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Description
In this session, Red Hat’s Graham Dumpleton discusses how to deploy JupyterHub on OpenShift and walks through the basics of Jupyter Notebook via JupyterHub.
With JupyterHub you can create a multi-user Hub which spawns, manages, and proxies multiple instances of the single-user Jupyter notebook (IPython notebook) server. The Jupyter notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based application suitable for capturing the whole computation process: Developing, documenting, and executing code, as well as communicating the results. Jupyter community created JupyterHub to support many users. The Hub can offer notebook servers to a class of students, a corporate data science workgroup, scientific or machine learning research projects, or a high-performance computing group.
A
A
Well,
hello,
everybody
and
welcome
to
another
openshift
Commons
briefing
this
time
my
colleague,
Graham
Dumbleton
from
Down
Under,
is
going
to
be
talking
to
us
about
deployment
Jupiter
hub
on
open
shift
and
we're
really
thrilled
to
have
Graham
doing
this,
because
many
of
you
are
using
Jupiter
notebooks.
A
lot
of
you
are
using
data
science,
workloads
and
ml
workloads
on
open
shift
and
testing
this
the
waters
out
in
this,
and
we
think
that
you
could
have
is
a
great
project
and
I'm
thrilled
to
have
this
background.
B
If
you're
already
watching
this
you're,
probably
well
aware
of
what
it
is,
but
it's
a
interactive
in
web
environment,
you
can
get
in
and
work
on,
documents
which
can
include
text
media
code
and
that
code
can
be
used
to
actually
pull
down
data
analyze.
It
chop
it
up
in
bits
and
pieces
and
then
present
it
in
a
graphical
form.
So
you
can
look
at
it
and
it
could
be
charting
and
so
on.
B
People
who
are
you
interested
in
using
Jupiter
notebooks?
You
have
individuals
who
use
it
for
self
teaching,
though
there
are
various
notebooks
out
there,
especially
in
the
Python
space
for
learning
about
Python,
for
example,
it
can
be
used
by
a
team
of
people
in
organization
who
work
together
in
analyzing
data
from
their
organization
and
trying
to
get
value
from
that.
B
One
example
is
in
financial
institutions
where
they
might
use
Dupin
notebooks
as
way
of
analyzing
stock
trading
data
from
a
previous
day
to
actually
try
and
work
out
new
algorithms
for
their
trading
system,
and
finally,
it
can
be
used
in
teaching
environments.
So
if
you
have
a
large
class
of
students
who
themselves
are
learning
about
data
analytics,
then
you
can
use
tuple,
because
the
mechanism
for
teaching
them
one
of
the
cutest
use
cases
or
uses
I've
ever
come
across
for
Jupiter
notebooks
was
actually
one
from
Singapore
and
I
love
visiting
Singapore.
B
So
it
was
a
bit
of
a
favorite.
Singapore
is
a
very
good
public
transport
system,
but
one
of
the
rail
lines
they
have
there
or
underground
lines.
The
trains
would
keep
stopping
and
they
didn't
quite
know
why
and
they
managed
accumulate
all
this
different
data
about
where
all
stoppages
were
which
train
it
was
what
time
of
day
and
so
on,
and
they
had
a
team
there
who
took
that
data
and
put
it
into
a
juvenile.
B
So
this
is
a
sort
of
example
where
you
can
take
data,
get
it
in
a
jiffy
notebook
and
to
arbitrary
analysis
on
it
and
present
that
data
and
come
to
conclusion
of.
What's
going
on
so
it'll,
be
really
good
in
a
company
environment
where
you
don't
have
existing
applications
to
work
with
your
data,
and
you
do
want
to
do
things
piecemeal
now.
The
topic
of
this
talk
is
is
not
just
joopa
notebooks.
It's
also.
This
thing
called
jupiter
hub
and
this
particular
comes
into
play.
B
When
we
talk
about
a
teaching
environment,
it
also
can
be
inside
an
organization.
We
have
a
small
team.
Jupiter
hub
is
a
means
of
running
up
instances
of
Jupiter
notebooks
in
an
environment
where
users
can
just
log
into
Jupiter
hub
and
they'll,
be
given
an
instance
of
Jupiter
notebooks,
and
so
they
can
use
that
may
be
an
empty
notebook
or
pre-populated
with
data
and
a
notebook
files.
B
You
can
upload
your
notebook
files
into
it
for
the
web
interface
or,
if
you
run
up
the
drip
notebook
inside
a
directory
which
already
has
those
notebooks
they'll,
be
already
visible
in
there,
and
once
you
have
that
you
can
then
click
on
any
of
the
notebook
files.
You
have
and
you'll
get
your
actual
interactive
notebook
where
you
can
start
working
away.
B
If
you
want
to
do
something,
there's
generally
a
package
out
there
for
doing
it
and
they're
easy
to
get
installed,
but
you
do
need
to
install
them
and
you
can't
get
a
terminal
up
inside
of
jupiter
notebooks
to
actually
install
the
extra
packages
you
need
in
your
notebooks,
so
running
a
droopin
notebooks
locally,
while
they're
good.
You
are
working
in
your
local
computer,
so
it
means
that
all
your
work
is
saved
locally.
You
don't
have
to
worry
about
how
you're
gonna
back
these
things
up
this.
B
B
They'll
need
to
have
the
same
Python
distribution
in
version,
and
when
we
talk
about
different
Python
distributions,
there
is
the
main
one
from
the
Python
Software
Foundation,
which
is
C
Python
and
there's
also
the
anaconda
Python
distribution,
as
they
have
different
package
indexes
for
downloading
packages,
and
those
package
indexes
aren't
quite
the
same
as
well.
So
you
can
run
the
differences
there.
But
overall
trying
to
do
it
yourself
on
your
own
box
from
scratch,
can
be
a
lot
of
efforts
to
set
up
and
maintain.
B
There
was
the
next
option.
The
next
option
you
can
use
is
to
run
docker
on
your
own
computer
docker
provides
a
means
of
running
applications
inside
of
what's
called
a
container,
and
it
isolates
that
container
from
other
applications
to
running
on
your
box.
But
more
importantly,
what
you
get
with
docker
is
the
to
bring
in
an
image
file
which
contains
all
the
bits
and
pieces
you
need
to
run
your
application
already
in
it.
So
the
Jupiter
project
people
make
available
a
whole
bunch
of
Japan
notebook
images,
a
minimal
notebook
one
is
just
a
Jupiter
notebook.
B
They
have
one
called
Saipa
notebook
which
has
pre-installed
you
note
a
whole
bunch
of
different
packages
suitable
for
data
and
links,
so
numpy,
scipy,
matplotlib
a
layout
book
and
some
of
the
other
ones
that
derive
from
it
also
have
the
option
of
being
able
to
use
Python,
2
or
Python
free
so
gives
you
that
flexibility
and
choice
and
to
do
it,
use
them.
So
it
can
be
a
great
way
of
starting
up
notebooks,
very,
very
quickly.
You
just
need
to
so
long
as
you've
got
docker
running.
B
So
that's
good
because
it
comes
with
everything
you
need
it's
a
particular
PI
from
distribution.
So
if
you
want
to
have
someone
else,
use
your
notebooks,
then
you
just
need
to
say:
go
run
this
docker
image
and
you're
off
to
get
good
enough
to
go.
These
images
are
read-only,
which
means
that
it's
you
can't
really
destroy
them.
You
can't
mock
them
up,
because
once
you
stop
them,
they
will
you
lose
it
all
the
work
that
you've
done
inside
of
them.
It
means
you
can't
wreck
them
up,
write
them
up
again.
B
The
next
time
I
go
all
the
way
back
to
where
it
was
before.
It's
an
isolated
environment
see
no
problems.
We
were
too
interfering
with
other
things
and
you
don't
need
to
maintain
these
things
because
people
are
providing
them
for
the
Jupiter
pro
book,
so
you
can
use
them.
These
docker
images
are
harder
to
customize
and
make
so,
if
you
want
to
add
in
additional
packages,
you'll
either
have
to
create
your
own
docker
image,
which
derives
from
it
notice
extra
bits.
Well,
every
time
you
start
up
you're
going
to
have
to
install
those
extra
packages.
B
These
packages
can
be
very
large
if
you're
on
a
really
slow
internet
connection
like
everyone
in
Australia,
then
you're
gonna
have
a
problem
pulling
these
images
down.
Some
of
those
images,
1.5
gigabytes
in
size
and
I,
wait
a
long
time
to
pull
them
down
over
a
really
slow
internet
here,
and
that
is
because
they
might
have
multiple,
multiple
Pyfrom
versions
in
there.
They
can
have
all
these
different
packages
that
you
don't
really
need
in
there
yeah
any
problem,
because
these,
just
when
you
run
them
up
a
running
in
container,
it
doesn't
mean
they're
isolated.
B
But
that
means
also
that
all
you
work
is
lost.
When
you
you
stop
it,
it
means
you
have
to
do
have
to
fiddle
around
with
trying
to
maps
volumes
into
the
docker
image
so
that
your
work
is
going
to
be
written
back
into
your
local
Beauty
can
be
saved
away.
Otherwise
you
have
to
configure
the
joopa
notebook
to
use
Abe
custom
contents
manager
install
those
files
elsewhere,
such
as
on
s,
free
or
Google,
Docs,
and
so
on,
and
one
last
food
issue
with
docker
images.
B
Always
you
have
to
be
concerned
about
is
that
when
you
start
them
up
is
the
access
to
them
secure
enough,
because
you
are
starting
up
a
web
server
from
this
docker
image
if
that
web
application
becomes
exposed
outside
of
your
box,
and
you
don't
secure
it
properly,
so
you
could
access
it.
Then
it
means
that
people
can
get
into
that
notebook
instance
from
outside
your
box
and
potentially
do
things
with
your
work.
B
So
what
other
options
are
we
go
for
can't
we
all
want
to
run
on
our
own
system
then,
and
this
is
where
we
can
start
to
look
at
software
as
a
service
or
hosted
options
now,
one
popular
way
of
very
quickly
having
a
look
at
notebook
if
you've
just
got
notebook
off
the
internet,
you
another
quick
look
at
is
thing
called
temp
NB.
This
is
a
project
which
is
done
by
the
Jupiter
project,
people
and
hosts
it
up
on
Rackspace.
B
You
can
go
here
and
what
will
happen
is
that
as
soon
as
you
hit
the
page
there,
it
will
give
you
an
instance
of
a
jupiter
notebook
now,
because
they
can't
know
in
advance
what
you
may
need.
It's
a
very,
very,
very
fat
image,
so
it
has
multiple
Python
versions
or
different
language
versions:
python,
ruby,
haskell,
r
and
for
the
different
language
run
times.
It
may
have
a
whole
lot
of
packages
which
are
pre-installed,
but
it
does
give
you
a
way
of
very
quickly
getting
up
and
running,
but
that
is
all
ephemeral.
B
After
a
while
it'll
go
away,
you
lose
all
your
work
so
great
for
looking
at
something
read-only,
not
great.
If
you
want
to
actually
use
it
for
developing
a
notebook
working
in
it.
The
next
option
is
to
go
look
at
people
like
Microsoft
and
Google
and
the
services
they
provide,
and
these
aren't
the
only
ones
available
there
are
other.
This
is
a
place
where
you
can
create
an
account
with
these
people
you
get
in
there.
B
You
get
your
own
little
space
where
you
can
work
in
and
usually
they
have
integration
with
their
storage
system,
so
that
automatically,
when
you
save
work,
it's
saved
away
and
it's
backed
up
by
Zim,
so
they're
the
two
main
options
you'll
find
for
those
now
these
are
really
good
because
someone
else
is
looking
after
them.
For
you,
you
don't
have
to
set
them
up
yourself
and
they
are
designed
for
use
for
multilingual
users.
B
So
my
understanding
is
that
you
can,
with
the
save
your
your
work
away
and
have
you
do
have
the
ability
to
have
someone
else
log
into
that
system
as
well,
and
you
can
share
you
a
note,
because
them
through
the
system
as
I,
understand
why
these
are
not
quite
so.
Good,
though,
is
they
are
still
a
shared
resource
model.
B
Different
people
are
going
to
get
in
there,
so
you
don't
have
any
visibility
of
how
the
system
is
implemented
underneath
and
one
would
hope
that
they
are
all
secured
so
that
your
own
little
work
is
separate
that
you
are
compared
potentially
competing
for
resources
on
the
one
system.
The
whole
system
is
essentially
out
of
your
control.
You
don't
know
how
reliable
is
your
relying
on
them
to
actually
is
keeping
a
system?
B
That's
working
and
you
probably
have
a
limited
ability
to
customize
it
or
limit
abilities,
select
which
versions
of
software
you
want
to
use
with
it
being
a
system
run
by
someone
else
and
not
on
your
own
premise.
You
have
to
worry
about
information
security,
I'll
see.
This
is
not
something
a
bank
is
going
to
use
if
you
want
to
work
with
share
trading
information
or
other
confidential
information
from
your
customers.
B
And
finally,
there
is
a
concern
here:
vendor
lock-in,
these
services
also
have
a
free
tier
and
what
they're
relying
on
is
they're
using
open
source
software
is
an
on-ramp
for
you
to
use
their
other
page
services,
so
you
may
want
a
database
product
to
store
all
your
data
in
though,
quite
happily
start
selling
that
to
you
and
then
means
you
asked-
are
locked
into
their
architecture.
It's
a
bit
harder
to
move
off.
B
So
what
about
self-hosting?
This
is
where
you
run
it
on
your
own,
your
own
machine.
Now
this
is
what
you're
doing
we've
joopa
notebook
directly
when
you
installed
it,
but
in
this
case
what
we
want
to
look
at
is
how
you
can
install
a
system
which
can
be
used
by
multiple
users.
At
the
same
time,
and
not
just
yourself
and
the
the
main
main
option
here
is
a
project
called
jupiter
hub
and
then
again
it's
from
the
Jupiter
project
team.
B
This
provides
a
system
where
you
can
log
into
it
and
you'll
get
a
jupiter
notebook
instance
to
play
with
now.
This
is
essentially
very,
very
similar
to
what
tempie
beii
is
set
up.
Timken
be
is
actually
a
separate
project,
but
it's
actually
simple
to
create
a
version
of
temping
be
using
jupiter
hub.
You
just
need
to
disable
the
authentication
you'll
see
how
I
do
that
later.
B
So
you
can
install
this
is
open
source
software,
so
you
can
customer.
However,
you
want
modify
it
for
your
particular
way.
You
want
to
do
it
setup
it
to
use
your
particular
authentication
mechanism
using
the
organization
you
can
use
setup
so
that
when
you
run
up
your
notebooks
they
have
persistent,
storage
and
and
so
on
or
use
your
custom
images.
And
there
are
many
many
deployment
options
you
can.
You
can
create
one
big
machine
and
run
everything
on
the
one
machine,
but
will
be
limited.
B
Therefore,
by
how
many
things
you
can
run
or
you
can
actually
start
to
farm
out
the
notebook
instances
across
machines
in
a
cloud
like
environment,
because
you're
running
this
yourself,
you
do
have
to
set
it
up
from
scratch.
You're
going
to
have
to
dedicate
infrastructure
to
it,
usually
because
you're
going
to
take
over
those
machines
just
to
run
this
and
there's
a
lot
of
effort
there
to
setting
up
setting
it
up
and
keeping
it
running.
That's
okay.
B
You've
got
a
IT
department,
but
if
you
don't
have
an
IT
department,
there
who's
going
to
do
all
this
work,
for
you
have
to
do
it
yourself.
You've
then
become
an
IT
operations
department
of
your
own,
which
it
may
not
be
what
you
really
want
to
be
doing
the
next
one
now
is
binder
now
this
actually
is
really
a
software-as-a-service
again,
it's
something
you
can
actually
go
out
onto
the
internet.
You
can
go
to
the
my
bided
org
and
give
it
a
URL
for
repository,
which
contains
the
notebooks
you
want
to
use.
B
So
this
works
actually
a
little
bit
different
to
the
temp
envy
service.
In
that
temp
MB
would
just
give
you
an
empty
workspace
with
a
whole
lot
of
soft
pre-installed
binder
allows
you
to
actually
give
it
a
repository,
and
it
will
build
for
you
on
the
fly,
an
image
which
incorporates
all
of
your
notebooks
that
you
want
to.
B
Actually,
work
with
and
also
install
all
the
different
Python
packages
that
you
want
to
be
installed,
which
you
need
in
your
your
notebook
that
might
take
a
little
bit
of
time,
the
first
time
it
does
that
because
it
doesn't
need
to
build
that
image
and
get
up.
This
is
something
where
you
can
get
onto
temp
to
my
binder
dog
and
use
it
and
we'll
give
you
that
ability
now
the
reason
I've
dropped
in
here
and
self-hosted.
Is
it
underneath
it's
actually
using
a
project
called
binder
hub
and
also
Jupiter
hub.
B
It
also
actually
relies
on
a
whole
bunch
of
others,
including
kubernetes
haraam,
and
all
these
other
bits
and
pieces
under
the
covers.
So
you
can
go
to
there
get
down
the
binder
hub
software
and
you
can
start
to
install
yourself
now.
There's
gonna
be
a
lot
of
work,
but
it
gives
you
that
that
capability
to
do
it
now
all
services
again,
because
it
is
a
software
as
a
service.
B
You
have
an
ability
to
customize
the
image
because
it
can
take
the
contents
of
a
git
repository
and
build
it
into
an
image
for
you
now,
but
it's
still
a
service.
It's
owned
by
something
else
say:
I
have
always
got
the
problems
you
had
before
with
information
security,
it's
a
shared
service,
how
reliable
is
and
so
on.
You
can
install
it
yourself
cuz,
it
is
open
source
software,
but
again
it
can
be
complicated
to
set
up.
B
You
have
to
ensure
that
in
an
environment,
even
in
your
own
organization,
you
set
up
all
the
authentication
security
correctly.
Now
one
of
the
things
we've
binder
harbor
when
I
look
at
it
is
that
well
isn't,
is
reinventing
a
pass.
You
think
about
what
a
platform
as
a
service
is
it's
the
idea
that
you
could
have
a
git
repository
somewhere,
which
has
a
whole
a
bunch
of
source
code
in
it
for
your
application,
and
you
can
tell
that
platform-as-a-service
here's
my
source
code.
B
You
go
build
into
a
image
or
some
other
format
for
me
and
get
up
and
running
for
me
and
I.
Don't
really
care
now,
that's
what
behind
the
hub
is
doing,
and
it's
doing
that
by
essentially
taking
a
whole
bunch
of
other
components
such
as
kubernetes
and
adding
in
components
own
components
of
its
own,
like
binder,
hub
repo
to
docker
and
all
these
other
bits
to
invent
its
own
pass.
B
B
I
can
just
log
into
my
existing
openshift
instance
and
say
here
is
my
image
which
I
might
have
up
on
docker
hub
and
you
can
get
it
up
and
running
and
I
haven't
had
to
do
any
extra
work
as
long
as
you've
got
the
quota
and
resources
in
the
account
with
it,
you
can
log
in
to
your
existing
account
and
get
it
up
and
running
and
all
go
now.
We
all
see
you
can
do
that,
but
we
want
to
make
this
somewhat
easier.
Now
we
can
do
this
through
templates.
B
Now,
in
the
case
of
binder
hub,
it
was
using
kubernetes
and
using
a
temporary
assistant
called
helm
to
do
it
now.
Helm
is
not
necessarily
the
simplest
thing
to
work
with
and
can
require
admin
rights
to
actually
get
it
installed
and
running.
So
getting
it
running
and
openshift
is
not
necessarily
a
simple
task,
but
it.if
does
has
a
simple
template
mechanism
itself
and
I've
got
a
whole
bunch
of
templates
here
which
I've
written,
which
allows
me
to
do
different
things.
So
I
can
install
a
Jupiter
notebook
from
an
existing
image.
B
I
can
already
be
using
the
existing
capabilities
of
OpenShift.
Build
up
from
a
repository
containing
all
my
notebooks
and
packages,
I
want
lists
which
pull
packages
are
installed.
I
can
do
all
that
for
this
very
simple
template,
so
I'm
just
click
on
it
and
I,
it's
very
simple
to
get
them
up
and
loaded,
but
I
can
do
the
same
thing
with
Jupiter.
I
can
install
drooping
up
and
say
run
it
with
existing
jopen.
B
No
image
or
I
can
actually
say,
go
and
build
me
a
new
job,
a
new
notebook
image
and
get
it
up
and
running
so
building
a
customized
notebook
image.
Very
simply,
just
click
on
template.
You
can
say
what
base
image
you
want
to
build
from
and
you
give
it
a
git
repository
in
a
way.
I'll
go
build
that
image
and
get
up
and
running,
and
that
is
using
this
thing
called
source
to
image
and
OpenShift.
B
That
is,
that
capability
of
taking
that
repository
running
it
through
this
builder
image
and
in
this
case
I've
got
a
builder
image.
I've
build
up
to
specifically
create
images
for
Jupiter
notebooks
and
it
will
then
go
off
and
deploy
it.
Nope
Jupiter
hub
deployment,
similar
thing,
I'm,
very
clear
click
on
template,
give
it
the
notebook
image
I've
already
created
and
get
it
deployed,
so
show
that
in
action
and
show
how
simply
is
I'll,
do
a
quick
demo
and
then
we'll
wrap
up
and
let's
see
what
Dian's
got
any
questions
or
anyone
else
has
joined.
B
B
So
I
got
a
completely
blank
open
account,
so
this
is,
if
I'd
had
access
to
my
existing
open,
shipped
account
inside
of
an
organization.
Now
you
know
totally
empty
I'm,
not
admin
or
anything
I.
Don't
need
to
do
any
any
special
access
to
do
this.
So
if
I
need
to
start
off
and
get
things
going,
then
I
only
need
to
do
a
couple
of
things
here
now.
The
first
thing
for
extra
security
reasons,
I'm
going
to
just
makes
a
little
bit
bigger,
create
a
service
special.
B
The
service
cap,
which
I'm
going
to
run
Jupiter
hub
under
in
particular
Jupiter
hub,
needs
to
be
able
to
run
up
extra
notebook
instances,
and
this
service
account
is
just
going
to
allow
me
to
do
that
by
giving
it
access
to
the
API
of
open
should
be
able
to
create
things.
So
I've
created
a
service
account
and
all
I
have
to
now
do
is
I've
got
a
set
of
resources
which
define
all
of
my
templates,
but
it's
also
going
to
go
off
and
build
me
all
my
images.
B
Now,
if
I
jump
back
to
my
user
interface
now,
I
can
go
in
here
and
see.
It's
going
off
or
bill
all
those
and
that'll
take
a
cut
a
few
minutes,
so
I'm
not
going
to
hang
around
for
it.
I've
got
some
already
pre-done,
so
I
get
over
to
my
other
demo.
They
say
they've
already
built
their.
The
quick
ones
took
a
minute.
Half
the
long
ones
took
a
bit
longer.
They
won
those
bottom
ones,
a
side,
pine
notebook,
intensive,
float,
notebook,
so
I'm
emulating.
What
Jupiter
project
does
there
and
Craig's
in
the
book?
B
Images
which
had
a
whole
of
stuff
pre-installed,
which
you
can
use
but
I,
won't
to
actually
deploy
that
now.
So
if
I
wouldn't
be
quiet,
I
just
go
to
my
catalog
touch-up,
for
my
templates
for
Jupiter
hub
and
I
can
just
deploy
it.
A
notebook
I
enjoy
minimal
notebook,
I'll,
give
it
a
password.
So
it
has
a
bit
of
security
in
there
and
that's
enforced
by
the
templates
and
that's
going
to
run
up
an
instance
of
my
notebook
so
very
quickly.
I've
gone
from
having
openshift
with
nothing
in
it.
B
B
B
B
That'll.
Take
a
few
minutes
so
we'll
skip
that
and
go
straight
to
a
running
instance.
So
here's
the
one
I
already
have
running
and
this
time
I've
got
a
little
custom
URL
on
it.
So
if
you
are
on
the
call
and
have
a
web
browser
handy,
you
can
go
to
this
address
temp
and
be
get
walk
on
HTTP
and
it
will
get
you
into
the
Jupiter.
So
I'm
going
to
do
that.
B
And
it's
going
to
so.
If
I
drop
back
to
the
web
console,
you
can
see
how
it's
already
started
me
up
at
my
own
Jupiter
notebook
instance,
and
in
anyone
who
comes
into
this
now.
I've
set
this
up
like
temp
in
B,
so
there
is
no
password.
Anyone
who
come
into
this
address
would
get
their
own
instance
of
a
notebook,
and
in
this
case
it
has
all
those
notebooks
from
Jake's,
wonderful
book
and
I
can
just
go
in
here
and
select
one
run
it
up
and
off
I'm
often
going
and
was
safe
to
anywhere
else.
B
No
one
else
has
dropped
on,
so
that's,
okay
and
I,
don't
see
they
could
just
run
this.
You
know
run
for
all
my
cells.
Work
on
that
and
do
I
think
I
would
normally
need
to
do
so.
That
was
very,
very
quickly,
both
getting
a
super
notebook
running,
but
also
building
an
image
from
custom
repository
files
or
even
just
running
up
Jupiter
hub
and
for
me,
that
is
a
much
simpler
way
than
doing
it
and
going
and
often
using
Jupiter
direct
Jupiter
does
have
a
village
to
work
with
kubernetes.
B
B
C
B
I,
don't
need
to
be
an
icy
operations
person
here
if
I
have
an
open
shift
account
in
a
instance
already,
then,
as
long
as
I
have
the
quota
to
be
able
to
set
up
the
size
of
Jupiter
hub
instance,
I
already
I
said:
I
want
for
the
number
of
users
I
need,
I
can
install
it
without
any
any
help
from
IT
operations.
People
I
still
have
the
ability
to
customize
that
deployment.
B
The
way
that
the
templates
are
set
up
is
you
can
drop
it
in
a
custom,
Jupiter
hub,
config
file
and
through
the
template,
or
you
could
even
actually
have
it
in
a
repository
and
itself
use
the
source
to
image
mechanism
to
build
up
a
custom
Jupiter
hub
image,
which
has
the
custom
configurations.
So
you
can
set
up
your
authentication,
your
requirements
for
persistent
storage
and
so
on.
You
can
set
all
those
up,
so
it's
not
a
fixed
way
of
doing
things.
B
It's
not
like
a
software-as-a-service,
there's,
still
a
great
level
of
customization
you
can
do
in
there
and
because
it's
simple
to
do
and
I'll
provide
I
will
be
on
the
track,
provide
all
the
structures
and
documentation
as
a
site
for
for
doing
always,
I
think
it's
a
good
choice
for
collaborative
in
a
company
or
even
people
in
education,
where
they
might
have
an
overshift
instance
already
internet
institution.
They
can
get
access
to
it
and
start
working
with
it
and
do
these
things
themselves
very
easily.
B
Now
we're
being
open
shift
and
open
shift
being
a
container
of
service
and
a
platform
of
the
service.
You
don't
have
to
dedicate
your
open
shift
instance
to
running
your
Drupal
hub,
notebooks
and
Ruppert
hub,
which
would
have
service.
You
can
start
to
deploy
other
workloads
in
here
and
one
example
of
this
is
some
work
being
done
through
another
project.
B
Looked
after
by
Red
Hat
called
rad
analytics
they're
doing
a
lot
of
work
with
being
able
to
run
spark
clusters
inside
of
open
ships,
so
you
can
potentially,
in
the
one
openshift
instance,
very,
very
easily,
deploy
a
spark
cluster
and
then
people
will
be
using
notebooks
which
run
up
with
Jupiter
hub,
which
are
communicating
with
that
cluster
that
you
can
racially
anything.
You
can
run
inside
a
container.
B
You
can
get
started
running
inside
of
openshift,
and
so
this
becomes
a
shared
resource
for
you
to
use,
and
not
just
amongst
yourself,
but
with
other
people
in
the
organization
as
well,
which
means
it's
not
dedicated
infrastructure.
You
can
share
infrastructure
costs
and
make
better
better
utilization
of
the
resources.
For
the
company
now
said,
all
you
can
do
whatever
you
want,
as
long
as
you've
got
the
quotas
and
limits
on
what
you
need
to
do,
and
of
course
all
is
this
open
source?
So
you
can
get
down
OpenShift
origin!
B
And
so
finally,
at
the
moment,
the
where
I'm
playing
around
ball
is
my
repositories
for
it.
They're
up
on
github
in
a
organization
called
Jupiter
on
open
shift.
So
if
you
are
interesting
that
you
can
go
there,
I
have
posted
various
blog
posts
on
the
open
sea
log
about
getting
Jupiter
running
in
Egypt
and
I'm
sure
we'll
be
doing
more
and
as
far
as
this
briefing,
you
can
find
a
lot
more
than
this
is
part
of
OpenShift
commons
as
well.
B
And
finally,
there
you
also
see
the
red
analytics
project
and
you
are
all
for
that
and
that's
that
is
providing
a
lot
of
things
for
machine
learning.
I,
don't
know
everything
they're
providing
but
there's
various
bits
and
pieces
in
there
for
using
spark,
but
also
different
ways
of
deploying
job
notebooks
as
a
means
of
visualizing
the
data
from
that
as
well,
and
so
that's
about
it
great.
A
Great
job,
Graham
I
think
that
was
really
a
great
tour
de
force
on
all
things,
Jupiter
related
and
and
if
you
really
do
see
that
there's
lots
of
different
options
for
this.
What
we're
seeing
in
the
open
ship
Commons
is
folks
from
both
the
edu
side
of
things,
the
education,
the
universities
and
enterprises
that
are
doing
interesting,
things
with
machine
learning
and
AI
and
all
kinds
of
fun
stuff,
as
well
as
all
of
our
old
friends
from
the
Python
communities
and
the
sci-fi
and
numpy
folks
using
Jupiter
stuff.
A
B
Yeah
open
shift
online
you're
not
going
to
have
sufficient
resources
in
the
startegies.
It
is
possible
to
get
a
single
jopen
notebook
instance
of
it.
They
they
tend
to
be
very
memory
hungry
when
you
to
actually
work
with
your
own
notebooks
and
data.
So
the
started
to
not
quite
enough
resource,
it's
useful
to
just
spin
it
up,
try
it
out
but
yeah.
If
you're
going
to
do
any
serious
work,
you
cannot
be
good
indeed
more
resource.
That's
where
the
protein
comes
in
and
you
can
you
can
get
this
up
and
running
on
protein.
B
Although
I
put
a
little
caveat
on
that,
there's
a
tiny
little
configuration
mistake
in
the
protein
at
demand
which
I've
been
trying
to
get
fixed
because
it
causes
a
little
bit
of
a
problem,
and
so
it's
not
quite
so
simple
to
get
them
up
and
running,
but
I'm
working
on
getting
that
fix.
But,
yes,
you
can
run
it
in
pro.
So
technically,
if
you
have
the
resources
in
there,
you
could
run
this
and
run
a
small
Jupiter
hub
clusters
for
us
more
people
and
get
up
running
there.
C
B
One
comment
you
made
about
the
future
Jupiter
hub:
I,
have
it
disabled,
but
one
of
the
things
actually
is
quite
exciting
in
the
Jupiter
space
at
the
moment
is
that
they
are
overhauling
the
web
interface
for
Jupiter
notebooks.
So
they've
got
this
project
coming
along
called
Jupiter
lab,
which
totally
overhaul
so
the
web
interface
of
Jupiter
notebooks
such
that
you
aren't
restricted
any
longer
for
having
a
single
notebook
on
a
page.
B
At
a
time
you
can
have
multiple
notebooks
and
in
a
tabbed
environment
within
the
actual
user
interface
I
have
got
had
that
running
and
it
looks
quite
interesting
but
I
disabled
it
at
the
moment.
That's
a
quite
interesting,
that's
coming
along
with
Jupiter
notebooks,
but
it
does
work
as
well,
though,.
A
So
the
interesting
thing
to
me-
and
it's
just
I-
mean
the
the
paid
Jupiter
hub
things
that
are
on
that's
on
Microsoft
Azure
or
the
data
lab
on
Google's
cloud.
Would
it
be
possible
for
someone
just
to
take
the
work
that
you've
done
and
convert
that
into
their
own
Jupiter
hub?
Offering
I
mean
it's
things
doable
and
you
could
just
customize
it
that
you
know
if
someone
were
so
so
wanting
to
create
their
own
version
of
data
lab?
Is
that
something
that
people
might
do
or
a
university
might
do
for
themselves?.
B
The
juban
have
so
far
is
quite
configurable,
so
I
didn't
I
in
my
demo
have
a
thing
with
authentication,
but
you
can
also
put
in
your
own
authentication
system,
so
you
might
have
to
construct
a
little
bit
of
the
web
interface
separately
for
your
actually
signing
up
and
creating
it.
But
you
can
have
SSO
hooked
into
Jupiter
hub
so
that,
if
you're
already
logged
in
via
this
separate
system
first,
then
the
SSO
works
as
soon
as
you
go
to
Jupiter
hub
instance
and
it'll
fire
in
opal.
B
A
I'm
gonna
look
to
see
because
III
think
I've
gotten
a
few
folks,
especially
from
the
edu
side
and
then
some
of
the
folks
in
the
financial
services
side
of
things
that
have
been
quite
interested
in
doing
something
with
Jupiter
hub
and
they
may
have
already
done
it
on
their
own
without
using
openshift
under
the
hood.
But
what
was
interesting
to
me
was
really
describing
it
as
you
can
have
two
for
your
hub
and
then
you
can
do
your
other
workloads
to
on
open
ship
and
I
know.
C
Had
a
question
well
I'm,
seeing
in
the
market
there's
a
lot
of
data
big,
you
know
big
data
analytics
without
the
data
scientist
and
they
know
that
they
can't
do
it.
They
can't
do
the
big
stuff
without
the
data,
so
nice,
but
they
don't
want
to
have
to
call
a
day
this
long
and
we
do
them
for
the
model.
This
seems
like
it
would
be
something
to
put
in
the
toolkit
them
yeah.
You
know,
could
you
build
up
a
reasonable
data
analytics
piece
without.
B
If
I
understand,
where
the
question
is
coming
from
you're
chopped,
dropping
any
bid
out
so
didn't
quite
get
all
that
the
intent
is
to
provide
a
way
of
doing
things
in
OpenShift,
where
you
have
much
much
control
more
control
over
how
you're
doing
things
compared
to
say
a
software-as-a-service.
The
idea
that
you
can
run
additional
workloads
in
there
to
support
what
you're
doing
and
customize
it-
and
this
is
where
you
bring
in
that
rad
analytics
project
or
any
other
project
which
are
providing
the
sort
of
capabilities
you
need
and
using
in
conjunction
with
this.
B
So
I'm
viewing
is
like
a
toolkit
approach,
as
opposed
to
a
software-as-a-service
where
it's
locked
down
and
works
at
only
particular
way.
So
I
think
that
whole
approach
to
things
is
sort
of
satisfying
what
you'll
think
you're
talking
about,
because
you
can
start
to
add
in
these
extra
bits
which
have
that
they're
a
domain
knowledge
of
what
you
need
to
do.
I.
A
You
know
that
company's
data
analytics
notebook
or
whatever
their
data
sources
and
have
all
the
hooks
and
bells
and
whistles
into
that
share,
Jupiter
notebook
and
then
they
could
customize
it
and
share
it
and
tweak
it
out
and
that
that's
really
one
of
the
wonderful
things
about
Jupiter,
notebooks
and
then
Jupiter
hub
lets
them
collaborate
on
these
things.
So
it's
it's
a
really
wonderful
platform.
It's
been
really
taking
advantage
of
a
lot
by
folks
in
academia
and
and
folks
at
work.
A
B
A
Some
pretty
cool
use
cases
so
I
hope
to
get
some
of
the
folks
on
and
the
different
industry
sectors
to
showcase
what
they're
doing
with
Jupiter
and
and
share
their
their
best
practices
too.
So,
hopefully,
we'll
have
a
few
more
follow-ons
with
this,
as
well
as
bring
in
the
right
analytics
folks
and
get
them
to
show
off
some
of
what
they're
doing
and
wealth
as
well.
A
There's
been
a
whole
bunch
of
talks
on
spark
on
tensorflow
and
using
Jupiter
notebooks
to
analyze
data
with
those
there's
tons
more
coming
as
a
new
project
and
community
developing
around
kubernetes
and
machine
learning.
That's
what
that
machine
learning
special
interest
group
is
all
about,
so
there's
lots
more
to
come.
So
thank
you
very
much
Graham
for
taking
the
time
to
do
this.
A
This
session
I'm
sure
people
will
find
it
useful
posted
up
on
blog
that
openshift
dot
or
dot-com,
rather
with
the
slides
shortly
and
they're,
going
to
have
our
first
machine
learning
special
interest
group
I
think
on
January
19th.
So
if
people
are
interested
in
joining
that
click
on
the
that's
below
and
I'm
sure
dude
real
hog
will
come
up
in
those
conversations
as
well.
So
thanks
again,
Graham
I
know
we'll
talk
to
you
all
soon.