►
Description
A demo of using Server Runtime + GA4K to spin up a JupyterHub environment, make changes and push code.
A
Hi,
everyone
welcome
to
another
server
runtime
demo,
so
today,
I'm
going
to
be
showing
the
ID
injection
capabilities
of
server
runtime,
some
here
in
a
python
project
where
you
can
see
I've
got
a
few
python.
Notebooks
I've
also
gotten
agent
configured
in
this
for
this
project.
In
my
kubernetes
classes,
if
I
go
to
infrastructure
in
kubernetes
cluster,
you
can
see
I've
got
a
agent
connected.
This
video
I
can
also
see
the
configuration
for
that
agents.
A
I've
got
certain
things
configured
with
setup,
remote
development
environments,
all
right,
so
I'm
going
to
go
ahead
and
so
I'm
gonna
go
and
like
anyone
would
create
a
new
Branch
to
start
a
change
right,
so
I'm
going
to
go
ahead
and
create
a
new
Branch
and
I'm
going
to
call
this
branch
test.
A
So
once
I've
got
the
branch
created,
I
can
go
ahead
and
create
a
workspace,
so
I
can
click
on
the
open
workspace
button.
Now
one
of
the
things
you'll
notice
is
that
this
has
a
Dev
file
or
yaml,
which
is
basically
a
standard
for
so
default.
The
standard
for
creating
developer
environments
and
I've
basically
taken
the
standard
python
example
from
the
registry.
The
default
registry
and
I've
stuck
it
here,
I
said,
uses
the
same:
Red
Hat
python
image
to
spin
up
a
python
environment.
A
Now,
there's
no
IDE
installed
in
this
environment,
so
I'm
going
to
go
ahead
and
what
I'm
going
to
go
is
say
open
in
workspaces.
A
I'm
then
going
to
select
an
IDE
to
inject,
so
I
can
inject
vs
code
or
Vim,
but
I'm
going
to
just
go
ahead
and
inject
Jupiter
Hub,
because
I'm
going
to
work
with
notebook
files,
so
I'm
going
to
go
say,
create
workspaces,
and
as
you
see
that
if
I
navigate
to
my
kubernetes
cluster,
you
can
see
that
a
namespace
and
isolated
namespace
has
been
created
to
run
this
workspace.
A
So
if
I
go
and
refresh,
you
can
see
that
it's
starting
up
I'm
going
to
pause
this
video
for
about
30
seconds
till
the
notebook
starts
up
completely.
A
So,
as
you
can
see,
my
workspace
is
now
running.
You
can
also
see
in
the
kubernetes
cluster.
The
Pod
is
running
as
well
for
that
workspace,
so
I
can
go
ahead
and
open
this
now.
The
first
thing
I
do
is
authenticate
with
gitlab.
In
order
to
get
into
my
workspace
and
make
sure
that
only
the
right
people
have
access
to
the
workspace
so
now
I
can
go
ahead
and
open
up
my
python
notebook,
so
I've
got
this
sample
python
notebook
here
and
then
just
like
any
other
Jupiter
notebook.
A
I
can
start
running
the
code
right,
so
I
can
go
ahead
and
run
some
of
this.
As
you
can
see,
it's
downloading
the
requisite
packages.
A
We
can
go
ahead
and
start
running
our
notebook,
so
I'm
gonna
go
ahead
and
import
all
the
libraries
I'm
going
to
run
this
function
and
I
can
then
actually
run
this
interactive
graph
as
well,
and
so,
basically,
you
could
interact
with
the
notebook,
as
you
would
right
and
then,
because
we
are
sort
of
automatically
authenticated
with
gitlab.
I
can
actually
go.
Make
changes
to
this
notebook
as
well
so
say
hello
to
the
door
and
save
my
changes
to
notebook.
Now
that
I've
saved
my
changes,
I
can
go
ahead.
A
Before
I
do
that,
I
need
to
set
up
my
email
address,
commit
and
then
click
push
right
and
so
now
I've
gone
ahead
and
pushed
my
changes
up
to
my
Branch
I
can
take
that
URL
and
create
a
merge
request.
So
once
I'm
done
with
my
workspace
I'll
iterate
on
my
code
and
make
changes
once
I'm
done
with
my
workspace,
I
could
go
ahead
to
The
workspaces,
View
and
click
on
terminate
and
that
will
start
dominating
the
workspace
and
the
namespace
as
well.
A
So
if
I
go
ahead
and
refresh
it's
terminating,
the
Pod,
as
you
can
see
in
kubernetes,
is
terminating
as
well.
It'll
kill
the
namespace
pods
and
everything
else,
and
you
can
see
now
that
the
workspace
has
been
terminated.
That's
it
for
my
demo.
Thank
you
for
listening.