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From YouTube: Edge Kubernetes and Healthcare: A Next-Gen Architecture that Scale... Benjamin Beeman & Jeremy Oakey
Description
Edge Kubernetes and Healthcare: A Next-Gen Architecture that Scales Across Thousands of Locations - Benjamin Beeman, GE Healthcare & Jeremy Oakey, Spectro Cloud
Edge computing and K8s have the potential to transform every industry, by bringing apps, data and outcomes closer to end-users, but it can be a significant paradigm shift for most enterprises when it comes to operationalization. For the healthcare industry, requirements such as security, availability and performance across thousands of locations are demanding for a new type of architecture and efficient tooling. Join this talk, if you're interested in learning about the requirements and gotchas of running and delivering K8s applications across thousands of edge locations, with 0 tolerance for mistakes. GE Healthcare's Senior Staff Software Architect, Ben Beeman and Spectro Cloud’s CTO, Saad Malik will discuss the lessons and how we need a next generation of edge architecture for the cloud native world. Beyond the theory, we will demo live the open source building blocks of managing the complete lifecycle at the edge, such as Cluster API, Libvirt, Docker and others.
A
Greetings:
everyone
everyone's
excited
lunch.
Your
revitalized
was
there
cookies
break.
Yet
no
okay
I'll
try
to
keep
you
awake,
so
I'm
presenting
today
with
my
friend
ben,
say,
hello,
ben
ben,
actually
couldn't
be
with
us
today.
So
what
I
have
just
to
sort
of
orient
you
is
we've
got
a
video
see
ben
was
nice
enough
to
record
his
section,
so
we're
going
to
play
that
for
you
and
then
I'm
going
to
pick
up
at
the
end
for
that.
So
we
all
get
to
watch
me
stand
here,
while
ben
does
his
awesomeness
okay.
B
And
welcome
I'm
benjamin
beeman,
I'm
a
staff
software
architect
working
for
ge
healthcare,
and
I
want
to
welcome
you
to
edge
day.
It's
really
great,
to
have
everybody
here.
After
two
years
of
not
seeing
each
other
in
person,
we
get
to
see
each
other
in
person,
except
that
I'm
not
there.
I'm
really
jealous
that.
I
couldn't
be
there,
but
I'm
sure
it's
really
exciting
for
you
to
meet
new
people
and
talk
about
one
of
the
most
challenging
aspects
of
kubernetes,
deploying
it
on
the
edge.
B
I'm
just
really
excited
to
be
part
of
the
conversation
I'm
accompanied
today
by
jeremy
okey,
the
vp
of
sales
for
spectacular
and
spectre
cloud
is
our
strategic
partner
going
forward
in
our
kubernetes
journey.
I
will
be
covering
our
requirements
and
jeremy
will
go
into
more
detail
about
the
solution
before
I
kick
our
story
off.
I
want
to
tell
you
a
little
bit
about
my
background
and
why
I'm
here
talking
to
you,
I've
worked
at
ge
healthcare
since
2011,
where
I
started
an
internship.
B
I
did
an
internship
at
diagnostic
cardiology,
where
we
were
building
a
restful
web
service
that
supported
html
front
end
displaying
diagnostic
cardiology
data.
I
was
able
to
join
a
leadership
program
when
I
started
with
ge
called
the
edison
development
program.
It's
a
great
program
because
you
can
switch
from
different
modalities
and
get
really
a
good
flavor
of
ge
in
general.
So
I
did
four
rotations
of
rotation
at
petamar,
a
rotation
at
ct,
and
then
I
liked
the
platform
team.
B
So
I
did
two
rotations
on
the
platform
team
and
then
took
my
off
rotation
role
with
the
ge
platform
team.
At
the
time
in
my
pet,
mr
rotation,
we
were
combining
the
pet
scanner
with
an
mr
machine.
Pad
is
really
great
at
detecting
areas
of
concentration
and
narrowing
down
where
cancer
cells
are,
and
mr
is
really
good
at
seeing
soft
tissue.
I
gotta
learn.
B
It
learn
things
about
how
they
detect
tumors
in
the
brain
and
then
the
mr
is
able
to
show
the
doctor
the
soft
tissue
trace
the
axiom
nerves
paths
so
that
they
can
determine
exactly
how
to
take
that
tumor
out
without
damaging
the
patient.
Then
I
moved
over
to
the
ct
recon
and
I
did
some
experimental
computation
algorithms
taking
data
from
a
ct
scanner,
and
this
data
has
to
be
reconstructed
into
these
3d
images
for
the
docker
and
this
reconstruction
algorithm
is
a
terribly
intensive.
B
Compute
algorithm
ct
is
constantly
looking
for
better
ways
to
optimize
these
computations
using
gpus
using
fast
compute
devices,
my
rotation.
We
took
a
an
algorithm
that
was
running
on
a
single
gpu
and
we
rewrote
it
to
run
on
multiple
gpus
so
that
we
could
determine
if
there
was
more
overhead
and
latency
or
speed
up
in
using
multiple
gpus,
then
I
moved
over
to
the
platform
team.
This
team
was
a
ge
healthcare
platform
team,
creating
common
solutions
for
all
the
modalities
in
ge.
B
I
worked
on
a
common
image
viewer
so
that
dicom
images
can
be
viewed
across
different
modalities.
Ct
x-ray.
Mr,
if
you
understand
what
dicom
is
icom
is
the
image
standard
for
medical
imaging.
I
did
take
an
outside
role
out
of
ge.
I
worked
for
a
year
for
a
company
called
tritec
which,
which
merged
with
central
square
and
became
central
square.
I've
worked
on
an
evidence
management
system
where
they're
tracking
evidence
into
the
police
department
and
the
different
chain
of
custodies
in
which
it
goes.
B
Public
safety
is
another
area
where
they're
incorporating
cloud
into
their
workflow,
but
they
still
have
several
reasons
where
they
can't
put
things
in
cloud.
They
still
have
to
have
on-premise
solutions.
Finally,
I
rejoined
ge
and
joined
the
ge
healthcare
edison
platform
team,
which
is
an
evolution
of
our
previous
platform
team
into
the
edison
platform.
So
I
currently
work
at
ge
healthcare,
the
platform
team,
where
we're
creating
edison
health
services
on
our
on-premise
platform,
that
we
call
the
edison
health
link
and
these
services
can
be
deployed
on
the
edison
health
link
or
in
the
edison
cloud.
B
The
edison
health
services
goal
is
to
service
all
modalities
at
ge,
such
as
ct,
mr
patient
monitoring
and
many
many
more
so
a
little
bit
more
about
the
edison
platform.
What
in
the
world
is
edison
well,
of
course,
we're
ge.
So
we
like
to
coin
the
phrase
edison,
because
you
know
thomas
edison
was
our
founder
at
a
high
level.
Edison
is
an
intelligent
platform
supporting
multiple
and
diverse
types
of
modality
applications
running
on
premise
and
in
the
cloud
across
ge
healthcare.
B
Essentially,
edison
is
an
ecosystem
for
our
internal
and
third-party
developers
to
deploy
apps,
new
and
old
to
healthcare
edge
locations.
Edison
is
a
compute
platform,
and
by
this
I
mean
that
it
is
the
engine
to
power,
complex
and
resource,
intensive
image,
reconstructions,
ai
and
other
resource
intensive
algorithms.
We
are
always
looking
to
optimize
speed
cost
and
provide
solutions
that
will
last
into
our
customers
future
endeavors.
B
The
resources
certainly
include
cpu
memory,
gpu
and
storage.
Sharing
these
resources
for
better
utilization
edison
is
also
seeking
to
have
a
unified
approach
for
developing
and
managing
solutions
across
on-premise
deployments
and
cloud
deployments
in
our
journey.
When
we
met
spectre
cloud,
we
were
looking
for
common
ways
to
package
and
deploy
applications
that
wouldn't
box
us
into
a
particular
type
of
technology
every
day,
we're
looking
for
the
best
ways
to
leverage
open
source
solutions
and
commercialize
solutions
to
better
enhance
current
applications.
B
One
of
the
main
goals
of
edison
is
to
be
an
enabler
of
legacy
applications.
Ge
healthcare
has
a
lot
of
powerful,
very
powerful
legacy,
applications
that
have
taken
decades
to
put
together
for
for
healthcare
solution
that
are
serving
patients
every
day.
These
applications
come
in
all
different
sizes
and
shapes
and
deployment
models
enhancing
upgrade
patching.
These
applications
can
be
a
huge
task.
B
B
I
also
want
to
take
a
brief
moment
and
talk
a
little
bit
about
healthcare
and
its
unique
challenges,
deploying
medical
devices
and
solutions
in
the
healthcare
industry
whenever
we're
trying
to
transform
technology
in
the
healthcare
world,
it's
important
to
consider
some
of
the
important
limitations
in
this
space.
You
know,
depending
on
where
you
are
in
the
world,
there's
different
regional
regulations
and
restrictions.
B
This
is
part
of
the
reason
that
we
have
the
requirement
to
be
able
to
run
without
a
direct
connection
to
the
cloud
we
need
to
be
able
to
deploy
fleet
manage
with
a
central
source
of
truth.
In
a
disconnected
world,
we've
mentioned
kubernetes
on
the
edge
and
in
edison.
This
is
what
we
mean
by
edge
in
our
platform
that
contains
kubernetes
and
stand-alone
vm
deployments.
B
This
is
deployed
on
physical
hardware
or
in
data
centers
that
are
located
at
our
client
sites.
In
our
case,
these
are
medical
facilities.
I
will
also
refer
to
the
edge
as
on-premise
as
an
on-premise
location.
All
of
these
terms
describe
the
same
thing.
This
is
a
local
edge
location
and
it
can
become
disconnected
from
services
that
are
hosted
at
local
cloud
providers.
It
has
to
be
fully
capable
of
running
independently
if
disconnection
occurs.
There's
also
other
concerns
when
we're
monitoring
systems.
B
When
we're
taking
data
off
the
system
to
pay
close,
we
have
to
pay
close
attention
to
phi,
which
is
protected
health
information
of
the
patient,
pii
information
that
may
personally
identify
the
patient
and
any
information
that
might
be
able
to
correlate
together
in
order
to
produce
some
phi
in
the
information
different
regions
around
the
world
have
different
unique
regulations
when
it
comes
to
medical
devices
and
and
how
you
deploy
in
the
area.
So
we
have
to
deploy
solutions
that
are
capable
flexible
and
configurable
to
meet
the
need
of
a
diverse
world.
B
Our
technology
deployed
into
the
hospital
environment
are
life
critical
applications,
life-saving
applications
that,
when
they
are
up
when
they're
running,
they
are
increasing
outcomes,
they
are
making
outcomes
better.
Ensuring
that
we
have
proper
uptimes
is
crucial
to
the
success
of
technology
in
the
hospital
world.
The
next
point
I
want
to
make
is
proximity
to
the
patient,
which
might
not
seem
as
relevant,
but
the
closer
that
you
get
to
the
patient.
The
more
costly
your
compute
devices
become
the
higher
the
regulations,
the
more
scrutiny.
B
This
proximity
can
be
proximity
to
the
patient.
It's
also
proximity
to
the
scanner
devices
themselves.
So,
if
we're
looking
at
an
mr
machine
a
ct
machine,
sometimes
these
solutions
need
to
be
deployed
close
to
the
scanner,
and
this
can
either
be
related
to
a
performance
issue
because
we're
pulling
so
much
data
off
the
scanner
we're
pulling
so
much
data.
B
You
know
as
we're
monitoring
patients
that
the
transmission
of
the
data,
the
further
you
get
away,
will
create
more
latency
for
the
operation,
which
can
be
unacceptable
for
the
treatment
as
you
get
further
away
from
the
patient.
There's
latency
issues
there's
also
more
opportunities
for
communication
failure.
The
third
point
I
need
to
make
in
our
highly
highly
regulated
software
environment
is
that
we
need
long-term
support.
B
Typically,
we
need
two
years
of
development
support
and
then
an
additional
three
years
of
production
support
as
we
deploy
the
solution
in
the
field,
and
the
type
of
support
that
we
need
is
not
to
just
take
the
latest
application
where
they've
fixed
some
issues.
But
we
actually
need
support
with
the
specific
versions
that
we're
using,
because
to
incorporate
a
new
version
can
create
a
whole
new
development
cycle
and
with
the
regulations
and
rigor
that
we
have
to
follow.
B
This
can
be
too
costly
in
a
development
cycle
to
roll
out
a
bug
fix
or
a
patch
for
an
ongoing
production
piece
of
software.
So
let's
talk
a
little
bit
more
about
this
melting
pot
of
innovation
and
technology
that
we're
trying
to
bring
some
order
to
this
expands
to
clouds
and
data
centers
at
g
healthcare's
providers,
oh
and
thousands
of
edge
devices
in
hospitals
with
a
myriad
of
diverse
application
deployments.
B
When
we
went
looking
for
a
fleet
management
solution
and
came
across
spectre
cloud,
there
were
four
basic
buckets
of
challenges
that
we
were
trying
to
solve
for
the
life
cycle
of
our
products.
In
the
field,
we
needed
a
central
place
to
manage
the
system
state
and
a
central
source
of
truth
for
that
state.
For
all
of
these
devices,
we
also
needed
to
support
configuration
for
the
entire
for
every
level
of
our
software
stack
commercial,
open
source
and
internal
software,
and
for
data
center
and
appliance
the
on
and
for
the
on-premise
solutions.
B
We
needed
a
simple
lightweight
solution
to
store
and
have
a
software
repository
locally.
That
was
not
only
able
to
store
every
type
of
software
that
we
were
delivering,
but
was
also
lightweight,
and
we
didn't
have
multiple
solutions
in
order
to
get
all
the
feature
effectiveness
that
we
we
need
the
ability
to
consistently
deploy
and
manage
across
every
environment,
whether
that
be
an
appliance,
a
data
center
or
a
cloud.
I
can
deploy
applications,
add-on,
services,
platform,
services
and
infrastructure
in
a
supported
common
way
without
reinventing
the
wheel
every
single
time.
All
right.
B
Let's
talk
about
lifecycle
management
of
this
stack.
We
needed
to
manage
installs
patches,
upgrades
from
essential
source
of
truth
for
over
a
thousand
edge
locations
for
each
system.
Every
system
would
have
a
cloud
configuration
that
I
can
go
to
that
becomes
the
central
source
of
truth
for
what
needs
to
be
installed
on
that
system
and
what
versions
of
those
things
are
installed
on
that
system?
Compute
resources.
B
We
have
software
components,
we
have
different
types
of
connectivity
per
site,
some
sites
are
connected,
some
sites
are
semi-connected
where
they
have
intermittent
connectivity
or
that
connectivity
performance
is
very
poor
and
we
have
some
sites
that
are
completely
not
connected
at
all,
and
we
still
have
to
support
that.
We
don't
want
one-off
solutions
for
every
single
one
of
these.
We
want
a
centralized
solution
that
manages
all
of
these
things
and,
with
all
of
these
multiple
system
deployments,
how
do
we
fleet
manage
this?
B
B
I
have
to
store
that
software
locally
on
my
system,
and
I
can
have
my
software
repository-
take
up
a
big
part
of
the
resources
on
the
local
system,
because
resources
on
a
local
on-premise
system
are
the
most
costly
resources
it's
prime
real
estate.
So
we
need
a
simple
single
solution
that
is
lightweight
to
store
and
then
provide
these
software
artifacts
any
any
type
of
artifact
that
I'm
going
to
deploy
to
the
system
and
manage
those
artifacts
in
a
very
light
way,
while
providing
the
smallest
possible
footprint.
B
So,
moreover,
we've
talked
about
many
of
the
challenges
in
the
hospital
environment
that
we're
deploying
medical
applications
into
supporting
these
medical
applications
as
a
platform.
But
most
of
all,
when
we
went
out
looking
for
fleet
management
solutions,
we
needed
to
wrap
up
the
deployment
the
upgrade
the
system
state
into
a
single
solution
for
all
of
our
deployment
targets.
B
I
want
to
work
through
a
single
pane
of
glass
configuring,
my
component,
whether
it
be
a
home-based
component
or
a
bm-based
component,
my
infrastructure,
my
kubernetes
layer
overall,
my
life
cycle
management
in
a
common
standard
way
that
we
can
share
with
our
modality
partners
within
ge
healthcare
and
they
can
configure
the
dynamic
applications
that
they
have
to
deliver
on
the
edison
platform.
Now,
let's
bring
it
all
together.
B
We've
talked
about
all
the
challenges
that
we're
facing
what
we
were
trying
to
solve
when
we
partnered
with
spectre
cloud.
Now
we
bring
inspect
cloud
spectracloud
answered
a
lot
of
things
for
us
in
this
fleet
management
area
with
spectrocloud's
declarative
model,
we
can
package
a
myriad
of
software
vms
containers
in
a
common
packaging
solution.
Spectrocloud
extended
its
declarative
profile
model
to
include
on-premise
management
and
os
layers.
So
not
only
can
I
configure
applications
container
applications
and
profiles,
but
now
we
can
configure
vm
orchestration
and
deploy
vms
on
premise
through
a
profile.
B
The
premise
that
spectre
cloud
management
is
built
upon
allows
for
a
disconnected
system.
I
can
completely
be
disconnected
from
the
spectrocloud
sas.
I
can
configure
my
system
through
that
sas
take
that
configuration
apply
it
to
a
completely
disconnected
system
and
the
management
on
board.
The
system
will
perform
my
installs
and
my
updates
and
keep
that
system
stay
consistent,
consistent
with
the
specification
that
I
can
pull
out
from
the
central
get
ops
driven
fleet
management
solution
for
our
on-premise
software
solutions
and
storage.
B
Spectrocloud
has
a
flexible
model
that
can
support
different
system
configuration.
All
of
this
comes
together
to
help
reduce
cost
and
complexity
and
reducing
cost
of
healthcare.
Solutions
can
reduce
the
overall
cost
of
healthcare,
allow
more
solutions
to
be
delivered
to
help
more
patients,
and
this
can
ultimately
provide
better
patient
outcomes,
as
spectrocloud
continues
to
become
more
flexible
on
premise
and
in
the
cloud
it
becomes
the
glue
that
edison
uses
for
a
common
cloud
native
solution,
both
on
premise
and
in
the
cloud.
B
Hey
I'd
like
to
thank
you
for
having
me
here
today,
and
I
appreciate
you
allowing
me
to
share
some
of
the
challenges
that
we
face
in
the
healthcare
industry,
and
I
hope
that
you
can
see
how
cloud
native
can
help
us
support
our
customers
and
our
applications
and
and
deliver
better
solutions
for
better
patient
outcomes.
Maybe
next
time
I
can
join
in
person,
but
I
hope
you
enjoy
the
rest
of
the
conference
and
have
a
great
day.
A
So,
as
you
can
see,
ben's
passionate
about
the
technology,
you
know
ge's
delivering
a
lot
of
new
technology
this
this
this
integration
between
the
highly
regulated
medical
devices
and
starting
to
do
new
things
like
analysis
and
do
that
at
the
edge
close
to
the
data
is
the
challenges
he's
been
talking
about.
So
let
me
double
click
in
a
little
bit
because
he's
talking
about
desired
state
and
a
spectra,
cloud
palette
platform,
cluster
profile
and
this
middle
section
is
actually
inside
spectra
cloud
palette.
This
is
what
the
declarative
model
visually
looks
like.
A
So
these
different
layers,
we
call
them
packs
and
you
can
sort
of
compose
your
blueprint
of
what
you
want,
the
desired
state
to
look
like
and,
as
you
can
see
on
the
right,
they
build
a
pretty
complex
stack
to
deliver
out
at
the
edge
because
there's
different
third-party
applications,
internal
developed
applications,
the
underlying
things
that
make
kubernetes
production
ready
and
the
fact
the
edge
environments
are
customers
environments
with
varying
requirements.
Some
are
virtualized.
Some
are
big
hearts,
big
machines,
some
are
small
machines,
creates
the
sort
of
challenge
ben
was
talking
about.
A
So
we're
going
to
talk
a
little
bit
about
what
we've
sort
of
delivered
for
ge,
with
some
specific
benefits.
You
know
they
need
a
plug
and
play
low
touch
box
if
ge
has
to
send
a
highly
technical
kubernetes
person
out
into
the
customer's
environment.
Just
logistics
alone
can
be
challenging.
Imagine
now,
if
you're
a
retailer,
you
have
retail
stores
and
there's
customers
around
or
you're
an
isv,
and
you
have
lots
of
customers,
and
you
just
want
to
ship
your
software.
You
don't
want
to
be
intrusive
into
their
business.
A
So
having
that
sort
of
light
touch
ability
to
deploy
is
important,
they
need
to
be
able
to
update
it
connected
semi-connected
disconnected.
So
how
do
they
sort
of
run
that
long
life
cycle
that
been
mentioned?
As
you
know,
two
years
of
support,
plus
three
years
of
production,
there
are
adjacent
virtual
machines
in
their
solution.
Not
all
our
technology
has
been
moved
forward
to
cloud
native
and
microservices
containers,
so
the
edge
solution
may
need
a
few
virtual
machines
off
to
the
side
as
well,
that
are
dependencies
for
the
application
stack.
A
While
the
developers
continue
to
modernize
and
transform
the
applications
to
be
entirely
cloud
native,
secondly,
this
desired
state
we're
talking
about
this
blueprint.
This
cluster
profile
ends
up
being
the
centralized
policy
so
that
we
can
push
this
policy
out
to
the
edge
device
now
what's
different
from
a
lot
of
technologies
is
sometimes
is
something
currently
matching.
Your
desired
state
may
only
be
measured
when
you
run
something
like
with
terraform.
When
you
run
a
plan,
apply
your
measuring
is
the
desired
state
of
the
terraform
script.
A
Actually,
what's
there
using
the
integration
of
cluster
api
and
terraform
together,
they
still
use
git
ops.
They
still
use
terraform
to
configure
a
lot
of
things,
but
it's
the
spectra
cloud
terraform
provider.
I
think
we
have
like
3.4
million
downloads,
so
it's
very
popular
most
of
our
customers
do
things
in
the
ui
and
as
they
scale
it
up,
they
move
it
into
git,
ops
and
terraform
ways
of
doing
things,
so
that
becomes
your
system
of
record
and
pallet
becomes
the
system
of
operation
we're
constantly
looking
at?
Is
the
desired
state
being
maintained?
A
That's
actually
done
at
the
cluster,
so
in
this
disconnected
state,
where
there's
no
management
plane
observing.
How
would
we
know
that
the
configuration
tried
to
drift?
Well?
We
know
because
it's
actually
being
monitored
at
the
cluster
in
a
constant
loop.
That's
measuring
it!
So
if
they're
disconnected
and
they
pull
that
policy
and
new
artifacts
down
and
sort
of
walk
them
across
that
gap
and
deliver
them
to
the
edge
device,
then
the
it's
applied.
It
now
matches
the
new
desired
state
and
it's
constantly
being
measured
to
make
sure
it
matches
that
desired
state.
A
And
it's
a
use.
What
you
like
approach!
We
provide
a
lot
of
capabilities,
but
ge
has
the
ability
to
bring
third
parties
proprietary
technology.
They
don't
have
to
wait
for
the
platform
to
support
it
and
so
that
sort
of
segues
into
this
local
repo.
We
provide
a
lot
of
out
of
the
box
easy
to
use
quick
one
of
our
problems
in
kubernetes
and
especially
edge,
is
we're
starting
to
see
a
skills
gap
problem
as
kubernetes
grows
and
becomes
more
popular,
we're
sort
of
fighting
for
constrained
resources
of
kubernetes
experts.
A
A
So
you
have
someone
to
call
on
what's
open
source
when
maybe
there
isn't
a
commercial
offering
or
maybe
even
what's,
internal
and
they're
just
struggling
of
how
to
make
it
work
on
kubernetes,
you
have
a
set
of
kubernetes
experts
that
they
get
access
to,
that
they
can
call
when
it's
sort
of
all
gone
wrong
and
finally,
having
multiple
management
points.
What's
important
here
is
there
are
prior
generations
of
kubernetes
management
and
I
think
we're
where
we
are
today
because
of
some
of
their
efforts.
So
we
can
thank
them.
A
But
what
happens
a
lot
of
times
when
you
start
talking
to
edge
we're
talking?
Not
tens
we're
talking
hundreds
in
g's
case
thousands
in
retailers.
You
may
have
tens
of
thousands
of
stores
and
a
lot
of
the
prior
generation
architectures.
They
needed
multiple
management
just
to
do
one
type
of
capability
cloud
or
edge.
So
maybe,
if
you
had
100
stores,
you
need
one
management
point
to
be
able
to
manage
100
stores
the
way
we're
architected.
A
You
may
only
choose
to
have
multiple
management
points,
because
maybe
of
you
need
something
in
the
eu
and
something
in
north
america
for
data
sovereignty,
or
maybe
you
do
need
air
gap,
we
do
support
self-hosted
and
air
gapped
as
well.
So
maybe
you
have
a
version
of
the
management,
that's
in
a
highly
classified
or
disconnected
where
you
want
the
whole
thing
to
be
self-encompassed.
We
see
this
in
department
of
defense,
intelligence,
energy,
oil
and
gas
control
networks.
Those
aren't
even
connected
to
the
internet
at
all.
A
So
you
have
the
ability
to
sort
of
choose
your
management
domain,
but
it's
not
being
forced
upon
you
because
of
a
limitation
of
the
architecture
scale
you
may
be
choosing
it
because
of
certain
regulatory
or
just
administrative
functions,
and
so
those
are
things
that
that
ge
has
seen
the
benefit
of
by
using
pallet
spectra.
Cloud's
pallet.
A
Now
we
talk
about
what
the
deployment
workflow
looks
like
we
try
to
make
it
really
simple:
you
can't
do
a
truck
roll
truck
rolls
are
very
expensive.
Having
an
expensive
field
engineer
a
lot
of
organizations
we
talk
to.
They
say
that
the
like
third
party,
they're,
using
for
deploying
field
technicians,
is
a
minimum
of
four
hours
just
to
do
the
truck
roll.
A
So
just
the
provisioning
the
device
make
it
simple,
have
someone
who
can
warehouse
stage
it
get
the
minimum
configuration
on
it
and
ship
it
out,
so
the
edge
location
it
doesn't
have
to
be
a
highly
technical
person.
It
could
literally
be
the
customer
of
the
isv
or
ge's
hospital
customer.
It
could
be
a
store
manager,
a
retail,
make
it
so
that
they
can
actually
go
through
a
couple.
Simple
steps
plug
it.
In
turn
it
on
scan
a
nfc,
I
think,
out
at
the
tabletop
out
there.
A
We
have
some
that
have
a
nfc
chip
on
top
of
them
with
a
little
app
and
that
registers
it
back
into
the
spectra
cloud
palette
platform,
and
then
this
blueprint,
this
desired
state
model.
Our
cluster
profile
is
pushed
down
and
then
that
long
running
life
cycle
of
capabilities
kicks
in
but
out
of
the
edge
we
try
to
make
it
as
simple
as
possible.
We're
really
trying
to
bring
a
cloud
experience
to
edge
and
edge
sort
of
hasn't
had
that
in
prior
generations.
A
So
this
distributed
orchestration.
What
we're
talking
about
I
mentioned
we
have
a
lot
of
the
local
resources
where
it
has
to
be
disconnected,
is
one
option
and
that's
how
ge
is
using
it.
So
there
can
be
things
like
a
local
cli.
I
just
need
to
put
a
little
bit
like
that.
Customer
might
need
a
proxy
or
might
need
a
specific
set
of
ip
addresses
that
are
static,
so
they
have
a
simple
sort
of
tui
text,
ui
that
they
can
configure
on
and
then
even
the
health
of
it.
A
You
know
maybe
there's
no
support
connectivity
direct,
because
it's
always
disconnected
or
it's
become
accidentally
disconnected,
give
them
sort
of
a
lightweight
version
of
the
web
ui
so
that
they
can
still
sort
of
see
the
state
is
the
desired
state
delay.
The
right
version.
Is
it
currently
in
sync
with
what
the
desired
state
requests
the
environment
to
be
so
some
local
troubleshooting
as
well,
and
doing
that
at
scale
of
thousands
of
locations
so
sort
of
three
key
takeaways?
A
Sorry,
you
wanted
to
picture
that
one
go
for
it
and
then
we
can
talk
to
you
outside
too
all
right.
So
a
couple
three
key
takeaways
one
reducing
the
costs
of
deploying
and
managing
at
these
locations.
You
know
the
costs
are
one
thing:
just
the
customer
perception,
the
get
the
touches
to
be
lighter,
get
the
intrusion
to
the
to
their
clients
or
hospitals.
Their
customers.
Are
you
know
their
direct
indirect
customers?
A
Are
the
hospital,
the
patients,
the
doctors,
those
guys
don't
want
you
in
their
way
with
their
technology,
so
reducing
the
overall
cost
of
engineering
and
the
high
touch?
That's
required
is
one
thing
they
just
had
to
have
and
they
get
that
working
with
the
edison
platform
on
a
modern
kubernetes
helps
their
third
parties
and
developers
also
be
able
to.
A
You
have
a
lot
of
third
parties.
You
can't
always
tell
them
everything
about
the
platform.
They
have
to
provide
a
lot
of
services
and
just
have
those
things
coming
to
get
repos
and
the
developers
don't
need
to
get
into
details
of
how
does
it
work?
The
edison
platform
provides
those
services,
and
so
they
have
a
broad
range
of
ecosystem.
A
In
this
case,
for
example,
hospitals
actually
buy
different
apps
in
the
edison
portfolio,
so
one
hospital
might
buy
app
one
three,
five
and
seven
another
one
might
buy
two
four
ten
and
twelve,
and
so
even
hospitals
have
different
compositions
of
what
services
and
software
they've
purchased
from
ge.
So
these
edge
devices
aren't
cookie
cutter
in
an
isv
where
maybe
you
deliver
the
same
full
stack
over
and
over
and
over.
A
This
is
a
little
simple,
but
they
do
have
sort
of
a
complex
environment
where
the
developers
just
need
to
know
that
they
can
push
these
things
and
the
edison
platform.
Then
can
deliver
them
all
the
way
out
to
the
edge
successfully
and
thirdly,
they
need
constant
access
to
the
latest
innovation.
They
don't
want
the
platform
to
have
to
always
come
back
to
us
and
say
I'd
really
like
to
use
x,
but
you
don't
support
x
yet
so
we
do
provide
a
lot
out
of
the
box,
but
they
can
always
develop
their
own
things.
A
It's
not
a
new
way.
You
know,
there's
great
controllers
and
operators
and
helm
charts
out
there,
so
they
can
integrate
those
very
quickly
and
try
things
over
and
over
and
over.
They
do
use
this
in
the
cloud
as
well,
so
a
lot
of
times,
they're
testing
and
iterating
and
developing
in
the
cloud,
and
then
they
push
things
out
to
the
edge
in
production.
A
So
unfortunately,
ben
not
being
able
to
be
here
with
us
was
unfortunate,
but
I
do
want
to
sort
of
thank
him
for
his
time
hopefully
view
this
next
time
we
have
a
table
top
out
there.
So
if
you
want
to
ask
us
more
about
edge
or
what
ge
is
doing
or
other
edge
customers,
please
come
visit.
Us
there's
also
a
the
new
stack.
A
Probably
all
you're
familiar
with
them,
the
tapas
tuesday,
it
starts
at
4
15
and
we're
sponsoring
that
it's
actually,
when
you
head
back
out
the
main
to
registration,
take
a
right
instead
of
exiting
and
it's
it's
off
through
there.
So
that's
where
the
tapas
tuesday
is
there's
a
panel.
I
think
we're
on
it.
Our
cto,
who
did
the
keynote
earlier,
is
on
it
and
there's
some
other
folks
from
vmware
and
another
on
the
panel,
so
join
us
for
tapas
tuesday,
as
well,
starting
at
4
15..
Thank
you
appreciate
it.
Everybody.