complete right

side which you mentioned,
Incident Response. Incident

Response is a strategy. It is
completely different and it's

related to but different than
Incident Management. Incident

Management is a system of
record. incident response is

mobilization and cost. text and
it's a very short window. In

Incident Response, you have to
have a strategy, you have to

have an on call strategy, you
have to get away from spray and

pray, which a lot of
organizations do blasted to

everybody and see what happens,
or what we call lazy

mobilization, which has picked
out one person who fixes

everything always. And let's
burn them out as quickly as

possible. One thing you'll
notice is that all of these

things I just described are not
technology, things, these are

all strategies and
considerations you have to make

before you implement the
technology. And that's where I

think a lot of organizations
fall short. And they hit this

kind of hype cycle where they
adopt new tech, it looks like

it's doing great things. They're
benefiting from the dashboards.

And then they realize that it's
not the information that they

needed, or they're not using it
correctly. And they have to

resolve that in the window
between that and being truly

effective. can be really long.

And that's where the danger
zone, I think, is for a lot of

organizations.

Ravi Lachhman: Excellent points.

I mean, so for some of the
listeners, it really is like a

journey, there's a whole science
behind what you can infer. So

I'll give, I'll give a little
bit of example, I'll play I'll

do my entire career in four
sentences or less. So from a

software engineer, where if you
think about what you're logging,

it's either implicit or
explicit. From a software

engineering perspective, it was
always explicit, I had to put

log statements in my code. So I
control what was going into log,

then would assume, okay, this is
running somewhere else, so that

whatever blackbox system is
running it, they have some sort

of way of tracking if something
totally wonky happens, which is

outside of our whitebox control.

And but as time goes on, right,
like I moved on, I changed jobs,

or change projects, to Chris's
point organizations, your

typical organization is very
heterogeneous. They have 1000s

of these applications that no
one potentially no one has,

there's no developer anymore.

And so how do you come up with
an approach to kind of cover all

of that, and that's very
challenging. There's no lowest

common denominator yet things
are running in COBOL. You have

things that are running in Go,
and you have things that you

don't know where they are, but
you got to bill for them once in

a while. It's so like, going
back to the metrics, you're

talking about, like RED metrics
and Golden Signals and whatnot.

Those are attempts, I think
they're good attempts, say at a

lowest common denominator, this
is what you should be looking

for. But is there's a lot I
mean, it's, it's I spent the

last year or two focusing on it.

I was my mind was blown. How,
how much science goes on behind

it. Yeah, it was fun. Changing
gears a little bit, Chris. Chris

is a Developer Advocate. One of
the hard skills you mentioned,

someone adopting a company
adopting new technology. How do

you advocate for things? Like,
just if you're an engineer, and

you want to bring in a new
technology or you want you're

passionate about something like,
how do you even start advocating

for change or advocating for
something new?

Chris Riley: That's a great
question. I mean, advocacy. It's

a fun role. It's, it's, it's a
challenging role in you know,

usually the best advocates come
from a technical position, you

know, historically. Sometimes
you hear the term evangelism, I

think that they're somewhat
synonymous, I prefer advocacy,

it seems a little less
intrusive, because this is not

intrusive. It's more a process
of stewardship, which is going

to get to the strategy that I'm
going to imply. Sometimes you

hear Developer Relations, which
there's a lot of opinions about

how the two work together, I'll
say, Developer Relations, this

tends to be something kind of
radically different, more like

building a game like this. So
advocacy, how do you advocate?

Well, first of all, you have to
agree that everybody is selling,

advocating, always, in even in
your role, it doesn't matter.

And it usually comes down to I
want to use a library or I want

to buy this tool or I want to
convince my peers to use the

same automation that I'm you
know, even care about the

automation. So all usually all
the moments where you're like,

hitting your head against the
desk, like why don't they listen

to me is the moments when you
should be like building rapport

in relationship. You know, you
can go and find all the cheesy

stuff out there on how to do
this, but it there's a lot of

empathy that's needed in a lot
of stewardship. So I think the

days of going to somebody and
saying do this because it's the

right thing are totally gone.

We're all too busy for that. I
don't I don't care how who you

are, it doesn't matter how right
the person talking to you is if

they tried to shove it down your
throat, you're not going to

listen. So thinking in terms of
stewardship is the approach that

I like to take. And you have to
believe in what your present, so

you can't like and that's one
thing that people don't

understand about advocates and
you've probably run into this is

like, I'm, I'm not promoting
anything, I don't already

believe it. Because if I did,
that, that if you're can be

genuine that comes across,
eventually, people are aware of

that. So you have to be genuine,
you have to think about

stewardship, the best trick is
give get, right, you want them

to get something from you, which
is generally a concept, an idea,

some sort of a decision, give
them something and buy give, it

can be really small. So help
them be more efficient. If I'm

trying to convince somebody that
pipeline analytics, for example,

matters. I'll give them a metric
that I know they care about, but

I don't care. So it you need to
you need to facilitate and also

tie what you're working on to
their objectives. Again, it can

feel really annoying, and I was
out. Once I figured out this

trick, I was annoyed by the how
well it worked by focusing on

their goals, not mine. And but
it does. And, you know, if

you're very utilitarian like me,
the outcome is what matters. So

I think everybody's an advocate,
I would encourage you if you're

in a technical role to consider
advocacy, if you if you enjoy

this process, in this journey of
working with people consider

advocacy. But everybody is
advocating to the point, Ravi,

that I've seen companies have
internal advocates as a part of

their DevOps service
organization. And they often do

things like run dojos, internal
dojos. And, and just continually

spread and steward best
practices. And as a result SREs,

that's kind of the function of
SREs these days. They're no

longer on call for their code.

They're stewarding the best
practices of supporting

applications and services.

Ravi Lachhman: Yeah, absolutely.

I think it boils into a lot of
what you see like expertise

roles. So like essary. And apps
like engineer, people who have

to use them using the
stewardship role. They're

stewards of the their domain
knowledge. So they have to make

sure that they disseminate that
across the organization, because

unfortunately, there's not an
essary in every sprint team.

There's not an app sec engineer,
and every, you know, two, two

pizza team whenever Bezos had a
conversation with someone from

Amazon, but I eat a lot of pizza
that my team would be three

people because me and two other
people can eat.

Chris Riley: Well, you decide,
is it a smaller team or more

pizza?

Ravi Lachhman: That could be
another podcast for their time.

And that's absolutely right.

Chris hit the nail on the head a
being very being very timely

podcast, if you go on LinkedIn,
or Indeed there's like a huge

rush of firms that are not
software companies hiring for

internal advocates, right? And
it's a lot of times I'll put

myself in the shoes of like,
let's say a staff engineer, you

know, if you if you
mister/misses, staff engineer,

or looking to be a principal or
chief, a lot of that there's a

huge part of advocacy in your
job because you're supposed to

be a change a change agent for
the company in well, how do you

do that? No, not like Chris
said, you're not going to be the

days of light is really
dictating this is to stack, this

is what we'll use. Those days
are dying, right? Like

organizations are being much
more accepting of, Hey, you know

what, we'd be pragmatic because
people go and come right, like,

no one's gonna be at the same
firm for 40 years. So your

legacy is during the time but
hey very important skills sets

to have. So kind of coming into,
you know, the homestretch here

for the for the podcast. I like
I kind of like to ask an

intrinsic question to every one
of the podcast guests. So I'll

go ahead and ask Chris this so
Chris, imagine you're you're

just fresh out of university or
and you're walking down the

street and you're able to time
travel or current Chris was able

to time travel into the day you
graduated University. Then you

ran into yourself with your
university cap on, what would be

some advice any advice that you
would tell young Chris entering

the real world?

Chris Riley: So I think I have
one. But I have to say that I

think I have a lot to learn.

Chris today has a lot to learn
from that, Chris also. And I

think those lessons are around
grit in determination and

passion, not that I'm not
passionate about what I do. But

certainly Chris in college
years, which is was much more

passionate.

So you, you underestimate how
much can be done in a long

period of time. And you
overestimate how much can be

done in a short period of time.

So college, Chris, extremely
impatient. And if I have any of

my peers listening to me now, or
coworkers, or people who know

me, let's say you're extremely
impatient, Chris, today, you are

one. So yes, that's true, I was
even more impatient than and

that impatience leads to a lot
of agnst and frustration, which

can come out in ways that are
not not productive at all. And

so patience is something that
I'm still learning. And playing

the long game is something that
I'm also still learning because

all I cared about was the short
game back then. And so I think

there's there's a lot to learn
in in both ways. And you'll

notice I didn't say the word
maturity, and I didn't say the

word experience, because both of
those terms kind of bugged me.

It's like, be a grown up kind of
stuff. I don't believe in that.

I think 23 year old Chris
actually had an amount of grit

that I still had today. But I
also think that he could have

chilled out a little bit. Chill,
Chris. I think that would have

helped be more effective in
accomplishing his goals.

Ravi Lachhman: Awesome. Yeah.

Very, very stellar advice. We
all can benefit from chilling a

little bit. Chill once in a
while. But hey, Chris, thank you

so much for being on the
podcast. I'm really looking

forward to your session at
{unscripted}. Or I enjoyed your

session at {unscripted},
depending when someone's

listening.

Chris Riley: Did I do well,
that's if time traveling right

now. How did it go? Was it
bloodbath?Or was it like super

mellow?

Ravi Lachhman: We'll find out.

There's some there's certainly
some personalities on this on

the panel session that Chris is
on. Be sure to catch it. But

Chris, thank you so much for
coming on the podcast. I always

enjoy having you on. And I catch
everybody next time.

Chris Riley: Thank you. And
yeah, make sure you attend the

panel and the entire event. It's
gonna be awesome Harness does a

great job with virtual events.

And there's a lot out there. I
understand that. So you got to

find the ones that that grab
your attention.