►
From YouTube: Using Auto DevOps to Deploy to GKE Autopilot (Demo)
Description
Partner Solutions Architect Regnard Raquedan shows how you can use GitLab's Auto DevOps with Google Kubernetes Engine (GKE).
Connecting the GitLab Agent with GKE: https://youtu.be/8SeuvDZsPLo
A
Today,
we'll
see
how
we
can
use
Auto
devops
to
deploy
an
application
to
Google
kubernetes
engine
with
auto
devops.
You
can
simplify
and
accelerate
the
delivery
of
any
workload
to
Google
Cloud
I'm
Bernardo
Caden,
a
partner
Solutions
architect
at
gitlab
and
I
help.
Customers
and
internal
team
members
alike,
learn
more
about
the
tight
integration
between
gitlab
and
Google
Cloud.
A
Let's
have
a
quick
primer
on
auto
devops
with
gitlab,
auto
devops.
It
simplifies
your
process
and
saves
you
Time
by
automatically
setting
up
the
Integrations
and
your
pipeline
that
deploys
to
your
environment,
in
this
case
we're
deploying
to
gke
what
Auto
devops.
Does
it
detects
your
code,
language
automatically?
A
It
builds
and
tests
your
code,
it
scans
for
vulnerabilities
and
then,
like
I,
said
it
deploys
application
to
your
desired
environment.
Before
we
begin,
let's
make
sure
we
have
a
few
things
in
place.
The
first
one
is
a
gitlab
project
with
the
kubernetes
agent
configured
I
have
a
separate
video
that
shows
you
how
to
connect
the
gitlab
kubernetes
agent
to
gke
I'll
post
that
link
on
this
video's
description.
The
second
is
a
gke
cluster.
This
could
either
be
an
autopilot
or
a
standard
cluster.
That's
already
up
and
running
to
complete
our
task.
A
For
today,
we
need
to
do
four
major
steps
providing
that
we've
completed
all
of
the
prerequisite
activities.
The
first
step
is
to
configure
the
kubernetes
agent.
The
second
step
is
to
install
the
Ingress
controller.
The
third
step
is
to
configure
and
enable
the
autodevops
in
your
project,
and
the
last
step
is
to
deploy
your
application.
Now,
let's
get
right
to
the
demo.
The
first
thing
that
we
need
to
do
is
to
configure
the
agent
I've
previously
set
up
and
configured
this
gitlab
project
to
be
connected
with
the
gitlab
agent.
A
So
now
what
we
need
to
do
is
to
modify
the
config.yaml,
that's
in
the
gitlab
agents
directory.
How
to
do
that.
I
will
click
the
web
IDE
button
here,
which
will
lead
me
to
the
files
in
the
project
and
let
me
edit
the
files
I
will
look
for
that
full
directory,
which
is
gitlab
agents
and
then
the
folder
or
directory
I
had
created
is
auto
devops,
Dash
gke
and
there
you
can
find
the
config.yaml.
If
you
had
created
the
project
and
used
a
different
agent
name,
agent
name
will
be.
A
You
know
the
directory
directly
under
agents.
So
now
the
config.yaml
I
will
paste
this
freelancer
code.
Okay,
now
the
first
one
is
to
have
the
CI
access
property
under
under
that
is
projects,
and
then
the
ID
parameter.
The
parameter
is
set
to
have
the
path
to
the
application
project,
so
you
need
to
pick
that
from
the
URL.
In
this
case,
this
my
project
is:
let
me
paste
it
here,
all
right
so
now,
I
have
it
make
sure
the
path
is
complete
and
once
I
have
that
I
will
hit
commit.
A
A
It's
the
gitlab
dash
gke
dash,
Auto
devops
cluster
I
will
navigate
to
the
end
and
you'll
see
the
actions
conceptual
menu
or
the
three
dots
I
will
click
that
and
I
will
hit
connect
I'll
be
prompted
with
this
command
to
run
on
cloud
shell,
which
I
will
click
here
running
Cloud
shell
and
the
cloud
terminal
will
load
it'll
preload
the
command
that
was
just
shown
in
the
previous
dialog
and
it
will
just
hit
enter
and
now.
I
am
connected.
Now
remember
the
command
the
hell
command
I
had
shown
in
the
previous
screen
or
previous
section.
A
A
Now
that
the
Ingress
installation
is
done,
it
might
take
a
few
minutes,
so
you
have
to
wait
a
little
bit
but
you'll
know
it's
done
when
you
see
this
command
completed
and
it
should
have
like
the
load
balancer
installed
and
then
the
IP
addresses
might
take
also
a
few
minutes
before
it
gets
assigned
so
yeah.
So
this
step
is
now
complete.
A
Before
we
go
to
the
next
step.
We
just
need
one
more
piece
of
information
from
the
kubernetes
cluster,
where
we
installed
the
Ingress
controller
and
that
is
the
load
balancer
IP
address
to
get
there
go
back
to
the
Google
Cloud
console
go
to
your
kubernetes
cluster
section
and
from
that
cluster
kubernetes
cluster
navigation,
select
services
and
address.
A
A
All
right
now
we're
at
the
third
step,
which
for
me
is
the
most
tricky
part
of
this
demo
and
that
is
to
configure
Auto
devops.
To
do
that,
we
need
to
take
into
consideration
three
variables
that
I'm,
showing
on
the
screen
the
cube,
Ingress
based
domain,
the
cube,
namespace
and
then
a
cube
context.
We'll
enter
those
variables
in
the
project.
A
Now,
let's
configure
those
variables
in
the
project
do
that
navigate
to
the
settings
section
of
the
project
and
from
there
select
CI
CD
once
you're
in
the
CI
CD
settings
scroll
down
to
find
the
variable
section
and
then
click
expand
and
we
add
the
variables
by
clicking
the
add
variable
button.
Now
the
first
variable
that
we
will
be
configuring
is
the
cube
Ingress
space
domain.
A
Now
this
is
the
variable
that
will
help
Define
the
URL
of
the
project
which
which
we'll
use
to
access
over
the
Internet.
We
can
use
a
DNS
service
for
this
and
for
this
example,
we'll
use
this
sort
of
a
wildcard
DNS
service
called
nip.io.
Now
to
to
set
that
we
will
use
the
load,
balancer
IP
address
that
we
copied
earlier
and
then
append
in
dot
nip
dot
IO.
So
this
is
your
base
domain
in
rest
based
domain,
and
then
we
don't
need
the
protect
variable
flag.
A
A
A
So
we
create
commit
onto
the
master
branch
and
that's
it
once
the
changes
are
committed.
This
will
trigger
a
pipeline
and
we
will
see
all
of
that
Ops
in
action
to
navigate
to
the
pipeline
and
there's
a
link
at
the
bottom
of
that
page,
which
has
the
pipeline
number
I,
will
click
that
and
from
here
the
the
jobs
and
stages
will
be
displayed,
and
this
set
of
jobs
and
stages
are
configured
by
Auto
devops.
A
We
didn't
do
anything,
it's
already
configured
for
us
fast
forward,
a
few
minutes
and
we
see
it
at
the
pipeline
passed
and
from
this
page
we
can
also
see
all
of
the
jobs
in
the
stages
were
completed
now
again
to
re-emphasize.
All
of
these
were
configured
automatically
by
Auto
devops
and
ensuring
of
code
quality,
the
building
of
the
container,
the
review
environment,
the
security
testing,
and
then
the
browser
performance
testing
were
done
and
configured
by
Auto
devops.
A
A
And
from
there
we
go
to
environments
and
we
see
the
environment
what
we
set
for
this
project
and
since
we
only
used
deploy
straight
to
production
environment,
we
accomplished
today's
tasks
by
completing
four
steps.
The
first
step
is
configuring
agent.
The
second
step
is
installing
the
Ingress
controller.
The
third
step
is
configuring
and
enabling
Auto
devops,
and
the
last
step
is
deployment
to
gke.
A
You
can
see
that
autopilot
in
gitlab
and
gke
are
great
match,
because
you
can
accelerate
and
simplify
your
deployment
of
applications
and
workloads
to
gke.
You
can
also
take
advantage
of
features
like
pipeline
integration
and
security
automation,
so
that
your
team
can
focus
on
business,
productivity.