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Description
Don’t miss out! Join us at our next event: KubeCon + CloudNativeCon Europe 2022 in Valencia, Spain from May 17-20. Learn more at https://kubecon.io The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects.
Observe with Rust: OpenTelemetry and Tremor - Gary White Jr., Wayfair
Tremor is an early stage event processing system for unstructured data with rich support for structural pattern matching, filtering and transformation. Hundreds of companies around the world are using Rust in production today for fast, low-resource, cross-platform solutions. Gather round your screens and lecterns to hear the story of open source infrastructure helping a tech company sell furniture. We will show how it all happens with Rust and Tremor, and how we tune in and out of what matters; all with a lower cost of infrastructure and maintenance. Tremor users also appreciate the “software-like” syntax of querying through their systems, without sacrificing the performance of Rust. We're proud as supporters of Tremor to integrate OpenTelemetry into our codebase and feature set. We are excited to share details of this integration, how it works, and how we use it at Wayfair. Come to hear bad jokes and good technical content!
A
A
A
I
have
literally
hundreds
of
emojis
in
the
waiver
slack
channel
that
spin
spinning
monkey
is
one
of
them
and
I'm
very
proud
of
it.
While
we're
talking
about
emojis,
let's
go
through
some
of
the
best
I've
curated,
my
favorites,
for
you
kubecon
only
the
best
for
you.
I
know
that.
There's
a
lot
of
passionate
emoji
enthusiasts,
showing
up
to
my
rust
talk.
A
You
can
see
a
baby
yoda,
a
nonsensical
upside
down,
alien
cowboy,
a
cat
that
is
projecting
such
panic,
energy
that
you
can.
You
can
feel
it,
and
it
feels
like
something
that
you
would
feel
too
and
the
open
source
program
office
train
where
you
can
string
them
together
and
have
the
osbo
logo
just
running
across
the
screen.
A
A
A
So,
let's
just
get
into
it
and
start
with
tremor
tremor
is
an
early
stage
event
processing
system
or
unstructured
data
with
rich
support
for
structural
pattern,
matching
filtering
transformation,
very
astute.
I
know
the
best
part
of
being
a
presenter
is
reading
directly
from
the
slide.
It's
very
engaging
for
your
audience.
A
I
ripped
that
definition
directly
from
oh,
it's
that
way.
Docs.Tremor.Rs
and
definitions
are
fantastic
to
start
with,
because
they
show
you
how
many
words
don't
make
sense
together,
and
I
hope
that
when
we
come
back
to
it,
it
shows
just
kind
of
how
much
we
can
really
in
time
that
we
have
together
and
I
think
the
best
way
to
fit
those
ideas
into
people's
heads
is
speaking
in
a
more
universal
language
and
speaking
in
gifs
and
pictures.
A
A
We
would
absolutely
want
to
know
if
our
database
is
overloaded
or
it
needs
some
help,
or
it
just
needs
some
clearing
out
right.
If
it's
stuck
on
a
transaction,
that's
important,
it
would
be
fantastic
if
we
could
just
magically
translate
all
the
ones
and
zeros
into
signals,
but
we
would
be
able
to
make
simple
decisions
on
how
to
maintain
our
critical
services.
A
We
drown
in
the
sheer
volume
that
we
receive
from
our
services.
The
data
is
unstructured,
so
we
make
cabana
dashboards
associating
it.
We
do
influx
charts
with
lousy
indexes
for
the
data,
and
we
do
a
lot
of
work
just
to
try
to
understand
what
our
applications
are
saying
and
on
top
of
having
a
regular
fire
hose,
we
aren't
able
to
design
for
system
traffic
during
peak
events
like
cyber
five
or
times
when
our
businesses
might
do
the
most
for
us.
A
A
A
Five
really
big
days
for
us.
We
found
that
tremor
on
cyber
five
was
processing
about
five
gigabytes
per
second,
and
that
may
not
feel
like
an
overly
impressive
number,
because
you
know
what's
the
meaning
of
it.
If
you
don't
understand
the
infrastructure,
that's
running
it
I
mean
with
enough
machines.
Any
application
should
be
able
to
handle
that.
A
You
know
we
would
fork
over
for
it.
We
would
spend
what
we
needed
to
to
make
sure
that
we
could
see
what
was
happening
as
the
tremor
team
came
by
and
realized
that
they
could
process
much
of
the
same
load
for
less
the
compute
workload
quickly
moved
over
now
we're
processing
similar,
if
not
literally,
the
same
load,
with
an
incredibly
small
footprint
comparatively
when
we
plug
our
current
footprint
into
the
gcp
price
calculator.
A
We
see
less
than
a
thousand
dollars
a
month,
40
times
less
significant
change,
and
it's
done
with
a
programmatic
interface
that
we
were
able
to
build
inside
the
company
if
the
cost
savings
aren't
compelling
and
the
speed
isn't
compelling
enough.
Let's
talk
about
the
plug
and
play
on
and
off
ramps
that
give
you
flexibility
with
tremor,
so
tremor
allows
us
to
interpret
these
raw
signals
that
we
get
from
the
infrastructure,
decorate
and
transform
them
as
needed,
and
then
ship
them
out
to
downstream
consumers.
A
It's
also
built
to
be
an
extendable
infrastructure.
So
tremor
has
the
ability
to
add
more
on-ramps
and
off-ramps
dynamically,
very
powerful,
very
cool
stuff
that
we
like
to
publicize.
So
we
have
on-ramps
and
off-ramps.
We
have
these
cost
savings.
I
want
to
go
back
to
the
original
definition
and
summarize
everything
that
we
just
talked
about
tremor
is
an
early
stage
event.
Processing
system
for
unstructured
data,
with
rich
support
for
structural
pattern.
A
We
can
use
it
to
process
signals
before
they
go
through
other
systems
or
we
can
process
signals
after
they
come
out
of
other
systems.
We
can
structure
the
data,
we
can
decorate
it,
we
can
shape
it.
We
can
do
what
we
have
to
do
to
make
it
useful
and
we
can
send
that
data
along
to
the
downstream
or
rate
limit
it
and
keep
it
to
ourselves
so
that
we
don't
overwhelm
our
observability
pipelines.
A
A
A
You
can
use
it
to
instrument,
generate,
collect
and
export
open,
telemetry
data
or
analysis
in
order
to
understand
your
software's
performance
of
behavior,
just
like
for
tremor.
The
definition
is
very
helpful
for
laying
the
groundwork,
but
practically
what
does
this
mean?
What
does
it
do?
How
does
it
work?
What
is
open,
telemetry
this
time
I
decided
to
skip
the
pictures
on
this
slide
is
a
glossary
of
terms
related
to
open
telemetry,
which
should
give
you
all
the
information
you
need
to
know
to
understand
how
it
fits
with
tremor.
A
I
think
this
slide
is
roughly
1200
words
and
an
average
adult
reading
at
300
words
per
minute
should
be
able
to
fully
read
and
digest
this
slide
in
less
than
five
minutes.
So
we'll
sit
here
for
about
five
minutes.
While
everybody
reads
the
slide
and
learns
the
important
terms
about
otel,
I'm
going
to
take
myself
off
the
side
so
that
you
can
see
yep
just
you
know,
take
a
second
I'll,
be
here.
A
Okay,
well,
yeah!
Let's
do
that!
Okay,
love!
You
too!
Okay,
bye!
All
right!
Put
that
on
mute
for
real
and
say
that
was
me
from
the
future.
He
told
me
that
this
slide
and
people
reading
it
was
the
worst
part
of
the
presentation.
People
were
walking
out.
People
were
saying
I
hate
this
and
it
made
a
really
bad
reputation
for
me,
which
is
what
matters
so
he
time
traveled
back
and
changed
the
slides
just
to
make
sure
that
this
presentation
went
on
real
hero.
A
Now
we
have
a
good
presentation
which
is
almost
as
good.
Let's
get
going
hotel
or
open
telemetry
is
a
step
towards
standardizing
the
way
that
these
signals
pass
from
applications
and
infrastructure
to
metrics
and
logging
tools.
In
an
ideal
world,
where
we
already
had
people
using
cell,
open
telemetry,
everything
would
magically
work.
Hotel
open
telemetry
hopes
to
encapsulate
sufficiently
common
application
and
infrastructure
signals
in
a
way
that
can
be
standardized
to
old
and
new
observability
tools.
A
A
A
Hotel
can
inject
bytecode
at
runtime
to
trace
important
metrics
and
operations
about
your
application
and
report
them
to
the
open.
Telemetry
collector,
it's
as
simple
as
pointing
to
a
jar,
doesn't
get
much
better
than
that,
but
to
integrate
integrate
code
into
the
framework.
Come
on
that,
I
bet
that's
harder.
Let's
see,
okay,
there's
not
that
much
to
it
either.
A
Custom
logic
aside,
you
just
do
a
standard
library
import
which
specifically
for
frameworks
like
spring
it
automatically
reports
metrics
and
allows
you
as
a
developer,
to
specify
anything.
You
need
my
viewpoint
as
a
developer
that
has
had
to
use
hotel
recently
to
learn
for
this
presentation
is
that
it
was
pretty
simple
process
to
dig
into
and
work
with,
having
the
option
of
a
default
configuration
being
able
to
help
later.
If
I
need
more
stuff
is
exactly
what
an
observability
platform
should
be
doing,
but
I
digress.
A
This
is
the
juicy
bit
getting
into
the
collector
the
agent
for
hotel.
The
collector
itself
is
not
a
back
end.
It's
a
translator
where
you
send
metrics
into
open
telemetry,
and
it
will
send
those
signals
in
a
way
that
prometheus
jager
fluent
bit.
Whatever
else
you
might
be
using
to
trace
your
metrics
can
understand,
and
this
might
seem
a
little
straightforward
or
facetious
at
first
I
mean
couldn't
we
just
process
directly
into
jaeger
or
prometheus.
A
When
you
place
agents
around
the
infrastructure
with
the
standard
library
that
allows
the
same
signals
to
come
from
many
applications,
it's
relatively
easy
to
collect
them
and
build
a
bigger
picture
instead
of
bespoke
application
code
built
into
your
back
ends.
That
knows
how
to
interact
with
jaeger
prometheus.
A
These
agents
are
more
effective
at
gathering
and
forwarding
these
metrics.
As
a
result,
exporting
into
the
collector
means
that
you
can
build
multiple
back
ends
or
change
back
ends
on
the
fly
as
you
need
to
in
the
collector
installation,
which
allows
you
to
focus
on
discerning,
what's
important
and
less
about
how
to
configure
back
ends.
A
A
A
A
If
you
make
a
request
to
a
back
end,
you
can
trace
it
along
the
way
using
zipkin
prometheus
jager.
This
stuff
is
built
in
there
moving
on
to
metrics,
I
think
that
metrics
are
probably
the
most
intuitive
signal.
They're
split
into
a
couple
of
categories
where
you
can
count
things
with
a
counter.
It
only
ever
goes
up.
It's
like
how
many
requests
you
receive
in
an
application
or
how
many
total
bytes
are
computed.
A
A
A
A
This
is
an
important
topic,
given
that
they
are
the
most
human,
readable
and
least
machine,
readable
part
of
any
observability
pipeline.
We'll
talk
about
this
more
when
we
think
about
how
tremor
and
otel
fit
together,
but
baggage
is
a
relatively
new
idea
to
me.
I
think
it's
a
newer
idea
in
the
observability
ecosystem,
given
that
it's
only
recently
been
put
into
hotel
baggage,
allows
us
to
associate
metadata
like
api
tokens
for
a
request.
A
A
A
This
is
the
link
on
the
slide
to
see
where
it
was
originally,
we
can
see
the
collector
on
the
left.
Oh
in
the
way,
aren't
I
put
myself
out
of
the
way
there
I
go,
and
you
can
see
that
the
data
on
the
left
is
being
put
into
a
receiver.
Then
a
processing
pipeline
and
being
spit
out.
The
other
end
to
an
exporter
right
in
the
middle
is
where
we
spent
most
of
the
first
part
of
the
talk
talking
about
tremor.
A
Let's
look
at
some
practical
examples
of
how
we
might
do
that.
One
practical
case
for
trauma
at
wayfair
is
rate.
Limiting.
We
know
that
if
a
given
stream
is
producing
any
signal,
then
it
might
be
overwhelming,
given
the
size
of
it
or
the
state
of
our
infrastructure
and
since
tremor
can
handle
that
extreme
throughput
and
then
rate
limit
the
application.
A
A
You
could
also
treat
it
not
only
as
the
intermediary,
but
something
that
helps
you
translate
signals
from
hotel
into
other
frameworks.
Now
this
isn't
the
main
use
case
for
tremor,
but
there's
a
argument
to
be
made
if,
if
you're
working
with
something
experimental,
much
easier
to
integrate
with
existing
infrastructure
like
tremor,
where
you
can
then
use
otel
as
an
on-ramp
on
your
existing
installation
and
verify
that
it
brings
a
lot
of
value
until
you
get
the
adoption
that
you
need
to
bring
open
telemetry
to
a
scale
that
is
at
an
enterprise
company.
A
A
Keep
it
keep
one
thing
that
open
telemetry
states
in
their
documentation
is
that
it
works
best
with
structured
data.
It
doesn't
work
great
with
unstructured
data,
so
when
you
have
logs
that
are
unstructured
that
you
expect
it
to
struck
to
do
and
work
with
it's
going
to
be
cumbersome,
but
if
you
use
tremor
to
shape
that
data
and
get
what
you
need
out
of
it
and
then
make
an
hotel
compliant
signal,
that's
counters
or
even
a
log,
that's
just
easier
for
it
to
manage.
A
Then
you
are
able
to
save
compute
from
the
oltp
from
the
otlp
open
telemetry
protocol
agent,
rather
than
having
the
agent
have
to
do
rate
limiting
or
deal
with
the
scale
of
those
logs.
Basically,
it's
the
same
ideas.
It's
just
that
you
don't
have
to
wait
until
after
open
telemetry
has
the
data.
You
can
do
this
from
the
start
as
well.
A
A
I'm
just
going
to
go
back
and
say
as
a
reminder:
I'm
gary
white,
I
work
for
wayfair
with
the
open
source
program
office.
You
can
learn
more
about
us
and
our
work
at
wayfair.github.com
if
you're
interested
in
tremor
and
would
like
to
get
involved,
you
can
also
check
out
tremor.rs
we'll
be
happy
to
have
you.