►
Description
Don't miss out! Join us at our upcoming event: KubeCon + CloudNativeCon Europe in Amsterdam, The Netherlands from 18 - 21 April, 2023. 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.
A
A
B
Hey
good
morning,
good
afternoon,
good
evening,
everybody,
my
name
is
Salman
Iqbal.
Thank
you
very
much
for
the
introduction
there.
Yeah
I
am
so
Monica
I
work
for
a
company
called
Appiah.
We
are
a
cloud
native
consultancy
and
we
have
we
work
in
the
cloud
native
ecosystem.
B
So
today
I'm
going
to
talk
to
you
about
how
do
we
scale
our
websites
which
are
running
in
kubernetes?
We're
not
it's
not
only
restricted
to
websites
just
to
do
with
all
workloads
that
you're
running
in
kubernetes
I
know
we
talk
when
we
talk
about
kubernetes,
there's
a
lot
of
talk
around
Auto
scaling,
so
things
that
can
automatically
Scale
based
on
some
traffic,
that's
coming
in,
perhaps
metric
or
whatever
it
might
be,
but
that
doesn't
happen
by
default.
There's
a
lot
of
work.
B
We
have
to
do,
there's
a
lot
of
configuration
we
have
to
put
into
our
into
our
system
and
what
are
those
things
how
we
can
do
it?
That's
all
we're
going
to
look
at
today.
B
So
it's
going
to
be
all
demo
and
hopefully
everything
will
work
and
if
it
doesn't
work,
don't
worry.
I
have
a
video
as
well
of
the
whole
whole
demo.
We
can
go
through
it
and
we
can
pretend
that
there
was
a
it
was
all
live,
but
I've
tested
a
few
times
before
as
well.
So
I
think
it
should.
B
It
should
be
all
good
if
you
have
any
questions
anytime
feel
free
to
ask,
and
you
know
we
can,
we
can
answer
as
you
go
along
if
I
know
the
answer,
I'll
try
and
answer
it.
If
I
don't,
then
we
can
search
up
the
answer,
the
normal
way,
which
is
using
Google
or,
if
you're,
feeling
adventurous.
B
We
can
ask
the
question
in
chat
gpt4,
how
about
that
and
you
can
decide
if
we
can,
if
you
can
search
ourselves
what
we
should
do,
but
it
should
be,
it
should
be
a
good,
laugh,
I
think.
A
B
Whatever
you
prefer,
we
will
do
excellent.
So
what
you're
saying
in
front
of
you
is
my
screen,
whatever
I'm
going
to
be
doing,
I'm
going
to
be
sharing
together.
So
here's
the
scenario
scenario
is
you're
running
a
website
and
that
website
could
be
anything
your
blog
could
be.
An
e-commerce
website
could
be
whatever
it
is,
and
a
lot
of
requests
actually
I'll
probably
put
a
put
some
diagrams
up
in
a
in
a
second.
B
If
you,
if
you're
giving
a
second
I,
shall
open
this
diagram
here
so
so
we
can
all
see
it
together.
One
second
last
just
double
check
yeah,
and
this
is
where
we
are
yeah
one
minute.
B
B
So
I
hope
you
can
see
this
I
know
we
all
know
all
the
various
components
how
things
how
things
work
in
in
kubernetes,
but
just
a
bit
of
recap
for
all
of
us.
What
we're
going
to
be
focusing
on
on
today.
Imagine
this
is
our
our
current
setup
of
of
our
website.
That's
running
so
at
the
bottom
you
can
see,
we've
got
some
pods,
let's
say
the
red
ones
are
the
pods
which
are
serving
the
traffic.
B
Is
your
it's
your
website
that's
running,
and
then
what
we
have
is
some
Services
which
are
sitting
in
between
in
the
middle
at
the
bottom
there
in
the
gray
bar
that's
the
service
service
is
basically
just
a
a
thing
that
sits
on
top
of
a
of
the
pods.
It
is
an
interface
and
that
deals
I,
think
of
it
as
an
internal
load.
Balancer.
B
If
you
have
multiple
replicas
of
your
pods
running
in
a
deployment,
you
can
use
our
service
and
the
service
acts
as
an
internal
load
balancer
through
traffic
to
one
or
the
other
parts
right.
So
something
needs
to
something
needs
to
do
that.
That's
where
the
service
sits
service
is
all
internal.
We
don't
expose
everything
anything
outside
the
cluster,
usually
using
a
service
we
for
that.
B
What's
what
we
use
is
an
Ingress
and
in
Ingress
is
what
I
would
call
it
an
external
load
balancer
and
the
purpose
of
the
Ingress
is
to
take
requests
coming
from
outside
of
the
cluster
and
send
it
over
to
the
container.
That's
running
our
website
and
that's
the
purpose
of
the
English
and
the
good
thing
about
the
Ingress.
Is
it
understands,
HTTP
requests?
So
if
somebody
says
Hey
I
want
to
send
a
request
to
www.cncf.com
forward,
slash
I,
don't
know
checkout,
it
will
send
them
it.
Can
it
can
understand
the
request.
B
You
can
look
at
the
headers
and
you
can
understand
a
request
and
make
the
routing
based
on
that.
So
we'll
look
at
the
Ingress,
we'll
look
at
the
service
because
we'll
create
this
and
we'll
look
at
the
Pod.
Now
the
thing
about
the
Ingress
which
we're
going
to
focus
on
on
today,
the
thing
about
the
Ingress
itself
is
here:
you
go
next
diagram
here.
We're
not
they're
not
supposed
to
be
the
slides,
but
I
thought
we'll
just
have
some
photos
of
what
we're
going
to
see.
B
The
thing
about
the
Ingress
is
ingress
usually
comes
in
in
two
parts.
There
is
the
Ingress
pod.
As
you
see
in
here,
the
Ingress
is
basically
a
normal
deployment,
so
you
would
have
you
can
pick
any
English
controller.
You
like,
in
this
case
we're
gonna,
look
at
nginx.
Everything
we
talk
about
today
is
open
source,
and
we
also
have
a
link
where
you
can
try
all
of
this
yourself.
B
It's
all
the
projects
in
in
our
open
source,
then
nginx
in
response
we're
talking
about
is,
is
the
open
source,
nginx
Ingress
pod,
and
the
point
of
this
is
yeah
at
the
point
of
this,
is
that
when
it
runs
in
the
cluster
we
install
the
Ingress
control,
cluster
doesn't
usually
come
with
it,
and
it's
attached
with
a
service,
so
this
is
now
runs
inside
is
running
in
the
cluster,
so
anytime
request
comes
in
from
outside
of
the
cluster.
It
goes
to
this
pod
and
that's
absolutely
that's
fine.
B
The
problem
is
what,
if
you
get
millions
of
requests,
this
can
become
a
bottleneck.
Would
you
agree
with
that?
Annie
I
I
hope
you
would
write.
This
could
become
a
bottleneck
right
because
all
the
requests
yeah
all
the
requests-
are
going
to
this
one
pod.
So
if
that
happens,
there's
two
things
you
can
do
number
one.
You
can
always
have
many
Ingress
requests,
Ingress
pods
running
the
questions
that
are
coming
in
I'll
answer
in
a
few
minutes,
so
to
keep
them
coming
and
I.
Please
do
it
will
answer
in
a
few
seconds.
B
B
Can
do
that,
but
it
will
take
up
resources,
so
you
will
have
to
allocate
these
resources
and
these
pods
might
not
be
doing
anything
for
the
time
where
there's
not
much
traffic
coming
in.
So
it's
a
bit
of
a
waste
and
we
don't
like
waste.
So
what
we
should
do
is
scale
up
when
there's
lots
of
requests
coming
in
and
scale
back
down
when
there
are
no
requests
and
that's
what
we
want
to
do.
So
that's
what
we're
going
to
look
at
today?
B
How
we
can
do
this,
how
we
can
and
look
at
all
of
this
and
and
then
we
can,
we
can
scale
up
so
before
we
go
any
further.
There's
a
couple
of
questions
in
here
and
I'm
gonna:
can
we
can
we
go
through
that
and
is
that?
Is
that?
Is
it
okay
with
you?
Should
we
go
through
some.
A
Questions,
that's
perfect.
We
should
go
through
them,
yeah
and
I.
Think
the
first
one
that
came
in
is:
can
you
root
traffic
other
than
HTTP
or
https
using
Ingress,
for
example,
psql
or
request.
B
So
yeah
thanks
Shadi
for
the
question
I'm.
Usually
you
you
root
HTTP
https
traffic
using
Ingress
I'm,
not
sure
if
you
can
do
psql,
but
we
can.
We
can
check
that
later
later
on
in
the
Stream
we
can.
We
can
do
a
quick
search
ourselves
together.
Usually
we
deal
with
HTTP
and
https.
There
might
be
some
extra
controllers
because,
because
these
are
different,
Ingress
controllers,
some
controllers
might
be
able
to.
B
Actually
you
know
what
we
can
do
I'll
share
some
reference
with
you,
which
might
be,
which
might
be
handy
so
I
work
with
Appia
and
I
also
come
work
with
a
company
called
learnkates
shout
out
to
Daniel
from
Maroon
kids,
there's
different
kinds
of
Ingress
controllers
and
different
controllers
provide
different
capabilities,
and
so
you
can
see
in
here.
This
is
a
comparison
sheet.
This
all
of
this
is
open
source.
You
can
check
out.
B
You
can
contribute
yourself
as
well,
so
you
can
just
search
for
learnkates
research,
and
this
will
come
up
and
in
here
it
is
nginx
ingress
and
then
on
the
left.
You
can
see
different
types
of
routing
mechanisms,
so
maybe
some
of
them
might
support
it.
You
can
check
it
out,
but
I'm
not
sure
it
doesn't
look
like
we
can
so
maybe
different
kinds
of
Ingress
controls
could
or
or
could
not
support.
It.
I
hope
I've
kind
of
answered
that
that
question
or
not
so
hopefully,.
A
And
it's
Shady:
if
you
want
to
ask
any
more
or
you
have
extra
questions,
feel
free
to
pop
them
in
there,
and
then
we
had
another
one
from
laurentina's
that
they
are
curious
and
how
should
they
Define
high
traffic.
B
Oh
very
good
question,
so
that
question
is:
how
do
you
define
high
traffic
website?
I,
don't
even
know
something
is
hard
traffic
up.
That
all
depends
on
on
on
your
application
itself.
So,
for
example,
you
can
say:
look
high
traffic
is
if
I
get
I,
don't
know,
100
000
requests
per
minute.
That's
high
traffic.
That's
all
depends
on
what
your
setup
is
and
what
you
can.
B
What
your
setup
can
deal
with,
how
many
requests
it
can
deal
with
at
a
time
what
we,
for
example,
today,
what
we
give,
what
we're
gonna
say
if
we
have
we'll
I'll
share
the
metrics
in
a
second.
If
you
have
active,
100
active
connections
inside
each
nginx
pod-
and
you
know
you
can
test
this
out
yourself
and
trial
it,
and
you
can
see
how
much
memory
and
CPU
consumes-
and
we
know
like
100
requests
per
second
is
just
an
example.
B
A
Ports
than
80
40
43
I
used
it
to
Port
three
one:
zero:
zero
upd
there.
B
Okay
cool,
so
I
think
looks
like
looks
like
should
be,
should
be
good,
so
excellent.
All
right
sounds
good
to
me:
shall
We
Carry
On,
then
honey,
yeah.
A
There
was
a
comment
in
the
beginning
with
which
was:
it
is
like
al7
load
balancer,
but
there's
not
a
question
there.
But
obviously,
if
you
want.
B
To
say
yeah
yeah,
it
is
that's,
correct,
yeah,
I
think,
that's
that's
what
they're
saying
is
absolutely
right.
So
that's
a
lyricism
load
balance.
So
that's
what
what
is
doing
it
doesn't
understand.
So
services
do
like
layer,
4
stuff
and
then
Ingress
does
the
layer
seven.
So
that's
what
they're
saying
is
absolutely
correct.
A
Perfect
and
then
there
was
a
from
Dennis
to
share
the
materials,
show
the
Google
Doc
here
before,
but
if
there's
any
materials
we'll
get
them
linked
to
to
everyone
attending
as
well
as
maybe
you
can
share
some
learn:
more
resources
in
the
end
and
so
forth.
But
yeah.
B
B
What
you'll
see
is
we'll
deploy
an
application
and
like
a
normal
application,
as
you
see
in
here
and
then
we're
going
to
throw
a
lot
of
a
lot
of
traffic
to
it
and
what
we
want
to
do
is
we
want
to
scale
up
this
pod
so
that
and
that's
and
that's
how
we're
going
to
do
it,
there's
a
few
steps
for
it
which
which
we're
going
to
talk
about
as
we
go
along,
but
first
thing
first,
what
we
should
do
is
deploy
our
pods
right.
B
So,
let's
deploy
an
application
that
are
that
we're
going
to
deploy
to
the
cluster,
and
then
we
can
see
what
we
can
do
in
terms
of
scaling
here
we
go
so,
let's
just
make
sure
it's
all
nice
and
big
and
everybody
can
see
it.
If
you
can't
please
let
me
know
if
you
want
to
change
the
the
background
from
from
dot
to
to
White,
so
we
can
do
that
too.
But
here's
what
we're
going
to
do
initially,
what
I
need
first
is
a
kubernetes
cluster.
B
Luckily,
for
me,
and
for
all
of
us,
what
we're
going
to
do
is
we'll
you
can
use
any
cluster
you
like
in
this
case
we
are
going
to
use
mini
Cube
cluster
before
nothing
is
running
on
the
cluster
right
now.
So
let
me
just
make
sure
we
have
enough
space.
So
what
we
have
is
Cube
CTL
get
nodes.
This
is
minicube
right.
So
this
is
a
local
cluster.
That's
running
on
my
machine
and
it's
got
nothing
running
inside.
Well,
just
the
components
to
run
kubernetes.
That's
all
it
is.
B
We
have
nothing
in
there,
so
I'm
gonna
go
inside
in
here.
Cd
demo
just
make
sure
we're
all
in
the
right
place,
yeah
excellent.
So
let's
yeah
that's
where
we
are
okay,
cool,
so
first
things
first,
is
we
need
to
deploy
an
application
deploy
a
website?
Let's
just
pretend
this
is
our
website.
This
is
our
super
fancy
website.
That's
going
to
get
lots
of
traffic
and,
let's
start
with
here.
B
Let
me
just
stick
this
thing
here:
I'm
sure,
you've
seen
deployment
files,
Plenty
or
plenty
in
your
life,
and
what
we
have
is
we're
using
Stefan
prodan
shout
out
to
Stefan
product
pod
info.
This
is,
you
know,
I'm
sure
you
might
have
seen
this.
Basically,
it's
just
the
website.
It's
going
to
run
it's
a
static
website,
we'll
deploy
this
on
on
our
cluster.
It
is
a
deployment
so
deployment.
B
We
can
use
to
scale
replicas
if
you
want,
but
in
our
case
we're
only
going
to
run
one
deployment
and
that's
what
we're
going
to
do
so
we'll
take
this
we'll
deploy
it
and
we
got
some
other
information
in
here
around
like
pods,
which
are
running
labels.
But
the
point
is
we're
going
to
create
this
deployment.
First,
let's
go
so:
let's
go
Cube
CTL
apply
ysf
we'll
create
the
deployment.
Hopefully,
if
everything
is
all
good,
we
can
do
acute,
pods
and
containers.
B
Creating
there's
going
to
be
a
lot
of
that
during
the
demo.
Of
course,
we'll
just
make
sure
the
container
is
come
up,
is
taking
a
lot
longer
than
I
expect.
Luckily,
it's
all
come
up.
Okay,
so
the
Pod
is
not
running,
but
how
do
I
just
a
tip
to
share
with
you
all?
B
How
do
I
know
if
anything's
running
correctly,
usually
what
I
do
is
I
can
if
something
is
running
and
I
want
to
make
sure
hot
is
running
and
because
I'm
going
to
be
deploying
a
number
of
components,
I
want
to
deploy
a
service,
how
to
burn
Ingress
and
then
we'll
try
and
access
it,
but
instead
of
just
jumping
through
everything,
I
can
test
everything
out
right.
Let's
just
make
sure
I
got
a
qctl
port
forward,
because
this
is
my
local
I
have
actually
the
cluster
I
can
port
forward.
B
It
I
can
say
which,
which
resource
I
want
to
put
portfolio
which
is
a
pod.
So
this
this
is
the
Pod.
Let's
stick
this
in
here
and
then
what
I
have
to
do
is
this
is
the
port?
The
container
is
running
on?
That's
the
port.
The
container
is
running
on,
so
the
the
the
syntax
goes,
I
pick
any
port
on
my
machine,
Let's
see
that
and
then
the
the
con,
the
port.
The
container
is
earning
on
9898
in
this
case.
Let's
just
deploy
that
so
9898
now
this
is
forwarding.
B
So
if
I
send
a
request
from
my
laptop
onto
onto
the
here,
you
go
if
I
go
to
localhost
8888.
B
This
is
the
website
that's
running
inside
the
Pod
right,
so
the
first
step
is,
is
all
good
we've
got.
We
have
a.
We
have
a
port,
that's
running,
it's
giving
us
a
website.
This
is
the
website
that
people
really
want
to
visit,
because
they
want
to
see
this
cute
cute
little
creature
on
here
and
that's
what
they
want
to
visit
right
and
what
we're
going
to
do
next
is.
We
need
to
be
made.
We
need
to
make
this
available
outside
of
the
cluster,
so
you
can
send
requests
to
it.
B
B
What
we
have
is
another
there's
gonna
be
quite
a
few
of
those
today,
as,
as
is
always
the
case
I'm
sure
you
agree,
Annie
lots
of
yam
files,
we
we
will
create
a
service
and
a
service,
as
you
said,
is
an
internal
load
balancer,
and
in
here
there's
a
few
things.
We
need
to
make
sure
that
some
of
the
configurations
match
up,
and
that's
all
we're
doing
in
here
and
picking
the
right
pod.
So
this
is
the
deployment
that
we
created.
B
Has
these
labels
app
info
pod
info
and
then
what
we
have
is
this
bit
here,
which
is
the
the
target
board.
So,
when
I
deploy
this
service,
the
service
will
be
attached
to
this.
The
spot.
B
B
Right,
so
that's
what
we
are
doing
now:
the
service
should
have
been
created
again.
Service
I
can
do
that
just
make
sure
everything's
correct.
Now
this
is
the
type
the
service
type
load
balancer
and
if
there's
different
types
of
services
in
kubernetes,
there's
cluster
IP,
there's
load,
balancer,
there's,
node,
port
and
and
there's
one
more,
which
I
can't
think
of
right
now
and
then
headless,
which
is
the
the
smaller
service
yeah.
That's
right.
This
is
using
load
balancer
type
service.
This
is
running
locally.
B
If
this
was
running
inside
a
it's
a
cloud
provider,
it
will
actually
go
in
the
cloud
provider.
It
will
go
in
provision,
an
actual
load
balancer
and
attach
it
to
the
nodes
which
are
running
these
workloads
and
that
you
can
imagine
imagine
if
you
create
like
multiple
services
with
multiple
load,
balancer
types
and
you
end
up
with
so
many
load
balances.
It
could
become
quite
expensive.
B
You
could
have
a
lot
of
load
balances,
and
this
is
why,
in
order
to
expose
Services
outside
your
applications
outside
we
use
in
English,
but
we
need
the
service
because
we
could
have
multiple
replicas
running
now.
I've
deployed
this.
In
order
to
check
everything
is
correct:
I
can
do
the
same
thing
as
before
or.
B
Sure,
let's
just
do
that
right
now,
because
I'm
just
looking
at
the
other
screen
here,
you
go,
I
shall
stick
this.
We
can
I
can
stick
this
in
the
chat
right.
So
if
I
should.
A
B
This
in
the
chat
Nanny
you
can,
we
can,
we
can
share
it.
So
that's
that's
the
English
and
there's
actually
quite
a
few
other
things
in
here.
You
can
check
like
this
English
controller
comparisons
manage
kubernetes
comparisons.
This
comparison,
comparisons
on
service
meshes
and
yes,
it's
all
open
source
as
well.
Of
course,
please
feel
free
to
add,
send
pull
requests.
All
the
information
is
on
that
page.
B
Okay,
excellent,
well,
good
right.
So
this
is
the
service.
That's
running.
I
just
want
to
make
sure
service
is
configured
correctly,
so
I
can
do
the
same
as
what
we
did
before
we
can
do
9000
and
then
we
can
test
it
out.
So,
let's
just
quickly
do
that
localhost
9000,
and
as
long
as
we
see
the
same
page,
that
means
we
what
we've
done
is
we
have
done
everything.
B
Correctly
and
so
far
we're
looking
good
right,
so
we've
done
that,
but
what
we
really
want
to
do
is
install
it's
installed
in
Ingress
and
well
I'm,
going
to
deploy
a
few
components
first
and
then
we'll
break
and
take
questions
in
a
few
minutes.
If
that's,
if
that's
all
good-
and
it
will
just
deploy
all
the
components,
then
we'll
we'll
take
some
of
the
questions
in
a
second.
B
So
here's
the
thing,
though,
what
I
want
to
do
is
I
want
to
deploy
this
Ingress
and
the
Ingress
is
something
like
this
right,
so
I'm
going
to
show
you
some
rules
in
an
Ingress.
Let's
just
go
back
to
here,
so
you
saw
the
service
file
and
I'm
going
to
show
you
the
Ingress
file
and
the
Ingress
file
looks
something
like
this.
B
B
All
it
says
is:
if
somebody
sends
a
request
to
this
path,
so
just
a
just
a
base
path,
you
can,
you
can
put
anything
you
like
here,
blah
blah,
you
get
anything
you'd
like
you
can
put
anything
you
like
in
here
and
if
you
send
a
request
on
in
this
case,
we're
saying
to
the
base
part,
send
that
request
to
the
service
pod
info,
the
one
that
we
just
deployed
and
that's
where
we
want
to
send
it
to
now.
The
thing
is
also
what
the
request
should
be
coming
for
example.com.
B
So
if
somebody
sends
a
request,
this
is
what
we
are
actually
asking.
So
this
is
not
just
path
based
Roofing.
This
is
host
based
routing.
So
if
the
request
is
for
example.com,
then
what
we
can
do
is
basically
we
can
send
this
the
request
to
the
Pod
it's
to
the
actual
service
and
then
down
to
the
Pod,
but
here's
the
thing
if
I
apply
this
to
the
cluster,
so
I
can
apply
this
to
the
cluster
right
now.
So,
let's
just
stop
this.
We
don't
need
this.
B
We're
going
to
do.
Kk
is
the
Alias
that
I
use
on
my
on
my
machine
for
for
cubes
tlk,
apply
minus
f
ingress.com,
deploy
this
on
the
cluster,
and
it
just
goes
in
and
stores
that
information
inside
the
hcd
database,
but
it
doesn't
know
what
to
do
with
it,
because
there's
nothing
inside
the
cluster
that
tells
us
what
to
do.
There's
no
controller,
that's
running
inside
we
haven't
installed
anything.
We
haven't
installed
this
bit
yet
this
this
Ingress
pod
is
not
running
yet.
So
how
do
you
do
that?
B
Well,
we
can
install
this
on
the
cluster
using
we
can
go
to
their
website.
There's
a
number
of
ways
of
installing
it.
What
we're
going
to
do
is
we're
going
to
install
using
and
Helm
is
a
package
manager,
as
you
might
already
be
aware
of,
and
the
good
thing
about
Helm
is,
you
can
have
what's
known
as
Helm
charts
and
the
charts
allow
us
to
install
all
the
components
necessary
and
that's
what
we're
going
to
do.
So,
let's
just
quickly
install
this
so
I'm
going
to
do.
Helm
I
have
the
command
in
here.
B
I'm
gonna
copy
it
from
my
other
screen
because
I
have
it
there.
So
this
is
just
adding
the
repository
which
I
already
have
and
then
I
can
just
use
the
helm,
install
command.
Let's
just
stick
in
here:
I
use
the
helm,
install
command
and
from
that
repository,
I
can
install
the
nginx
Ingress
on
my
cluster.
B
So
you'll
install
a
bunch
of
things
in
my
cluster,
the
controller
that
it
needs
to
run
inside
a
pod
and
also
the
services
and
anything
else
that
might
need
to
install,
and
you
can
set
some
variables
at
the
same
time,
I'm
doing
I'm
just
telling
it
to
also
use
basically
watch
Ingress
is
without
class.
You
can
Define
that
class.
Then
Ingress
uses
but
I'm
just
setting
that
right
now.
B
So
once
once
I
run
that
what
I
should
do
is
basically
go
ahead,
get
all
the
get
all
the
bits
they
need
bring
all
the
yeah.
Here
you
go,
bring
all
the
configuration
down
and
apply
to
on
the
cluster.
What
I'm
doing
right
now,
just
for
demo
purposes,
I'm
installing
everything
in
the
same
namespace.
That's
where
it's
going!
Everything
is
going
in
the
same
namespace,
which
is
the
default
namespace
just
for
demo
purposes.
Usually
you
would
deploy
things
in
different
namespaces
and
that
that
is
the
right
way
of
going
about
it.
B
So
this
is
just
for
demo
purposes.
If
I
do
Cube
CTL
get
pods.
What
I
should
see
is
this
bit
here.
What
we've
installed
is
nginx
support
info,
and
this
is
an
nginx
Ingress,
that's
running,
so
this
is
the
controller
that
we've
deployed
right
so
so
far
we're
all
good
we're
deployed
the
the
Ingress
and
then
here's
what
we're
going
to
do,
because
this
is
mini
Cube.
This
is
running
locally
right
and
the
name
of
this
Ingress
is
nginx.
B
I
can
see
if
I
can
try
and
get
to
the
Pod
that
I
have
deployed.
In
order
to
do
that,
I
can
do
a
number
of
things.
I
can
get,
because
this
is
local.
This
is
local
right,
so
I
can
get
the
IP
of
the
mini
Cube,
and
that
will
just
that
will
basically
be
able
to
access
that
I'll
answer.
Some
of
the
questions
I
see
some
good
questions
are
coming
up.
B
I
will
answer
that
in
a
second
I'm
just
going
to
quickly
show
you
the
website
that
we
can
access,
because
our
our
thing
was.
If
somebody
sends
a
request
to
example.com.
No,
this
is
running
locally,
send
it
to
the
Pod,
but
I
can
use
a
new
command
from
so
we
have
Cube
CTL
to
get
a
service.
As
I
said,
Ingress
is
normal,
a
service
which
is
in
here.
You
can
see
this
since
this
service
here
load
balancer
service.
B
It's
called
main
engineering
same
address
right,
so
you
know
how
we
did
port
forwarding.
This
is
what
I
can
do:
mini
Cube
mini
Q
service,
similar
to
that
Main,
nginx,
Dash,
Ingress
and
dash
URL.
This
will
just
give
me
a
URL
locally.
I
can
use
to
access
the
website
just
to
make
sure
we.
What
we're
doing
is
absolutely
correct
right.
So
it's
going
to
run,
there's
a
there's,
a
spelling
mistake
in
here,
and
they
should
run
in
a
second
and
give
us
the
the
URL.
B
Here
you
go
he's
given
us
two
URLs
in
here.
So
I
can
access
this
and
see
if
the
website
is
there,
but
the
problem
is
I.
I
can't
do
that
because
I
have
this
host
property
inside,
so
what
I
can
do
is
I
can
curl
actually
and
let's
just
make
sure
this
command
is
running
as
long
as
this
command
is
running,
I
can
curl
it
I
can
do
this,
I
can
pass
in
a
header.
B
Are
we
coming
we're
building
up
to
building
up
to
the
part
of
scaling
in
a
second
example,
.com
and
then
I
can
stick
the
URL
that's
been
given
to
me,
and
you
can't
I
know
this.
Sounds
it's
not
as
exciting
as
seeing
that
the
cute
little
creature
that
we
have
in
the
in
the
in
the
URL,
which
let
me
see
if
I,
can
pop
back
onto
it's
not
as
exciting
as
this,
but
what
we
can't
do.
What
we
can't
see
is
is
well
there.
You
go.
B
That's
the
message
greeting
from
pod
info:
this
is
where
the
logos
is
coming
from.
I
hope
you
all
agree.
This
is
what
we're
doing
so
so
far.
What
we've
done
is
deployed
our
application
and
the
bit
that
we're
going
to
do
next.
Is
we
what
we
need
to
do
and
we'll
we'll
take
a
couple
of
minutes
to
answer
some
questions,
real,
quick
and
then
we'll
move
on
to
the
next
part.
We've
got
this
setup.
Complete.
B
We've
deployed
our
application,
we've
deployed
Ingress,
we
know
Ingress
Works,
we've
sent
the
request
to
it
and
we
can
see
it
running,
but
there
was
only
one
request.
We.
What
we're
going
to
do
in
a
few
minutes
is
pretend
we
have
not
pretend
we're
actually
going
to
do
a
lot
of
requests
and
see
how
we
can
scale
up
before
that
I'm
going
to
do
a
few
things.
B
I
need
to
decide
how
do
I
scale
up
so
I
need
to
pick
a
metric
that
can
scale
up
and
then
I
need
something
else
to
help
me
to
scale
up
and
then
I
think
Annie.
This
may
be
a
good
point
to
answer
some
questions.
There's
one
question
I
think
I'll
start
with.
If
that's
okay,
because
I
that's
yeah,
that
can
that
we
can
answer
really
quickly.
I
think
there's
a
question
on
can
I
add
multiple
ingresses,
if
possible,
are
there
any
precautions
when
using
it?
B
Yes,
you
can
add
multiple
ingresses
in
the
cluster.
What
you
have
to
do
is
in
here.
You
can
have
multiple
ingresses
and
let's
just
go
in
here
and
what
you
have
to
do
is
in
here.
You
have
to
Define
what
class
name
you're
using
what
do
you
have
to
watch
out
for?
Well,
the
the
things
that
you
have
to
watch
out
for
just
make
sure
you
use
the
right
English
class
name
for
the
English
to
use
I've
seen
some
examples
in
the
password.
B
People
have
run
multiple
ingresses
in
the
same
cluster
because
of
different
requirements
from
different
kinds
of
applications,
but
yeah,
there's,
there's
not
everything
that
you
have
to
watch
out
for
when
you
set
up
an
Ingress
is
is
the
same.
What
you
have
to
do,
for
example,
don't
declare
the
same
host
twice
but
I.
Don't
think,
there's
that
many
pitfalls
for
it.
That
I
wanted
to
answer
that,
because
it's
related
any
what
other
questions
we've
got.
So
we
can
quickly
answer
yeah.
A
To
check
out
as
well
that's
always
great
to
see,
and
also
there
was
a
question
before
to
get
that
link
to
link
to
the
previous
resource
to
LinkedIn
as
well
and
Jillian
helped
out
with
that
one.
So,
thank
you
so
much
there.
A
And
then
we
have
the
questions.
So
there
was
a
question
which
goes
as
how
does
kubernetes
know
that
I'm
running
my
kubernetes
in
a
cloud
provider
such
as
AWS
and
how
does
it
know
what
type
of
load
balancer
to
provision?
And
there
was
some
helpful
information
already
provided
by
another
commentary.
But
but
obviously,
let's
answer
the
question
here
as
well.
B
Yeah
so
yeah
I
think
Avinash
also
on
their
answered
questions.
So
when
you,
when
you
deploy
in
when
you
deploy
inside
kubernetes
in
a
different
cloud
provider,
what
happens
in
kubernetes
is
when
you
create
resources?
What
you
can
do
you
have
something
called
controllers:
that's
running
inside
the
cluster,
so
built-in
controllers,
like
the
the
replication
controller.
B
So
if
you
query
credit
deployment,
the
replication
controller
is
watching
in
hcd
to
see
if
there's
any
changes
for
it
and
it
creates
that
the
same
thing
happens
when
you're
doing
a
cloud
provider,
they've
got
their
own
controllers,
which
is
extra
bit
of
Logics
that's
running
inside
the
cluster.
So
when
you
deploy
something,
it
basically
acts
upon
it.
That
says:
yo
I
need
to
create
a
load
balancer,
and
it
will
tell
you
already.
You
already
know
if
you
want
to
carry
this
kind
of
load
balancer.
B
This
is
the
configuration
you
have
to
pass
in
order
to
create
this.
You
can
see
in
here
in
in
well
this
spec
in
here,
but
there's
metadata
information,
there's
annotation
section
also
which
which
we
haven't
included
in
here
in
The
annotation
section
you
might
have
to
give
it
some
helpful
hints
as
if
you
need
something
additional,
so
each
cloud
provider
will
ask
you
to
do
something
slightly
different
in
in
the
English
configuration.
So
the
Ingress
is
the
only
part
which
could
be
slightly
specific
to
different
managed
provider,
but
everything
else
stays
the
same.
B
A
Yeah
perfect
and
then
the
last
question
so
far
comes
from
Alejandro,
who
asks?
Is
it
necessary
to
deploy
a
service
in
load
balancer
mode?
If
I'm
using
my
cluster
within
a
public
cloud?
In
this
case?
Wouldn't
it
become
enough
to
configure
an
Ingress
pointing
to
the
service
and
the
load?
Balancer
would
assign
the
external
IP
to
the
Ingress
instead
of
the
service.
B
Oh
yes,
a
very
good
question
again:
yeah,
it's
not
I
I
just
did
it
as
just
to
show
but
yeah.
Definitely
not
it's
not
necessary
to
deploy
service
in
a
load
balancer
mode.
We
don't
want
to
do
that
either,
because
we're
gonna
have
an
Ingress
that
will
take
care
of
everything.
So
you
don't
have
to
you.
Don't
have
to
deploy
a
load
balancer
mode,
that's
absolutely
correct,
because
you
can't
do
any
authentication.
You
can't
do
any
of
that
stuff.
So
yeah!
That's
that's
what
you're
gonna
do
perfect.
A
And
we
got
a
comment
from
one
of
the
earlier
Christians
askers.
That
perfect
makes
sense.
Thank
you.
So
perfectly
done
there.
A
Yeah
and
then
we
have
Pearl
asking
that
if
this
repo
is
public,
can
you
please
add
the
GitHub
link
as
well.
B
Sure
I
will
do
I'll
share
the
link
in
a
few
minutes
when
we're
when
we're.
When
we
take
a
break
but
yeah,
there
is
there's
a
whole
blog
that
Daniel
Plan
should
put
together
on
this
stuff.
I'll
share
the
link
in
a
few
minutes,
and
then
we
can
you
can
you
can
check
it
there
is
that,
if
that's
that's
all
good
I'll
have
to
I
have
to
dig
it
up.
It's
it's
somewhere
here,
but
you'll
have
to
give
me
two
minutes
to
do
that,
but
we
can.
B
Thanks,
thank
you,
Ernie
for
keeping
it
ticking
along.
This
is
excellent,
stuff,
okay,
cool.
So
what
we've
done
so
far
is
deployed
our
application,
but
here's
a
bit,
though,
what
we
want
to
do
is
scale
our
Ingress
I'm
going
to
talk
about
Ingress,
but
you
can
assume.
All
of
this
also
applies
to
anything,
not
just
the
Ingress,
but
you
can
apply
this
to
any
kind
of
pod.
That's
running
inside
the
application.
B
You
can
pick
any
product
you
like,
and
you
can
do
that,
but
we're
going
to
talk
about
Ingress,
but
just
just
because
it's
a
good
use
case
before
I
can
do
that.
How
do
I
scale
up
is
the
question.
The
question
is
and
the
way
you
scale
up
is
you
need
what's?
This
is
what
we
want
to
do.
I'm
going
to
put
this
diagram
up
here,
you
go!
B
Imagine
we
have
a
deployment
which
is
our
Ingress
deployment
and
it's
running
some
multiple,
multiple
pods
right
now
and
it
says,
let's
just
say
it's
just
running
one
and
then
what
we
want
to
do
is
query
some
Metric.
B
So
query
is
a
metric,
I.
Think
there's
some
questions
service
measures
we'll
answer
that
later.
So
what
we
want
to
do
is
we
want
to
query
some
Metric.
But
how
do
we
get
this
metric?
Well,
there's
a
few
things
you
have
to
do
to
get
these
metrics
number
one.
Your
application
has
to
provide
these
metrics.
So
usually,
if
it's
a
it's
a
website,
you
would
create
an
endpoint
in
your
application
forward,
slash
metric
and
add
those
metrics
in
there.
B
Oh
this
one
real
Prometheus
monitoring
and
that's
what
we've
got
to
do.
I,
don't
know
if
people
seen
this
movie,
I
haven't,
but
apparently
it's
a
very
good
movie.
B
So
what
we're
going
to
do
is
we
are
going
to
use
another
open
source
project
called
Prometheus
and
the
good
thing
about
Prometheus
is
comes
in
different
parts.
We
can
install
it
on
the
cluster.
You
have
what's
known
as
a
Prometheus
server
and
that's
basically
the
central
component
for
everything
it
scrapes
the
metrics
and
stores
it
and
in
the
right
format,
in
the
format
that
it
makes
and
and
also
the
good
thing
about
Prometheus
is
it
can
talk
to
the
right
components.
B
Well,
when
I
say
right,
components,
I'm
talking
about
the
kubernetes
API
and
discover
all
the
services
that
are
running
in
the
cluster
and
all
the
pods,
so
you
can
go
ahead
and
find
it.
But
the
main
thing
is
all
the
containers
that
are
running
in
the
cluster.
If
they're,
exposing
metrics
on
an
HTTP
endpoint
on
usually
forward
slash,
metrics
path,
it
can
take
all
those
metrics
regularly
and
stories.
B
Now
that's
what
it
does,
and
this
is-
and
this
is
really
good
and
also
it
gives
you
a
really
cool
dashboard
which
we're
going
to
use
in
a
second.
So
basically,
what
we
need
is
somewhere
where
we
can
store
this
metrics
and
then
once
we
have
this
metric,
then
there's
another
component
inside
kubernetes,
another
kind
of
resource
called
the
horizontal
pod,
Auto
scatter,
there's
two
kinds
of
well
really
in
kubernetes.
You
have
three
kinds
of
Auto:
scalers
you've
got
the
cluster
Auto
scaler.
B
So
there's
a
component
called
the
horizontal
part
order,
scalar
and
then
that's
what
we
are
going
to
do
so,
there's
a
bit
there
we're
going
to
query
and
we
are
going
to
use
the
horizontal
portal
together.
So
how
do
we
store
these
metrics?
How
do
I
get
this?
Well
again:
lovely
Helm,
we're
going
to
use
Helm
and
we'll
install
this.
So
if
I
can
I
think
the
the
screen
is
is
big
enough
and
then,
if
I
do
Helm
in
school,
Helm
install.
B
Let's
just
do
this.
I,
have
you
know,
for
the
sake
of
saving
a
couple
of
a
couple
of
seconds
here,
we're
just
going
to
install
Prometheus
again
once
we
install
Prometheus,
we'll
have
a
bunch
of
PODS
that
will
be
spun
up
for
us.
So
let's
just
make
sure
everything
is
good.
Okay
get
pods,
so
you
can
see
in
here
as
I
said,
there's
it
installs
a
number
of
components
right.
B
The
bit
that
we
really
care
about
well,
but
we
care
about
pretty
much
everything,
there's
a
couple
of
bits
in
here
which
are
doing
different
things.
If
you
have
alert
manager,
if
you
want
to
send
alerts,
it's
if
you
haven't
tried,
Prometheus
I
would
highly
recommend
trying
it
out
if
you're
looking
for
for
a
solution,
there's
there's
many
solutions
out
there
of
course
check
it
out
on
landscape.cmcf.io
a
bunch
of
so
solutions
for
monitoring.
But
if
you
this
is,
this
is
a
really
good
one
to
get
started
with.
B
As
you
can
see
for
me,
it
was
quite
simple
to
start
with:
I
can
install
inside
the
cluster
using
Helm,
and
once
it
comes
up
I'll
just
wait
for
it
to
come
up.
Everything's
almost
This
Server
is
almost
there.
So
once
the
server
comes
up,
what
we're
going
to
do
is
then
we
will
I'm
going
to
start
collect
some
metrics
right,
but
what
metrics
can
we
collect?
B
B
I'll
show
you
in
a
second
luckily
for
us:
I
don't
have
to
modify
the
I,
don't
have
to
modify
the
nginx
deployment
itself
because,
luckily,
for
us
there's
some
metrics
that
already
exposes-
and
this
is
this-
is
the
nginx's
this
page
and
it
already
exposes
a
number
of
metrics
on
the
four
slash
metrics
endpoint
and
one
of
them
is
nginx
connections
active.
So
if
there's
active
Connections
in
there
I
can
scale
up,
but
we
can
Define
that
ourselves.
We
can
Define
our
metric.
B
We
can
say
hey
if
there's
like
more
than
100
active
connections
inside
each
deployment
scale
up,
because
that's
a
lot
for
that
to
take
in
that's
what
we're
saying
right.
So
we
don't
have
to
do
anything.
But
if
this
was
your
application,
you'd
have
to
go
in
and
you
have
to
make
sure
that
you're
exposing
the
right,
metrics
right,
for
example,
let's
just
go
in
here:
let's
just
make
sure
we
got
our
pause
up
and
running.
Luckily.
So
far
we
are
good.
So
everything
is
running.
Let's
just
check.
B
If
our,
if
I
can
do
minicube
service
Prometheus
server,
we
will
get
that
lovely
UI
in
on
which
we
can
go
in
and
have
a
quick
look
see
if
we
can
see
some
some
stuff,
that's
running
so
here
you
go.
It's
going
to
start
up
in
a
second
foreign
go
here.
We
are
so
this
is
what
it
looks
like
I
can
I
can
like
query
something,
let's
just
say:
if
I
want
to
see
how
many
CPU
cores
I'm
running
right.
So
let's
just
execute
this
and
machine
CPU
cores.
B
It
looks
like
there's
a
line
here,
but
really
all
of
these
are
the
labels
to
go
with
the
requests
that
we
made
and
you
can
see.
Oh,
this
machine
has
eight
cores
right.
This
is
the
value
that
is
giving
and
also
we
have
a
lovely
graph
in
here.
We
can
see
this
graph.
It
looks
good
right,
so
we've
got
the
graph,
but
how
about
the
bit
that
we
actually
care
about?
Well,
the
bit
that
we
care
about
the
metric
is
the
engine.
B
Magic
all
I
did
was
install
Prometheus
and
Prometheus
Master
grab
the
metric
understands
it
already,
because
the
metric
is
already
exposed.
It
picked
it
up.
So
let's
just
execute
this
and
let's
just
go
to
the
table
real,
quick
one.
You
know
we
we
sent
one
request.
Remember
that,
like
we
have
this
this
pod
info
open
that
we
send
the
request
to
so.
Basically,
there's
just
only
one
active
connection:
that's
running
that's
kind
of
cool,
but
we're
gonna.
We
will
we'll
pump
a
lot
on
there.
B
B
How
are
we
going
to
pump
a
lot
of
requests
in
before
that?
What
we're
going
to
do
is
used
Locust.
B
And
Locust
is
another
open
source
tool
that
you
can
use
written
in
Python
for
load
testing,
and
it's
really
great.
You
basically
have
the
Locust
file
I'm,
just
gonna.
If
you
haven't
checked
it
out,
definitely
check
it
out
if
you're
looking
for
something
to
do
with
Locust
I'm,
just
going
to
briefly
show
you
there's
just
an
example
in
here:
if
you've
written
python
before
might
seem
familiar,
if
you
haven't
is
kind
of
straightforward.
In
this
case
we
can
define
a
locust
file.py
in
there.
We
can
write
all
the
configuration
hey
go
to
this
URL.
B
Go
to
that
URL
there's
how
many
users
I
want
to
have.
This
is
how
many
concurrent
users
I
want
to
have.
You
can
write
this
and
the
good
thing
is.
We
can
do
this
in
kubernetes
as
well.
How
can
we
do
this
in
kubernetes?
Well,
I'm
glad
you
asked-
and
this
is
how
we
can
do
this
in
kubernetes
we
can
write
this
configuration
first,
we
can
deploy
more
yaml
file
Locus
itself,
because
it's
basically
a
python
package
right.
So
that's
the
python
package
you
can
install
using
Piper.
We
can
run.
A
B
That's
good
Locus
will
run
our
cluster,
but
if
you
wanna
and
then
we
have
a
service
everything,
because
we
need
to
have
that
UI
to
send
that
and
then
the
Locust
file.py
that
I
was
talking
to
you
about
the
one
that
we,
where
we
write.
What
we
should
be
doing
is
this
big
here,
Locust
config
map
config
map
is
something
which
we
use
in
kubernetes
to
store
some
information
and
config
mapping.
Here
is
what
we're
saying
is
just
send
the
request
to
example.com.
That's
what
we're
saying.
B
That's
all
send
the
request,
example.com
and
then
we're
going
to
ramp
up
right.
So,
let's
just
deploy
Locus,
it's
making
sense
so
far,
honey
I
hope
right.
So
that's
what
we're
going
to
do
excellent,
so
perfect.
For
me
this
will
keep
running
and
let's
just
go
to
the
right
place
where
we
will
be
going,
make
sure
we're
all
good.
B
B
B
The
thing
is,
we
have
the
horizontal
bottle
together
and
the
horizontal
scale
is
very
good
if
you
go
to
kubernetes
HPA
cuber,
that
is
HPM
kubernetes,
horizontal
part
order,
scale
up,
which
you
can
check
out
yourself
later
on
the
thing
with
the
horizontal
scaler
is
I
can
Define
in
here.
If
we
could
scroll
down
for
a
sec
to
the
right
place,
we
can
say
stuff
like
okay:
where
are
we
am
I
in
the
right
place?
Yeah.
A
B
Can
say
stuff
like
hey
if
the
if
the
memory
goes,
if
the
CPU,
if
the
applications
contain
consuming
more
than
50
of
the
CPU
scale
up
or
if
you're,
using
this
much
memory,
scale
up
or
scale
back
down
what
it
doesn't
do
is
for
you
can
do
custom
metrics,
but
it's
a
little
bit
more
involved.
But
there
is
a
little
bit
easier
way
of
doing
all
this
stuff,
and
this
is
where
something
called
cada
comes
in
yeah
another
open
source,
kubernetes
event,
Driven
Auto
scaling
it.
B
B
So
what
we
can
do
we
can
deploy
this
in
the
cluster,
and
this
comes
in
multiple.
It's
got.
Multiple
Parts
too
I
have
a
diagram
to
show.
Let's
go
in
here
here
and
once
you
install
in
the
cluster.
What
it
has
is
a
few
things
has
a
metrics
API,
so
it
can
consume
metrics
for
us
we're
using
Prometheus,
but
it's
all
good.
This
can
consume
metric
too.
Instead
of
Prometheus.
B
You
can
use
this
and
then
it
has
the
adapter
to
make
sure
to
put
the
metrics
in
the
right
places,
and
then
it
has
a
controller,
the
bit
that
runs
inside
the
cluster
that
says
okay.
This
is
what
I
need
to
do:
installs
a
bunch
of
custom
resource
definitions
which
we're
going
to
touch
upon
and
also
the
thing
that
we're
not
going
to
cover
today,
but
something
that
you
should
really
check
out
is
the
scalers
for
cada,
for
example.
B
The
the
good
thing
about
is:
if
I
can
go
to
the
scalars,
you
can
have
a
bunch
of
scalers.
For
example,
you
have
something
like
Kafka
queue
out
sitting
outside
the
kubernetes
cluster,
where
it
might
be
sitting-
and
you
might
say,
hey
I
want
to
scale
up
if
there's
messages
more
than
100
messages
in
a
Kafka
queue,
and
then
you
can.
You
can
scale
up
based
on
that
and
you
can
Define
that
or
you
might
based
on
a
different
like
a
SQL
query
with
a
SQL
query
scale
up
on
that.
B
Well,
that's
what
cada
is
excellent,
so
definitely
check
out
open
source
project
cater
check
it
out
and
installing
it
is
the
same
as
before.
Really
what
we're
going
to
do
is
we
are
just
gonna
install
using
how
and
we'll
answer
some
questions
in
a
second
just
want
to
make
sure
we
got
to.
We
want
to
get
to
so
I'll
install
this
inside
the
cluster,
give
it
a
second
and
it
should
bring
up
all
the
components
that
we
need
and
clear.
B
So
here
you
go,
you
can
see
this
operator
is
starting
up.
That's
the
bit!
That's
going
to
figure
out
when
to
scale
it,
but
how
does
it
know
when
to
scale
well?
This
is
where
we
use.
Let
me
just
go
here:
something
called
the
scaled
object.
This
is
not
kubernetes
native,
but
once
you
install
cada
it
installs
these
custom
resource
definitions,
and
in
this
case,
what
I'm
telling
it
hey
your
target.
Is
this
main
engine
exit
Ingress
deployment
right?
That's
the
one
that
we
want
to
scale.
B
We
can
give
it
some
information
around
how
many
replicas
we
like
to
have
minimum
maximum.
What's
the
cooldown
period
after
they
can,
it
can
go
back
down.
What's
the
polling
interval,
one
or
one
minute
or
whatever
it
might
be,
but
the
main
thing
is:
what
is
the
trigger
and
the
trigger
is
talk
Prometheus,
so
we
want
to
go
to
the
Primitive
server.
Look
for
this
metric
name,
nginx,
active
and
some.
Well.
B
That's
the
metric
thing,
but
what
we
this
is
our
query:
what
we're
going
to
do
is
look
for
the
nginx
Ingress
active
connections
that
we
talked
about
before
match
it
to
the
name
over
one
minute
and
the
threshold
is
under
100.
So
if
the
requests
for
a
pod
go
over
100
active
connections,
scalar
and
it
will
decide
how
many
replicas
it
needs
to
have
and
that's
what
we
need
to
do
right.
So
that's
what
we're
going
to
do
so
if
I
go
in
here
and
let's
just
make
sure,
we've
got
the
right.
B
Pods
pods
are
all
running.
Everything
is
good
and
I
can
deploy
this
scaled
object.
Okay
y
minus
F
scaled
object,
so
the
scaled
object
is
going
to
sit
in
the
cluster
and,
let's
just
give
it
a
second
taking
longer
than
help.
Oh
there
you
go
even
if
it
takes
a
split
second
longer
when
you're
doing
a
demo
feels
like
an
eternity,
but
that's
what
we
are.
So
what
we've
got
is
everything
is
not
set
up.
We
have
everything
in
our
cluster.
B
How
do
let's
just
quickly
scale
up
because
I
know
we're
running
out
of
time.
So,
let's
just
scale
up,
but
there's
one
more
thing:
I'm
gonna!
Do
we?
What
we
want
to
see
is-
and
let's
just
go
in
here-
gonna
bring
up
the
locusts.
B
Let's
bring
up
Locust.
This
is
because
it's
deployed
as
a
service
as
well,
so
it's
going
to
bring
up
Locust
in
a
second
and
then
we'll
have
a
UI
in
which
we
can
send.
We
can
start
sending
information.
So
let's
just
put
this
on
the
side:
real,
quick.
Let's
just
do
that,
how
long
we
got
Annie.
How
are
we
doing
for
time?
We.
A
Have
10
minutes
left,
but
we
already
have
five
questions
to
answer
already
so
yeah,
okay,.
B
B
Okay,
excellent,
so
what
we've
got
is
a
couple
of
things
in
here,
so
we
have
this
thing.
We
have
Prometheus,
which
is
running.
So
let
me
just
quickly:
do
this
hey?
How
about
this
right?
Look
at
that
nice.
What
we're
going
to
do
is
start
sending
requests
when
we
start
sending
requests-
and
this
is
the
UI.
But
what
we
want
to
do
is
see
the
pods
scale
up
we're.
B
We're
not
gonna
just
do
an
accusative
get
pods,
that's
a
bit
boring
so
I'm
going
to
do
something
and
give
you
a
little
bit
more
fantasy.
So,
let's
just
quickly
go
to
the
the
UI
the
place
that
we
are
yeah
scaling.
This
is
all
this
is
also
in
the
in
the
repository
and
we've
got
this
dashboard
that
that
Danielle
put
together
so
I'm
going
to
run
this
dashboard
and
you'll
see
that
in
a
second.
B
Oh,
that's
not
great.
B
How
about
that
right!
We
do
not
want
like
we
don't
want
to
see
this
is.
This
is
basically
pulling
information
from
the
cluster
itself,
all
the
pods
that
are
running
inside
the
cluster,
that's
always
showing
you.
So
these
are
all
the
KD
operator,
blah
blah
that
all
matches
up.
We
have
one
nginx
pod,
so
once
we
start
sending
requests,
what
we
should
see
is
the
number
of
requests
increasing
and
then
eventually
we
should
see
the
pods
scaling
up,
because
we've
defined
everything
we've
got
metrics
that
we're
collecting
we've
got
the
scaled
object.
B
We
have
the
pods
that
are
running
and
that's
what
we're
going
to
do
so,
here's
what
we're
going
to
do.
We
are
going
to
send
the
request
to
the
Ingress
directly
via
the
the
host
here,
which
is
the
service
itself
and
we'll
do
something
like
this.
So
let's
have
a
peak
users
of
2000.
Why
not,
as
you
can
see,
I
tested
this
up
spawn
10
users
per
second,
so
we're
going
to
start
swarming
in
a
sec
and
then
this
is.
This
is
Locust
that
will
start
giving
some
information
like
you
can
see.
B
It'll
start
ramping
up.
What
you
can
see
is
a
total
number
of
requests.
I'll
have
to
zoom
out
slightly
so
I
can
show
you
all
all
the
information
total
number
of
requests
make
it
a
little
bit
bigger
total
number
of
requests
that
are
going
in
and
response
times
it's
taking
a
little
bit
long,
because
what
we
want
to
do
is
if
I
can
execute
this
again
and
we
should
see
in
a
second
a
bunch
of
requests
coming
in.
B
B
What
we
should
see
is
our
look.
Ingress
is
already
starting
to
spin
up
right.
We
didn't
do
any
of
that.
You
saw
I,
didn't
do
this
because
kada
came
in
and
he
started
to
say:
hey,
you
have
a
bunch
of
requests
that
are
going
up.
So
if
the
requests
are
going
up
response
times
we're
going
up
to,
but
active
connections
were
also
going
up.
So
let's
just
quickly
execute
this.
B
Oh
you
can
see
this
faint
line
in
here,
but
you
can
see
that
active
connections
have
shot
up
real,
quick
and
what
we
have
now
is.
If
I
can
hop
back
onto
this,
you
can
see
three
three
parts
that
have
come
up.
This
is
I'm
not
making
this
up,
because
this
is
all
happening
in
the
cluster.
So
if
I
do
keeps
I
get
pods
and
we
have
a
bunch
of
these
pods
that
have
come
up
and
then
more
will
come
up
as
as
it
requires
what
Kayla
does.
B
Is
it
actually
calls
horizontal
autoscaler,
so
it
creates
that
auto
scaling
for
it,
and
then
it
updates
the
deployment
right.
So
it
updates
the
deployment
directly
and
then
it
basically
starts
scaling
up
that
it
needs
to,
and
this
is
what's
happened-
we've
gone
from
one
to
three
and
if
I,
if
I,
if
I
let
this
run
for
a
while,
you
can
see
like
three
are
dealing
with
it.
100
requests
per
second
they're
all
dealing
with
this
fine.
B
Usually
when
I
do
this,
if
I
were
to
do
it
like
I'll,
let
it
run
and
then
we
can
pop
in
the
horizontal
portal
to
scale
a
little
scale
up,
and
you
don't
just
have
to
do
it
for
this.
You
can
do
it
for
anything
you
like.
A
A
B
A
Perfect
I'm
great
that
the
demo
works,
there's
always
a
bit
of
nerve-rack
about
that.
So
there's
a
question
that
came
in,
which
is
the
first
in
line.
Please
explain
how
it
does
all
of
this
come
together
with
service
mesh
like
istio
for.
B
Example,
so
service
mesh
is,
you
can
inject
a
service
mesh
is
used
for
a
number
of
other
things.
This
Auto
scaling
is
not
part
of
service
mesh.
It's
not
one
of
the
one
of
the
one
of
the
features
of
service
mesh.
It
doesn't
do
that,
but
you
can
still
have
a
server
server
smash.
That's
running,
you'll
have
you'll,
just
have
to
make
sure
you
know
like
if
you're
using
the
right,
Ingress,
Gateway
or
or
the
Ingress
itself.
B
That's
the
configuration
that
you
have
to
do,
which
is
doesn't
touch
any
of
the
Auto
scaling
stuff,
but
yeah
the
the
istio
service
mesh
do
not
have
the
auto
scaling
capabilities
for
that.
You
have
to
use
this
I
hope
that
answers
the
question
a
little
bit
but
yeah
apart
from
that
everything
else
is,
is
the
same.
It's
not
it's
not
not
much
different.
A
Great
there
was
another
question:
I
thought
the
default
installation
of
nginx
Ingress
controller
using
Helm
will
install
Ingress
controllers
Daemon
set
that's
one
pod
per
node.
B
Yeah
this
I
think
it's
it's
a
deployment.
I
can't
I
can't
remember
you
could
be
absolutely
right.
It
will
start
one
quad
per
note,
but
the
thing
is:
I
have
one
node
and
here
is
minicube,
which
is
which
is
fine
and
there'll,
be
one
part,
but
it's
not
necessary
that
one
pod
will
be
able
to
deal
with
all
the
requests
that's
coming
in.
B
A
Yeah,
that's
good
and
then
Jose
asked.
Can
we
configure
the
time
interval
in
which
Community
scales
our
application
in
the
cluster
based
on
usage
metrics?
Let's
say,
for
example,
we
have
some
deployments
that
we
need
to
react
faster
to
an
increase
of
incoming
load
than
others.
B
They
are
looking
all
right.
Okay,
so
time
is
so
so
the
polling
interval.
Yes,
you
can
change
that
polling
interval.
I,
can't
remember
what
the
what
the
least
the
lowest
value
that
you
can
set.
Yes,
you
can
you
can
change
that
polling
interval?
You
can
go
much
faster.
That's
very
well
picked
up
there
and
yeah.
That's.
B
Oh
yeah,
you
can,
and
you
could
use
anything
you
like
for
for
visualization,
usually
for
with
Prometheus
grafana
goes
well,
I
know,
that's
they
both
run
kibana
grafana,
but
grafana
goes
quite
well
with
visualization
I've
never
used
kibana
with
if
I'm
using
Primitives,
but
but
you
can
yes,
you
can
use
that.
A
Great
and
then
Jules
asked,
is
it
possible
to
scale
up
across
different
Cloud
providers
instead
of
relying
on
one.
B
Very
good
question,
so
the
question
is:
can
I
use
I'm
I'm
going
to
assume
the
question
was?
Can
I
use
cada
to
scale
across
multiple
Cloud
providers?
Is
that
correct
I
think?
Do
you
think
that's.
B
I
think
it's
a
little
bit.
There
is
some
stuff
that
was
done
I'm
just
going
to
think
about.
Let
me
have
a
quick
look
or
we
can
quickly
pop
into
chat,
GPT
and
ask
it
I.
Think
if
you
do,
if
you're
doing
a
bike
club
across
multiple
Cloud
providers,
there
is
more
work
that
you
have
to
do.
There's
probably
some
projects
out
there
that
can
help
you
with
it.
I
can't
really
think
of
it
at
the
top
of
my
head.
B
A
Well,
the
cloud
is
definitely
very
big
topic,
so
they
should
see
a
lot
of
content
around
there
yeah
and
then
there
was
another
question
one
from
Diego.
If
there's
a
details
attack
that
sends
a
lot
of
requests,
how
we
could
avoid
Auto
scale
to
burn
the
budget
Waf
in
front
of
the.
B
Yep
web
application
firewall-
that's
that's
an
excellent
suggestion.
Yeah.
You
can
definitely
use
that
to
make
sure
that
you
protect
yourself
from
DDOS
and
there's
a
few
more
options
there.
So
yeah
Diego,
very
good,
very
good
point
yeah
right.
A
And
then
we
had
Oliver
asking
what
is
the
URL
of
the
gate,
repo
that
has
this
code
I
think
yes,
I
am
the
same
as
the
viewers
one.
If
we
can
share
it.
B
A
B
B
B
A
Is
the
difference
between
the
auto
scalers
provided
by
CSV
and
cada,
is
cater
compatible
with
traffic
Ingress
and
opa
cluster.
A
B
Yeah
so
I
think
as
Clarkson
I've
seen,
the
cloud
service
providers
are
are
integrating
cater
in
in
their
solution,
but
I
think
all
the
cloud
service
providers
also
don't
provide
this
by
by
default.
So
this
you
have
to
add
this.
On
top
of
it,
this
there's
nothing.
The
cloud
service
providers
provide
you
to
scale
your
application
like
that
I'm
just
sending
the
URL
as
well
yeah.
A
Perfect
and
then
to
the
last
question:
oh
there
we
go
it's
sent
so
for
people
who
are
in
YouTube.
The
link
is
bitly,
slash,
kcd
and
then
Dutch.
B
Scaling
Dash
scaling,
so
let
me
put,
let
me
put
it
up
in
here
here:
you
go,
that's
the
link
you
can
like
screenshot.
Do
whatever
you
like,
so
here's
the
links
appeared
Ohio
there
we
have
a
bunch
of
blogs
on
there
check
it
out
learntase.io.
So
all
the
resources
are
in
here.
The
demo
at
the
bottom
is
bitly
forward.
Slash
kcd
scaling.
So
you
can.
You
can
check
that
out
on
there
perfect.
B
It
all
depends
all
depends.
You
can
handle
the
requests
that
are
coming
in,
that's
fine.
Otherwise,
if
you
have
control
over
it,
you
should
scale
up.
I
mean
it's
not.
Ingresses
are
usually
very
good
at
handling
the
traffic.
If
you
have
the
right
number
of
instances
running,
sometimes
you
might
have
to
boost
up
or
not,
but
this
is
just
one
example.
You
should
really
look
at.
Do
you
need
to
use
this
for
your
workloads
too,
but
you
can
depending
on
what's
happening
in
your
cluster.
B
If
you're,
if
your
cloud
provider
controller
can
handle
it,
usually
they
are
good.
Usually
they
are
good,
perfect.
A
And
well
answered
there
on
quick
as
well,
because
we
are
out
of
time.
So,
let's
start
wrapping
up.
So
thank
you.
Everyone
for
joining
the
latest
episode
of
cloud
native
live.
It
was
great
to
have
a
session
about
operating
high
traffic
websites
on
kubernetes
and
as
always,
and
particularly
this
time,
also
really
love
the
introduction
and
questions
from
the
audience.
So
many
questions
great
that
we
got
to
through
them
all
and
as
always,
we
bring
you
the
latest
Cloud
native
code,
every
Wednesday,
so
in
the
coming
weeks,
stay
tuned
for
more
great
sessions.