►
From YouTube: MicroShift a lightweight OpenShift at the Edge Ricardo Noriega & Miguel Angel Ajo Pelayo (Red Hat)
Description
MicroShift a lightweight OpenShift at the Edge
Speakers: Ricardo Noriega de Soto & Miguel Angel Ajo Pelayo (Red Hat)
OpenShift Commons Gathering Kubecon EU
May 17, 2022 Live from Kubecon EU in Valencia, Spain
Full Agenda here: https://commons.openshift.org/gatherings/OpenShift_Commons_Gathering_at_Kubecon_Europe_2022.html
Learn more at: https://commons.openshift.org
A
A
And
we're
here
to
present
microshift
new
and
very
exciting
project
is
getting
a
lot
of
attention
lately
and,
as
we
say,
more
or
less,
it's
a
lightweight
implementation
of
open
sheet
for
for
the
edge,
so
I'm
gonna
do
we're.
Gonna
do
like
a
brief
introduction,
some
few
slides
and
then
a
cool
demo.
I
I
hope
the
demo
gods,
you
know,
are
good
with
us
and
yeah
to
give
you
a
little
bit
of
explain
a
little
bit
the
situation
for
the
past.
A
Over
for
over
a
decade
the
it
industry
has
been
trying
to
move
workloads
from
their
legacy
appliances
to
to
the
data
center
to
centralized
locations
to
the
cloud.
But,
however,
more
and
more
diverse
devices
are
connected
to
to
the
internet.
Those
devices
are
producing
huge
amount
of
amounts
of
data
and
it's
getting
important
to
to
get
computing
power
next
to
where
the
data
is
generated,
which
is
near
those
its
computing
devices
and
and
those
remote
locations.
A
A
Like
we
provide
distributed
worker
nodes,
we
provide
three
nodes
cluster
we
provide
lately
single
node,
openshift
right
and
in
the
other
side
of
the
spectrum
we
have
real
threads
red
for
edge
is
a
flavor
of
red
hat
enterprise,
linux
that
is
optimized
for
edge
computing
use
cases
and
when
I
say
optimize
this,
because
we
pick
certain
technologies
that
are
very
suitable
for
for
these
scenarios,
like
rpm
os
3
for
immutability
automatic
upgrades
and
rollbacks
in
case.
Something
goes
wrong.
A
Secure
onboarding
process
for
devices
and
this
operating
system
is
very
well
designed
for
field
field
deployed
devices.
I
will
explain
later
what
it
is
and
the
recommended
way
to
to
deploy.
Applications
on
on
rail4x
is
by
using
botman,
usually
static,
containerized,
workflows,
workloads,
so
microsift
comes
in
to
fill
the
gap
in
between
right,
as
I
mentioned
before,
to
try
to
manage
the
our
workloads
consistently
from
the
cloud
to
the
edge
there
you
go
and
what
is
microshift.
Microshift
is
a
small
form
factor.
Openshift
optimized
for
field
deployed
devices.
A
Our
team
has
been
really
focused
on
integrating
microshift
into
realforex.
It
provides
a
minimal
openshift
experience
and,
when
I
say
minimal
is
because
we
provide
a
lot
of
openshift
apis
like
routes,
security
context,
constraints
et
cetera,
but
we
don't
picture
microshift
as,
for
example,
a
platform
to
build
your
own
container
images
in
the
edge.
It
doesn't
make
make
much
sense
for
edge
computing
use
cases.
A
A
So
what
is
this
field
deploy
devices?
I
have
like
something
to
show
here.
This
is
a
jetson
nano
from
nvidia.
It's
really
really
like
a
this
is
the
developer
kit
that
has
some
connectivity
and
something
just
fall
off.
You
know
they're
very
cheap,
so,
and
the
question
is
that
why
are
they
so
different
from
from
servers
right
like
what
the?
What
are
the
characteristics
that
make
them
special?
So
we
all
are
kind
of
used
to
work
with
servers.
Servers
are
highly
standardized
and
highly
scalable.
A
You
can,
for
example,
plug
more
memory
like
more
storage,
accelerator
cards
and
so
on,
but
these
field
deploy
devices
are
usually
like
systems
on
a
board
systems
on
chip
or
single
board.
Computer,
sorry,
that
are
really
pre-integrated
and-
and
it's
very
difficult
to
you
know,
put
more
add-ons
on
top
the
scenarios
where
you
deploy.
These
field-of-play
devices
are
usually
remote
locations
with
no
physical
security
barriers
with
network
with
the
network
that
is
unstable
or
not
present.
A
There
is
no
out-of-band
management
system.
Probably
there
is
no
ssh
enabled
even
so.
The
way
that
we
operate,
these
devices
compared
to
servers
is
very
different
and
the
way
that
we
deploy
those
devices
is
is
completely.
You
know
the
opposite
from
from
servers
in
a
centralized
location
in
a
data
center
very
quickly.
This
is
a
how
we
picture
the
the
deployment
workflow
of
a
field
deployed
device.
A
So
I'm
a
customer-
and
I
want
to
deploy
my
edge
solution
right,
my
application,
so
red
hat-
has
a
software
called
image
builder
to
to
create
customized
images
of
red
enterprise,
linux
and
rail4h
as
well.
So
I
create
my
own
image
with
my
dependencies
and,
for
example,
microshift
right
then
I
go
to
my
hardware
vendor,
and
I
say
I
want
2
000
devices
and
you
can
put
this
image
on
on
those
devices.
A
Finally,
once
the
device
is
registering
to
my
system,
it
will,
for
example,
get
a
register
against
my
acm
advanced
cluster
manager
instance,
and
I
will
have
2000
devices
ready
to
get
my
applications
deployed
in
a
github's
way.
So
this
is
somehow
the
the
workflow
that
we
picture
how
we
compare
openshift
with
microshift
openshift.
You
can
think
about
openshift
as
this
vertically
integrated
solution.
A
A
Openshift
chips,
cluster
operators,
so
those
will
be
able
to
manage
the
infrastructure,
the
operating
system,
the
versions
of
different
components
and
so
on.
However,
microsift
is
for
is
designed
for
the
edge
for
those
customers
that
want
or
those
users
that
want
to
build
their
own
image
of
the
operating
system
and
want
to
manage
those
devices.
The
way
that
they
want
like
it
could
be
with
red
hat
fleet
manager
or
some
other
orchestrator
right.
A
A
A
As
you
can
see,
there
is
an
rpm
or
stream
image
when
you
build
rail48,
rpmos
3
will
contain
the
list
of
rpms
that
are
part
of
the
system,
and
that
is
immutable.
If
you
want
to
upgrade
the
system,
you
will
have
to
build
a
new
image
and
the
upgrade
will
be
done
automatically.
But
it's
part
of
you
know
it's,
although
all
that
software
is
completely
immutable,
you
cannot
change
it,
let's
say
and
finally,
just
to
show
you
that
microshift
is
about
the
glue
of
the
components.
A
B
B
B
B
Sorry,
yeah,
you
can
see
the
pods
running
like
the
bottom
ones
are
microsiev
workloads
like
we
have
a
service
ci,
the
router
core
dns.
For
now
we
have
flannel,
but
we
are
still
in
the
process
of
deciding.
What
are
we
going
to
use
there
and
also
the
cube
beard,
hotspot
provisioner,
but
that's
still
being
yeah.
B
B
So
I'm
running
an
access
point,
a
server
for
some
cameras
that
we
have
here
and
we
are
going
to
connect
in
a
second,
then
a
regular
service
and
an
offensive
route
that
which
is
going
to
be
announced
via
mdns
for
the
cameras.
So
the
cameras
will
be
connecting
to
the
to
the
access
point
running
in
in
microsoft
and
they
will
connect
to
the
camera
server
and,
and
then
the
application
in
there
is
going
to
be
analyzing,
the
the
video
of
it.
Oh,
where
is
my?
B
So
they
will
look
for
the
for
the
microsift
access
point
and
they
will
try
to
to
find
the
the
application
behind
dns
and
then
register
on
the
camera
server.
And
then
the
camera
server
connects
and
gets
the
video
feed
and
then
on
the
server
side.
We
have
a
a
small
application,
like
very
simple,
is
not
optimized
or
anything.
We
are
using
the
face,
recognition,
python
library
that
is
going
to
process
the
video
feeds
looking
for
faces
and
try
to
look
for
ricardo
me
and
put
put
a
name
and
yeah.
B
So
if
I
log
here,
the
the
camera
server
yeah
his
camera
already
connected
to
the
to
the
server
and
the
server
probably
connected
back,
hopefully
to
to
the
camera,
and
when
I
plug
this
one,
this
one
is
also
connected
to
the
access
point
running
in
microsift
and
then
into
this
service.
And
now
we
have
a
a
video
feed
here.
Microsieve.
B
B
B
B
B
B
You
can
even
embed
your
application
containers
into
the
image
of
the
container,
so
it
I
mean
it
will
not
need
to
download
the
the
images
of
your
application
containers,
and
maybe
you
just
manage
the
the
image
or
of
your
device,
and
you
tell
the
device
to
update
and
it
will
do
an
atomic
update
and
your
application
is
inside
and
and
you
can
even
have
off
offline
devices.
Even
that
is
not
better
yet,
but
you
could
even
do
that
and
yeah
that's
it.