►
From YouTube: The Level Up Hour (E32): Kubernetes Past & Future
Description
Buckle up, this is a big one! This week, Red Hat CTO Chris Wright joins the Level Up Hour to talk about the theoretical future of Kubernetes. Kubernetes has transformed the way we think about applications, cloud computing, DevOps processes, and even what it means to build software, and it really is much more than just an application development platform. Come join us for the episode, bring your questions, and help us really get into it.
Watch more Chris Wright in Technically Speaking:
https://www.youtube.com/playlist?list=PLbMP1JcGBmSGMPKkLoq6CGwwKDxl9VvBE
Want to attend #KubeCon?
Share what you’ve learned on The Level Up Hour using #tluh, and post a link to it in the level-up channel on https://discord.gg/5VMVGJt to enter.
https://events.linuxfoundation.org/kubecon-cloudnativecon-europe/
Follow us:
Chris Wright https://twitter.com/kernelcdub
Langdon White https://twitter.com/1angdon
Chris Short https://twitter.com/ChrisShort
What is the Level Up Hour?
Every Wednesday at 9am ET we stream live demos on how Red Hat Enterprise Linux (RHEL) users and admins can benefit their organizations and improve their careers by learning how to use containers, Kubernetes, and Red Hat OpenShift.
Learn more at:
https://red.ht/leveluphour
http://red.ht/3ayHlHI
How to participate in the The Level Up Hour:
Watch on YouTube every Wednesday at 9amET
Chat with us on Discord https://discord.gg/5VMVGJt
Check out our GitHub repo https://github.com/level-up-hour/
About OpenShift:
Red Hat OpenShift is an open source container application platform based on the Kubernetes container orchestrator for enterprise application development and deployment.
https://www.openshift.com/
https://github.com/openshift/
#RedHat #OpenShift #tluh
Buckle up, this is a big one! This week, Red Hat CTO Chris Wright joins the Level Up Hour to talk about the theoretical future of Kubernetes. Kubernetes has transformed the way we think about applications, cloud computing, DevOps processes, and even what it means to build software, and it really is much more than just an application development platform. Come join us for the episode, bring your questions, and help us really get into it.
Watch more Chris Wright in Technically Speaking:
https://www.youtube.com/playlist?list=PLbMP1JcGBmSGMPKkLoq6CGwwKDxl9VvBE
Want to attend #KubeCon?
Share what you’ve learned on The Level Up Hour using #tluh, and post a link to it in the level-up channel on https://discord.gg/5VMVGJt to enter.
https://events.linuxfoundation.org/kubecon-cloudnativecon-europe/
Follow us:
Chris Wright https://twitter.com/kernelcdub
Langdon White https://twitter.com/1angdon
Chris Short https://twitter.com/ChrisShort
What is the Level Up Hour?
Every Wednesday at 9am ET we stream live demos on how Red Hat Enterprise Linux (RHEL) users and admins can benefit their organizations and improve their careers by learning how to use containers, Kubernetes, and Red Hat OpenShift.
Learn more at:
https://red.ht/leveluphour
http://red.ht/3ayHlHI
How to participate in the The Level Up Hour:
Watch on YouTube every Wednesday at 9amET
Chat with us on Discord https://discord.gg/5VMVGJt
Check out our GitHub repo https://github.com/level-up-hour/
About OpenShift:
Red Hat OpenShift is an open source container application platform based on the Kubernetes container orchestrator for enterprise application development and deployment.
https://www.openshift.com/
https://github.com/openshift/
#RedHat #OpenShift #tluh
A
B
Hi
everybody
and
yeah,
so
today
we
as
you
can
see
on
the
screen
we
have
a
very
special
guest
is
chris
wright.
He
is
the
chief
technical
officer
of
red
hat
and
knows
some
technology
stuff
and
in
particular
knows
a
bunch
of
stuff
about
both
linux
and
kubernetes.
In
fact,
I
think
your
twitter
handle
is
colonel
c
dubs,
so
you
know
it's
kind
of
like
he's
kind
of
a
colonel
guy.
B
You
know,
as
we
have
said
on
the
prior
shows
we
have
given
all
of
you
and
everyone
else:
free
tickets
to
red
hat
summit,
so
you
know
be
sure
to
attend
because
it
happens
to
just
be
free,
so
there's,
but
there's
lots
of
good
stuff
coming
up
in
the
one
that
is
coming
up
next
week,
where
it's
kind
of
like
the
way
I've
been
kind
of
thinking
about.
It
is
like
it's
focused
on
like
keynotes,
and
so
it's
kind
of
all
the
big.
B
C
So
some
of
the
things
that
I'm
talking
about
red
hat's
focused
on
the
hybrid
cloud,
we
think
a
lot
about
the
open,
hybrid
cloud
and
where
open
source
creates
the
you
know
the
sort
of
infrastructure,
support
and
capabilities
for
building
applications
and
delivering
them
all
across
the
the
open,
hybrid
cloud.
What's
really
interesting
to
me
right
now
is
that
notion
of
hybrid
cloud.
C
It's
not
new!
It's
been
around
for
a
while.
We've
been
thinking
about
it
and
and
sort
of
advocating
for
it
and
supporting
our
customers
who
are
living
that
as
a
daily
reality
for
quite
some
time
today,
and
maybe
we
were
kind
of
the
early
ones
and
and
the
lone
voice
for
a
while.
Today,
you
find
similar
types
of
concepts
from
public
cloud
providers
and
and
other
software
vendors
across
the
industry.
C
It's
you,
you
can
mine
it
for
information
and
use
that
information
to
change,
how
you
run
your
business
or
change
how
you
respond
to
particular
events.
I
I
think,
that's
really
interesting
and
then,
when
you,
when
you
throw
in
another
kind
of
hyped
up
technology
buzzword,
I
live
in
a
buzzword,
compliant
world.
So
just
in
case
you're
wondering.
C
C
C
A
B
So
I
want
to.
I
want
to
continue
this
conversation
a
little
bit,
but
I
want
to
back
up
a
half
a
second
and
just
be
like.
Could
you
define
edge
for
us
because
I
think
it's
one
of
those?
It
is
a
very
buzzwordy
term
and
the
reason
I'm
asking
for
the
definition
is
not
so
much
because
the
definition
but
because
I
want
to
know
what
do
you
think
of
the
aspects
in
that
definition
are
the
important
bits
or
what
are
the
hard
bits
about
what
we
call
edge.
C
Now,
oddly
enough
from
a
public
cloud
provider,
putting
a
piece
of
their
equipment
in
that
data
center
looks
like
the
edge
of
the
cloud
to
the
cloud
provider,
but
it's
in
the
data
center
from
a
data
center
perspective.
So
again,
that's
why
the
perspective
matters
and
as
you
kind
of
move
out
from
that
core
data
center,
there's
different
hops
in
in
the
network.
C
C
C
B
When
you
talk
about
the
bandwidth
we
had
and
stuff
like
that,
but
now
they're
ridiculously
large
right,
like
I
mean
you
know,
when
we're
talking
about
doing
like
machine
learning
or
whatever
you
know,
dropping
a
terabyte
of
data
on
something
for
a
problem
is
like
whatever
that
sounds
normal,
and
you
know
it
still
still
kind
of
blows
my
mind
a
bit
right
that
you
know
terabytes
of
data
getting
thrown
around.
I
mean
I
have
terabyte
hard
drives
for
crying
out
loud,
and
I
remember
buying
my
my
500
meg.
B
You
know
big
spend
hard
right,
yeah
the
so
I
think
I
think
that's
a
the
really
good
point
is
like
trying
to
make
sure
that
you
have
the
appropriate
compute
right
near
the
appropriate
data
is
a
at
least
for
me,
an
interesting
way
to
think
about
the
edge.
The
only
thing
I
want
to
do
to
was
pause
for
a
second,
because
I
remembered
that
I
forgot
my
super
ugly
slides
and
so
let's
run
through
those
real
quick
just
because
otherwise
it
wouldn't
be
a
show.
A
B
C
A
Where
an
airbus
350
generates
anywhere
between
800
and
900,
megabytes
of
data
per
flight,
yeah
right,
like
just
sensor,
data
right,
like
parts
failures
that
kinds
of
things
that
data
is
being
analyzed,
and
that
is
just
fascinating
to
me
that
wow
one
flight
can
generate
almost
a
gig
of
data.
That's
that's
impressive
right,
like
what
can
you
do
with
that
to
optimize
your
fleet
of
hundreds
of
airplanes.
C
A
C
Also
collecting
not
just
flight
data
but
weather
data,
because
you're
looking
at
where
there's
likely
to
be
storms
and
there's
seasonal
weather
patterns
that
mean
it's
more
means,
it's
more
efficient
to
fly
one
route
versus
the
other
route
and
that
that's
all
you
know,
those
are
just
airplanes.
Cars
produce,
you'll,
you'll,
hear
anywhere
from
or
40
plus
terabytes
a
day
in
in
data
with
a
in
a
vehicle
wow,
and
so
yes,
as
lange
said,
there
was
always
data
there.
C
You
know
I've
I've
dialed
up
and
wondered
if
I'd
ever
get
that
floppy
disk
downloaded,
but
the
data
rates
are
so
phenomenal
and
when,
when
you
think
about
the
richness
of
video
data
and
the
different
ways
that
you
can
apply
computer
vision
to
video
data
to
to
discern
something
people
use
video
data
when
it
there
might
have
been
an
easier
sensor.
To
give
you
pointed
information,
but
with
a
video
you
can
collect
a
whole
setup.
C
B
Seeing
what
we're
re-streaming
across
multiple
I
mean,
I
think
part
of
that
tendency
too,
is
also
interesting,
because
you
know
there's
600,
megs,
okay,
all
right,
so
the
it's
also
interesting
like
somewhere.
I
don't
know
five
ten
years
ago,
or
so
you
know
somebody
got
it
into
their
head
that,
like
we,
we
have
enough
hard
drive
space
to
basically
store
all
the
things
that
we
can
discover.
B
We
don't
know
what
questions
we
want
to
ask
yet,
but
let's
make
sure
we
grab
all
of
the
data
so
that
we
can
ask
whatever
question
we
want
to
later
and
there's
a
lot
of
really
cool
factor
to
that.
There's
also
some
questionable
ethical
factors
to
that.
But
you
know,
for
the
sake
of
kind
of
this,
show
right
the
it
really.
It
really
just
blows
out
the
data
problem,
but
also
you
know,
gives
us
all
kinds
of
really
interesting
new
questions.
We
can
ask
and
techniques
we
can
use
right.
B
B
Let's
get
your
slides
before
my
my
awesome
slide,
so
this
is
the
level
up
hour
where
we
talk
about
kind
of
like
why
containers
are
interesting
and
why
you
might
want
to
start
using
containers
in
your
everyday.
You
know
kind
of
life.
You
know
a
little
bit
focused
towards
administration
or
administrators,
but
also
for
developers
as
well.
You
know
what
I
kind
of
comment
on
is
like
I
use
containers
all
the
time
now.
Basically
anytime.
I
do
anything.
B
D
B
C
B
It's
like
my
fingers
can
type
it,
but
I
can't
necessarily
say
it
right
and
then
you
could
also
chat
with
us
on
our
discord
as
narendev
asked
this
morning.
Yes,
we
are
having
a
show
today,
however,
just
fair
warning
because
of
summit
and
kubecon,
we
will
not
be
having
shows
next
week
or
the
week
after,
but
then
we
will
be
back
with.
I
want
to
say
container
health
index.
I
think
the
week
after
that
I
can't
remember
now
I
should
have.
B
B
A
D
D
But
then,
if
you
look
at
it
as
a
blank
sheet
of
paper
and
you're
willing
to
take
all
your
expertise
of
your
network
administrator,
maybe
you
go
make
a
cni
plug-in
to
take
everything
you
know
about
networking
and
just
abstract
it
away,
so
that
a
developer
who
needs
an
ip
address
or
to
live
on
the
right
network
segment
doesn't
really
have
to
think
about
it.
If
you're
in
operations-
and
you
know
how
to
roll
out
software
safely
over
multiple
regions,
you
can
make
a
controller
for
that.
D
You
can
name
it
the
multi-region
deployment
controller
and
take
all
of
your
expertise,
sterilize
it
into
that
thing
and
share
with
other
people.
And
lastly,
if
you
harness
the
power
of
open
source,
then
you
can
get
a
whole
community
of
people
to
do
the
same
thing
and
then
share
that
knowledge
and
propagate
it
through
these
systems,
and
we
just
happen
to
call
it
kubernetes.
A
B
Yeah,
so
you
know,
obviously
we
had
a
little
bit
of
a
chance
to
talk
about
this
before
the
episode
today.
So
I
kind
of
wanted
to
kind
of
walk
into
this.
Is
that
one
of
the
things
that
came
up
in
that
discussion
is
kind
of
this
idea
of
kubernetes
as
a
control
plane,
and
you
know,
as
as
we
joke
around
about
on
the
show.
Sometimes
you
know
not
everybody
watches
the
show.
Has
a
computer
science
background.
B
So
could
you
give
us
a
definition
of
what
a
control
plane
is
you
know
and
actually
that
that
would
really
even
be
from
an
engineering
background?
You
know
we've
kind
of
co-opted
the
term
in
in
the
software
world,
but
how?
How
would
you
define
it
and
I
I
don't
think
we
really
care
if
it's
a
dictionary
definition
as
much
as
to
say
this
is
what
we
mean
in
this
context.
You
know.
C
Yeah,
it
is
a
little
kind
of
a
nebulous
term,
although
it's
used
really
pretty
consistently,
especially
in
certain
certain
subject
areas.
I
I
would
say
there
is
when
you
think
about
applications
or-
or
you
know,
computer
systems,
there's
there's
two
basic
worlds.
One
is
the
world
that's
doing
the
actual
stuff.
Sometimes
we
call
that
the
user
plane.
Sometimes
we
call
that
the
data
plane.
You
know
whatever
it's
the
place,
where
your
your
application
is
running
and
doing
applicationy
things,
business
logic,
manipulating
data
as
it's
flowing
through
the
system,
etc.
C
You
also
have
something
that
decides
when
where
and
how
things
get
done
and
that's
more
the
control
plane.
So
you
know
I
I
the
some
of
the
orchestration
conversation
bit
around.
What
kubernetes
is
for
containers
the
podman
to
cube
kind
of
bit
that
you
were
highlighting
earlier.
That
orchestration
is
is
a
a
form
of
controller.
C
It's
and
that's
what
we
call
control
plane
activity
in
the
in
in
the
setup
of
a
of
a
networking
connection,
you
have
some
oversight,
that's
ensuring
that
you
connect
the
two
ends
and
then
the
data
flows
through
the
system.
You
know
so
there's
a
control
plane
element
of
how
do
you
set
the
whole
thing
up?
Maybe
that's
authentication
to
the
system,
maybe
setting
up
a
handshake
to
do
encryption,
and
then
you
let
the
data
flow.
C
So
another
example
of
just
how
there's
a
there's
a
control,
plane
element,
that's
controlling,
what's
happening
and
then
there's
a
user
plane
or
data
plane.
That's
doing
the
actual
low-level
work
and
kubernetes
combines
the
two
so
in
the
in
the
show,
with
kelsey
we're
kind
of
deconstructing
that
back
to
what
what
are
the
differences
and
almost
always,
we
think
about
the
user
plane
most
of
what
we
spend
our
time
on.
It's
writing
applications.
The
applications
do
the
application
logic,
but
it
turns
out
managing
things.
Controlling
things
is
hard.
I
mean
it's.
C
C
So
what,
as
I
mentioned
earlier,
we
spend
most
of
our
time
thinking
about
the
application
logic
building
building
apps.
There
really
isn't
an
app
that
doesn't
have
some
kind
of
control
controller
associated
with
it,
because
you
have
to
get
you
have
to
decide
when
to
start
it
and
when,
when
and
how
and
why
to
run
it
just
to
oversimplify
it
and
the
the
the
focal
point
for
kubernetes.
C
C
You
know
always,
so
if
you
want
it
to
have
five
and
one
dies,
you
restart
one
and
there's
so.
There's
there's
you
know:
kubernetes
is
watching
all
of
that
and
paying
attention
and
and
just
managing
the
resiliency
and
making
so
the
declarative
statement
that
you
set
out
with
when
you
said.
I
want
this
application
to
be
to
be
deployed.
This
way.
C
It's
like
a
very
different
world
which
gets
a
little
abstract
and
a
little
hard
to
imagine,
but
the
what
there
are
efforts
in
different
industries
where
they
spend
all
of
their
time
focused
on
the
control
plane
and
I've
given
presentations
to
to
teams
that
work
on
things
like
control,
plane
systems
for
for
networks
and
made
this
observation
to
those
teams.
Like
hey,
you
know,
you're
off
there,
building
something
it's
pretty
specific
to
your
world.
C
C
But
we
can
extend
it
arbitrarily
with
the
same
rigor
of
creating
apis
and
declaring
the
creating
the
declarative
state
for
how
you
would
like
that
system
to
behave,
and
you
can
build
arbitrary
control
logic
to
witness.
The
current
state
understand
your
desired
state
and
work
in
a
forever
loop
rectifying.
D
C
Reconciling
the
difference
between
your
current
state
and
your
desired
state,
basically,
that
is
what
a
controller's
doing,
and
it's
just
it's
fascinating,
because
we
don't
think
of
it.
That
way,
when
you
change
your
perspective
and
think
of
it
differently,
you
suddenly
a
whole
world
of
opportunity
opens
up.
B
So
I
think
I
mean
one
of
the
things
that
that
occurred
to
me
too.
Is
that
like
do
you
have
like
a
little
bit?
Do
you
have
like
a
little
bit
of
a
challenge
with
having
some
of
those
conversations,
because
there's
like
these
classes
of
software
problems
or
like
like
things,
you
want
to
go,
build
that
on
the
face
of
them,
look
really
easy
and
then
you
get
into
it
and
you're
like?
Oh,
my
god.
This
is
impossible.
B
B
Yeah
package
managers
are
in
a
similar
vein
and
something
else
that
seems
like
a
really
easy
on
the
face
of
it.
Software
problem
orchestration,
I
actually
think,
is
in
that
same
bucket
right,
like
writing
a
good
orchestrator
that
is
resilient
and
repetitive
and
always
does.
The
right
thing
is
really
really
difficult,
and
so
I'm
curious
about
you
know.
You
said
you've
had
some
of
these
conversations
with
people
about
like
kind
of
leveraging,
something
like
looking
like
kubernetes
in
other
kind
of
context.
Do
they
go?
B
D
C
C
So
in
some
cases
it's
just
cute
idea,
clever,
abstract
theory
never
going
to
apply
it
thanks
for
the
conversation
chris
in
other
cases,
it's
it's
eye
opening,
like
wow,
that's
actually
solves
a
real
problem
that
we
have
that
we
are
struggling
with,
and
now
we
have
a
tool
to
to
solve
that
and
distributed
systems
are
hard.
I
mean
there's
a
reason
that
there
are
academic
programs
that
have
been
researching
distributed
systems
for
decades
right.
C
C
Are
things
called
crds,
which
would
be
a
custom
resource
definition,
which
is
essentially
an
extensible
way
to
to
build
a
schema
that
describes
the
state
of
the
system
that
you
care
about
and
then
a
custom
controller
associated
with
that
crd?
Now
you
have
a
kubernetes
resource.
It
looks
feels
behaves
like
a
kubernetes
resource,
but
it
has
a
this
custom
controller.
C
We
build
the
operator
framework
on
top
of
that
infrastructure,
and
now
you
have
an
operator
which
is
code
that
can
run
an
application
in
a
in
a
specific
way,
including
understanding
life
cycle
management.
Maybe
backup
restore
the
kind
of
auto
scaling
you're
responding
to
metrics
that
are
specific
to
the
application.
Well,
it
looks
like
I'm,
you
know,
sort
of
not
keeping
up
with
my
slo,
and
so
I
need
to
add
extra
instances
because
throughput
you
know
peak
load
or
whatever.
C
That's
already
a
control,
plane
activity
and
that's
work
that
we
do
already
and
the
thing
that
I
find
kind
of
interesting
and
and
actually
exciting.
And
it's
a
different
take
on
on
the
world,
is
that
that
control
plan
activity
just
managing
a
single
application
like
that,
an
operator
to
to
run
a
database.
C
C
Like
right
there
it's
a
big
deal
and
then
but
wait
there's
more
and
then
you
could
take
multiple
sres
from
different
perspectives,
combine
their
experiences
and
expand
and
improve
that
same
operator,
which
is
code
so
now
you're,
bringing
the
an
open
source
community
aspect
and
code
development
aspect
to
operations.
How
do
you
build
and
manage
systems
which
mostly
open
source
software
projects
are
about
features,
functions,
capabilities
and,
like
exercise
left
for
the
reader?
How
do
you
actually
run
that
thing?
C
C
So
you
have
to
have
code
and
automation
to
manage
that
complexity
and
to
me,
that's
why
it's
so
interesting.
There's
this
whole
world
that
that's
opening
up.
That's
about
community
development
collaboration,
making
operations
really
a
first-class
citizen
in
the
world,
which
is
also
including
the
control
plane
systems
that
are
what
operations
teams
depend
on
to
run
and
operate
infrastructure
and
platforms
and
systems,
and
and
all
that
so.
B
It's
really
interesting,
I
mean
because
what
I
I
never
really
thought
about
this
before,
but
it's
one
of
the
things
that
I
would
regularly
talk
about
when
talking
about,
like
modularity
in
app
streams,
was
basically
being
able
to,
or
even
like
some
of
the
earlier
things
that
we
did
that
were
similar
is
like
one
of
the
things.
That's
really
nice
about
rpm
dev2
right
just
package
managers
in
general
is
that
you
can
encapsulate
there's
some
expertise
encapsulated
in
the
packaging
format
that
you
are
benefiting
from.
B
The
problem
I
was
highlighting
with
like
modularity
was
that
it's
it's
not
very
discoverable,
so
you
know
if
you
want
to
run
an
apache
web
server,
for
example
on
rel
you
just
you
know,
yum
install
hdvd
right.
However,
if
you
want
to
host
your
html
pages
out
of
people's
home
directories,
you
have
to
go
and
set
up
like
public
html
directories
and
all
this
stuff.
B
Who
knows
how
to
set
it
up
and
but
knowing
what
that's
called
is
very,
very
difficult,
and
so
it's
kind
of
like
a
smattering
of
those
operations
that
you're
talking
about
right,
because
what
what's
so
difficult
about
our
operational
environment,
a
lot
of
the
times
these
days
right
is,
like
you
know,
we're
all
building
on
the
shoulders
of
giants
these
days
right.
So
as
a
result,
we
have
to
run
all
of
these
relatively
complex
systems
before
we
even
get
to
our
codes
right.
B
I
don't
need
to
actually
understand
how
to
run
a
mariadb.
Well
right
I
can
you
know
I
can
run
one
on
my
laptop,
but
it's
it's
not
going
to
be
robust
right.
You
know,
so
I
I
think
that's
really
interesting
and
I
think
that's.
I
don't
think
operators
get
enough
of
that
credit
because
you
know
maybe
it's
partially,
just
because
they're
so
new,
you
know,
but
let's
I
guess
what
I
would
kind
of
wonder
then
is
like
okay.
B
C
A
C
Take
a
a
system,
that's
a
kind
of
a
complex
distributed
system.
That's
not
about
only
containers
running
on
kubernetes,
so
maybe
edge
the
there's.
A
set
of
devices
that
run
off
cluster
you
can
you
can
those
devices
could
show
up
as
kubernetes
resources
and
you
could
manage
and
control
those
devices,
and
you
could
even
use
something
like
a
type
of
controller.
That's
built
around
an
ansible
run
time
so
that
your
your
sort
of
control
plane
loop
is,
is
a
an
ansible
playbook.
C
Plane,
yeah
get
keeping
it
sort
of
practical
like
these
are
things
that
people
have
to
do
already
today,
other
you
know
other
examples
might
be.
You
want
to
leverage
just
a
sas
service
that
it's
somewhere
out
there.
You
can
build
a
a
resource
that
that's
a
proxy
for
that
service
and
create
policy
and
a
control
plan
around
how
you
access
that
service
as
a
as
a
custom
resource
and
again
it
kind
of
it's
a
real
thing.
Applications
today
have
to
coordinate
some
of
their
work
with
with
a
sas
service.
C
You've
got
some
notion
of
a
feed
of
data.
You've
got
some
notion
of
actions
that
you
take
when,
based
on
certain
events.
Now
that
there's
there's
some
common
patterns
there
that
you
could
apply
to
a
whole
set
of
of
of
different
domains.
That
I
is
where
it
does
to
me,
get
really
interesting,
but
you
know
kelsey.
D
C
An
an
idea
of
it's
just
a
physical
world,
so
you
you
talk
about
the
io
itot
convergence,
which
is
another
buzzword
where
ot
is
operational
technologies,
operational
technologies
like
where
technology
and
the
real
world
meet
so
servo
motors
connected
to
a
network
to
to
you
know,
change
the
flow
of
a
big
of
air
or
liquid
through
a
pipe
or
something
like
that.
That's
an
operational
technology.
C
You
could
imagine
a
world,
that's
really
just
managing
physical
infrastructure,
but
a
control
plane
running
on
kubernetes.
So
there's
no
output.
The
application
is
like
your
your,
whatever
your
your
factory,
but
the
the
control
plane
is
sitting
supported
in
kubernetes
and
a
very
different
look
or
view
of
the
world
from
what
you
think
about
kubernetes
and
running
pods
and
applications
and
in
containers.
A
So
we
have
a
question
here
that
I
think
is
kind
of
relevant.
Do
you
think
there
will
be,
or
are
there
already
other
kubernetes
distributions
similar
to
openshift,
but
serving
a
different
purpose
in
user,
to
which,
I
would
say,
there's
different
versions
of
openshift
to
an
extent
right
like
different?
You
know
footprints
that
you
can
use
for
those
purposes
but
like
when
I
think
hpc
like
one
like
the
super
computers
right
like
I
don't
think
those
are
running
kubernetes
right
like
or
are
they
no?
Some
are
some
aren't.
C
C
And
you
could,
you
could
say:
openshift
has
a
focus
on
the
enterprise
and
enterprise
applications
to
make
it
super
broad,
but
pick
a
specific
use
case,
and
that's
all
that's
already.
It's
already
a
possibility
and
you
already
see
that
to
a
degree
scaling
kubernetes
up
or
down
tailoring
it
to
a
particular
form
factor.
You
know
some
interesting
stuff
at
cubecon,
around
cube
and
home
automation
right
very
much,
not
an
enterprise
world,
just
a
very
different
application.
C
Creates
overhead,
especially
in
the
I
o
path
and
if
you're,
trying
to
squeeze
every
cycle
out
of
the
system,
you
don't
want
to
include
any
additional
overhead
containers,
don't
introduce
that
same
type
of
overhead
because
the
application
is
confined
in
to
a
namespace
and
resource
controlled
with
secrets.
But
in
the
end,
it's
just
an
application
running
directly
on
the
linux
kernel
underneath
right.
C
C
Kubernetes
ability
to
be
tailored
to
specific
scheduling
requirements
is
an
example
of
how
you
could
see
these
worlds
coming
together
and
then
the
hpc
world
itself
is
evolving
to
take
on
more
and
more
gpu
accelerated
machine
learning
type
workloads,
which
is
already
something
that
we
focus
on
in
the
kubernetes
world.
So
you
see
these
these
places
coming
together
and
I
think
it's
really
interesting.
A
C
There's
the
the
host
processor
is
doing
more
than
just
placing
workloads
because
it
does.
It
is
optimized
for
a
certain
type
of
math
right
and
so,
but
but
that
control,
plane
logic
of
place.
The
vector
processing
on
the
gpu
and
the
integer
processing
on
the
cpu
on
the
cpu
is
is
like
again
oversimplified,
but
just
an
example
of
how
you
could
imagine
systems
evolving
so
yeah.
Absolutely,
I
think
it's
it's
a
really
interesting
space
and
there's
this
convergence
of
use.
C
Cases
that
that
draw
towards
okay,
maybe
kubernetes,
could
be
a
really
useful
tool
for
hpc
and
maybe
there's
a
a
scheduler
and
a
set
of
resource
controllers
that
are
very
gpu
centric
and
connectivity
centric.
That
would
be
the
right
way
to
tailor
a
cube
distro
for
hbc,
for
example.
Right
now
I
haven't
given
it
a
lot
of
thought
but
yeah
good
example.
A
B
So
I
did
have
another.
This
is
a
thought
I've
kind
of
had
for
a
while
is
like
is
what
would
you
say?
Is
there
a
strong
good
comparison
between
like
the
linux,
kernel
and
kubernetes,
because
in
in
my
mind
at
least
right?
They
they
share
a
lot
of
similarities,
and
you
know,
I
kind
of
wonder,
is,
like
you
know,
could
the
linux
kernel
essentially
evolve
into
being
something
like
kubernetes
or
you
know?
I
don't
know
if
vice
versa
is
quite
the
right
word,
but
like
or.
C
B
C
Well,
I
mean
they,
they
live
at
different
layers
in
the
stack
and
so
there's
there's
probably
real
value
in
keeping
some
separation
and
allowing
these
two
independent
layers
to
to
sort
of
evolve
on
their
own,
but
they're
tightly
interconnected
and
the
the
you
know
the
the
way
that
you
leverage
the
underlying
operating
system
at
the
cube
level
is
direct.
I
mean
it's
a
one-to-one
mapping,
you
do
a
little
bit
of
setup,
you
create
a
namespace,
you
do
some
resource
allocation
and
and
set
up
the
resource
controls
around
those
controls
around
those
resources.
C
You
pull
an
image.
You
make
sure
it's
connected
to
some
kind
of
a
virtual
switching
infrastructure
and
connected
to
any
pvs
that
it
might
need
the
storage
side,
and
then
you
launch
the
app
the
application
as
an
application
running
on
linux.
It's
just
all
that
stuff
sort
of
disappears,
and
now
you
have
this
little
vertical
slice
of
your
own
linux
host
sitting
underneath
you,
and
so
are
there
specific
things
that
we
can
do
between
the
two
projects
to
advance
them
both?
C
Absolutely
and-
and
it's
part
of
why
I
mean
I
don't
mean
to
make
it
a
commercial
for
for
red
hat,
but
it's
part
of
why
we
deliver
openshift
integrated,
because
we,
like
we
deal
with
this
every
day.
We've
got
dependencies
capabilities
that
are
driven
in
the
cube
layer
that
create
dependencies
on
the
underlying
operating
system
right
right,
so
we
have
to
do
that.
There
are
extensibility
notions
in
the
os
and
extensibility
notions
in
kubernetes
and
they're.
C
C
Exactly,
but
if
you
ex
extract
that
out,
it
fits
a
general
purpose,
machine
learning
workload
that
kubernetes
would
support.
Well
and
you
you
want
to
have
a
feedback
loop
between
that
that
controller
or
that
out
of
the
kernel,
sort
of
scheduler
hinter
and
the
actual
scheduler
itself,
so
that
there's
there
could
be
real
tight
integration
between
those
layers
and
maybe
you're
doing
that
because
of
all
the
applications
you're
running
on
kubernetes
and
you
want
to
intelligently
place
them
for
resource
consumption
concerns.
C
I
mean
clouds
aren't
cheap
and
if
you
don't
pay
attention
to
how
you
consume
cloud
resources,
it
can
get
really
expensive
really
quickly.
So
you
know
it's
not
just
turn
it
off
when
you're
not
using
it,
but
also
optimize
it
when
you
are
using
it
and
some
so
just
some
some
interesting
potential
examples,
there's
also
networking
and
storage
where
and
observability
where,
with
a
building
block
inside
the
kernel
like
ebpf,
what
could
you
do?
That's
connecting
those
different
worlds.
C
B
B
B
You
know,
and
obviously,
if
it
was
research
more
that
it
was
like
something
that
you
could
fire
up
and
and
make
work.
But
you
know
they
had
working
demos,
it
was
pretty
cool,
and
so
you
can
imagine
that
optimization
right
and
that's
and
kind
of
going
all
the
way
back
to
the
very
beginning
of
this
conversation,
and
for
me,
that's
hybrid
club,
like
you
know,
is
that
I
don't
know
where
the
stuff's
going
to
be
running.
But
it's
going
to
be
running
somewhere
and
I
have
guarantees
on
its
performance
and
to.
C
C
It's
terrifying
on
one
level
and
it's
not
performance.
It's
like
there's
policy
compliance
around
where
data
sits
and
soft
data
sovereignty
and
data
governance
like
there's
a
whole
set
of
things
that
could
become
constraints
around
how
you
build
this
system,
but
if
you
can
define
clearly
those
constraints
and
understand
how
how
they're
managed
everything
that's
within
bounds
becomes
within
bounds,
and
you
have
a
real,
flexible
system
that
that
still
is
operating
within.
You
know:
performance
promises
and
right
data
compliance
promises
and
all
the
things
that
are
important
well,.
B
C
B
Yeah,
okay,
cool,
because
you
know
I
I
think
this
is
hilarious.
So
hopefully
you
will
too
we'll
see.
So
I'm
gonna
share
the
slides
again
so
on
this
show
we
give
out
points
for
kind
of
watching
the
shows
and
filling
out
some
codes,
and
you
know
making
suggestions
for
the
show
and
that
kind
of
stuff.
And
so
then,
every
time
we
have
an
episode,
we
give
out
our
sweet
sweet
internet
points
which
at
the
moment
only
have
intrinsic
value.
B
But
we
we
we're
joking
around
about
our
liaison,
who
keeps
telling
us
the
same
story
about
where
we're
gonna
get
to
extrinsic
value,
but
so
narendev
top
of
the
stack
with
five
thousand
points.
Netherlands,
hackham
and
chris.
Just
by
way
of
explanation,
we
have
completely
made
up
how
to
pronounce
people's
nicknames.
B
So
you
know,
there's
there's
some
backstory,
you
know,
but
basically
what
I
do
is
what,
if,
with
the
forum
to
kind
of
protect
some
privacy,
I
I
give
people
a
place
to
just
say:
give
us
a
name
to
say
on
air,
and
so
we
have
noah
friction
with
3
800
points
and
sorry,
netherlands,
hack
them
with
4
900
points
and
then
joe
fuzz,
who
still
seems
to
be
a
little
m.I.a.
We
need
to
know
why
he's
yeah.
They
are
not
submitting
points.
D
B
We
they
did
not
collect
points
for
the
last
episode,
so
we
we
need
you
to
do
that.
However,
I
think
I
forgot
to
take
my
handy
handy
note,
so
that
I
could
put
the
points
codes
in
so
give
me
one
second,
and
I
will
do
that,
but
I
usually
have
the
links
pre
pre-allocated,
but
that
should
be
it
so
chris
thanks
so
much
for
coming.
We
really
appreciate
it.
B
You
know
I
I
like
when
we
can
talk
a
little
bit
about
you
know
like
the
future.
You
know
as
well
as
kind
of
the
practical
of
what
we're
doing,
and
you
know
I'm
really
looking
forward
to
red
hat
summit
next
week.
I
hope,
hopefully,
everyone
on
the
show
is,
you
know
in
the
audiences
and
then
kubecon
eu.
Despite
the
time
zone.
That
looks
like
there's
going
to
be
a
bunch
of
interesting
stuff.
B
B
B
C
A
C
A
A
B
C
Digs
into
some
details,
he
actually
is
going
to
talk
about
a
project
that
he
started,
which
is
looking
at
cube
just
as
a
control
plane,
so
coincidental
to
the
to
the
conversation
that
I
had
with
kelsey
but
but
shows
how
much
interest
there
is
kind
of
percolating
up
around
different
parts
of
the
cube
community.
So
cool.
B
A
Well,
thank
you
all
for
joining
out
there
in
the
crowd,
and
we
will
see
you
here
on
the
channel
here
in
a
couple.
Well,
not
a
little
under
an
hour,
we're
gonna
be
talking
about
day.
Two
operations
part
two
on
the
openshift
admin
hour.
Next
so
stick
around
and
when
in
doubt
subscribe
to
the
calendar,
because
I
know
time
zones
are
hard.
This
one
will
help
you.