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Description
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B
B
A
A
Yeah,
we
are
excited
to
invite
some
also
illustrious
guests.
Yes
today,
so
we
have
I'm
gonna,
I'm
gonna
ask
y'all
to
indicate
the
group
you're
with
because
red
hat
has
been
renaming
a
bunch
of
the
teams
that
we
have
quite
a
bit
lately,
and
so
so
I'm
getting
very
confused,
but
first
up
james
faulkner.
You
want
to
tell
us
a
little
bit
about
who
you
are
and
and
what
you
do.
C
Sure
yeah,
so
thanks
for
having
me
on
so
james
faulconer,
I
work
in
the
make
it
easy
for
you
formerly
known
as
the
middleware
business
unit.
Now
the
application
services
business
unit.
I
do
product
marketing
for
our
suite
of
of
cloud
native
runtimes
for
running.
You
know
a
very
horizontal
set
of
use
cases
for
applications,
so
you
know
the
traditional
ones:
node.js
spring
boot,
java,
ee,
jakarta,
ee
and
now
some
of
the
more
modern
stuff
with
the
things
like
carcass.
C
So
yeah,
I've
been
at
red
hat
for
about
four,
almost
five
years,
actually
five
years
in
february,
it'll
be
five
years
prior
to
that,
I
spent
a
bunch
of
time
in
sun,
microsystems
and
oracle,
and
I
was
also
at
liferay
for
a
few
years
as
well,
so
I've
been
in
the
java
space,
for
I
don't
know,
12
years
now.
I
think
something
like
that.
C
B
C
B
C
B
A
D
Yeah
thanks
yeah,
my
name
is
danielle
and
actually
I'm
working
with
james
faulkner
in
the
same
team
in
the
runtimes
team,
so
yeah,
I'm
technical
marketing
major
a
little
bit
more
focused
on
technical
stuff,
like
a
creative
workshop
demo
and
a
technical,
some
enablement
for
many
developers
in
the
iot
operation
team
really
about
the
cloud
name:
runtimes,
yes,
parker's,
spring
booth
and
node.js
and,
of
course,
device
eap.
That
is
our
still
be
cash
cow
yeah.
So
that's
what
I'm
doing.
D
A
Kind
of
entertaining
it's
kind
of
like
there's
a
there's,
a
woman
who
lives
in
cambridge,
so
I
live
in
downtown
boston
and
cambridge
is
like
right
next
door
and
she
is,
I
see
her
all
the
time
around
the
world
at
conferences.
I
have
seen
her
once
in
the
boston
area,
which
I
think
is
also
amazing,
so
yeah
when
you,
when
you
travel
a
bunch
it
can
be,
it
can
lead
to
some
entertainment,
yeah.
C
Sorry,
landon
yeah
go
ahead.
One
story
on
that.
There's
like
there's
a
guy
that
works
at
red
hat
today.
I've
only
seen
at
conferences
and
so
and
we
see
him
in
almost
every
single
conference.
His
name
is
george
he'll
know
he
works
at
red
hat
and
it's
just
hilarious.
Every
time
we
see
each
other
like
hey,
buddy,
good.
A
You're
right
there's
something
to
be
said
about
the
like
circuit.
You
know
I.
I
often
wonder
if
that's
if
it's
similar
for
and
much
longer,
lasting
in
a
sense
for
like
actors
and
actresses
or
like
people
who
work
in
you
know,
tv
shows
or
movies
or
whatever
you
only
see
them
kind
of
on
the
circuit
you
know
or
like
comedians
or
whatever,
like
I,
I
suspect
it's
a
similar
experience
yeah,
but
you
know,
obviously
I
you
know
being
a
me
and
a
nerd.
I
only
have
experience
with
the
software
conference
circuit.
A
A
Like
literally
it
popped
up
when
I
was
about
to
switch
perfect,
yes,
all
right,
let's
see
if
we
can
find
the
right
window,
but
I'm
going
to
share
my
my
awesome
awesome,
slides
that
I
do
for
every
show,
and
I
think
I
even
corrected
all
of
the
bugs
in
them
this
time,
which
is
even
better.
But
what
I
like
to
do
is
to
quickly
start
off.
I
like
to
say
you
know
in
case
you're
lost.
A
But
we
also
cover
a
lot
of
development
stuff
and
I
think
we're
going
to
cover
a
little
bit
more
on
the
developer
side
of
the
house
today.
But
this
is
the
level
up
hour.
Your
hosts
chris
short
and
myself,
I'm
langdon
with
a1
on
twitter
and
chris
is
chris
short,
and
if
you
want
to
chat
with
us,
you
can
chat
in
the
in
the
whatever
streaming
platform
chat
you're
on
and
we
will
see
it
on
twitch
and
and
respond
either
on
the
show
or
on
twitch.
A
A
But
you
can
definitely
join
us
there
and
we
we
sometimes
get
into
interesting
discussions.
We've
been
trying
to
flesh
out
the
discord
to
kind
of
cover,
all
the
shows
as
well.
So
any
of
the
shows
that
we
do
on
openshift
tv.
You
can
kind
of
come
and
chat
with
us
there,
offline
and
yeah.
So
do
you
have
the
oh?
You
dropped
it
already.
So
I'm
already.
B
B
A
A
So
I
asked
the
two
of
you
here
today
because
we
have
through
the
show,
so
oh
wait,
you
know
what
I
did
miss
a
slide.
I
thought
I
did,
and
here
I
was
doing
so
well
so
and
the
reason
I
want
to
make
sure
I
go
back
to
it
is
because
it's
somewhat
important
to
my
point.
So
what
I
want
to
point
out
is
this
is
episode
22
of
our
episode,
so
we've
actually
been
doing
this
a
while
now.
Mr
short,
it's
been.
A
A
B
A
Advance
like
I,
I
actually
did
this
one,
and
the
reason
I
want
to
point
it
out
is
because
we
have
been
doing
the
show
for
a
whole
bunch
of
episodes
now
and
we
have
been
recently
covering
or
been
using
nexcloud
as
kind
of
our
example.
Application
and
nextcloud
is
cool
and
does
its
stuff
well
and
that's
a
little
bit
the
problem
in
that
you,
we
can't
break
it
in
right.
A
B
A
So
what
I
wanted
to
invite
you
on
the
show
about
was
to
talk
about
that
application,
but
then
the
part
that
I
think
you
also
did,
which
I'd
also
like
to
talk
about,
was,
I
think
it
was
actually
a
migration
originally
from
a
monolith.
Application
yeah,
that's
right,
correct,
okay!
So
so
that's
an
even
better
story.
So
why
don't
you
tell
us
a
little
bit
about
the
app
and
what
it
does
or
maybe
a
pointer
to
to
where
it
lives
and
that
kind
of
stuff.
C
Sure
so
the
cool
store
is
it's
the
retail
shopping.
It's
a
fake
retail
shopping
experience.
It
was,
I
did
not
write
the
original
one
written
by
eric
chabel
and
a
few
others
really
intending
to
showcase,
not
necessarily
the
retail
experience,
but
showcase
our
business
rules
management
system.
How
business
analysts
can
you
know
edit
a
spreadsheet
so
that
they
can
alter
the
the
shipping
or
promotion
costs
or
promotional
details
without
having
to
go
in
code?
So
it
kind
of
separates?
C
You
know
the
business
guy
from
the
from
the
coder,
and
so
that
was
originally
a
monolith.
A
java
ee,
you
know,
essentially
a
war
file
that
gets
deployed
had
the
brms
or
business
rules
management
system
technology
in
it
it
also
had
a
front
end
written
in
a
web
toolkit
called
vadin
and
it
had
a
few
products.
You
select
the
products,
you
click
the
purchase
button.
It
calculates
the
shipping
costs
and
any
promotional
details
based
on
the
brms
rules,
and
then
you
get.
C
You
know
your
result
and
when
I
joined
red
hat
in
2016,
microservices
were
all
the
rage
and
also
all
the
rage
was
or
container
orchestration
with
openshift
and
the
openshift
two
to
three
kind
of
transition
that
was
in
that
time
period.
So
we
really.
I
thought
it
would
be
a
great
example,
because
everybody
knows
retail,
everybody
uses
some
kind
of
online
shopping.
C
So
it's
a
very
familiar
use
case,
and
so
it's
it's
easy
to
add
features
and
demonstrate
various
technologies
using
those
features.
So
adding
things
like
an
inventory
system
or
adding
a
payment
gateway
or
something
like
that
and
all
fake
of
course,
but
we
really
used
it
as
a
as
a
as
a
I
guess,
a
way
to
showcase
containers
and
an
open
shift,
as
well
as
the
the
microservices
capabilities
that
that
people
like
bursarto
bursata
were
were
talking
about
very
heavily
at
the
time.
C
Migration
from
a
monolith
to
a
microservice
and
then
along
the
way,
adding
features
from
openshift,
like
you
know,
blue
green
deployments
and
build
pipelines,
and
things
like
that,
so
that's
sort
of
the
the
genesis
of
that
application,
and
so
in
more
modern
times,
we've
we've
continued
to
add
new
features
like
we've
added
an
api
gateway,
poor
man's
api
gateway.
If
you
will
with
camel
we
added
a
single
sign-on,
we
had
a
infinite
span
for
for
in-memory
data
grids
for
storing
the
shopping,
cart
details
for
each
user.
Things
like
that.
C
We
also
rewrote
the
ui,
because,
although
vauden
is
great
it
it
wasn't
what
people
were
looking
at
when
they're
looking
at
microservices
a
lot
of
people
do
things
like
single
page,
apps
and
front
ends
and
things
like
angular
and
react.
So
we
wrote
the
front
end
in
angular
turned
out
into
microservice
as
well
with
node.js,
and
so
we
had
all
these
different
technologies
kind
of
sitting
in
this
one
demo,
and
so
a
lot
of
the
the
field.
A
A
You
know
in
particular
what
I
also
enjoy
is,
and
the
kind
of
thing
I
like
to
show
off
is
you
know
in
a
real
world
application,
the
likelihood
it
is
just
one
programming
language
is
very
low,
and
so
what
I
particularly
like
is
that
you
kind
of
have
a
kind
of
a
node.js
component
as
well
as
a
bunch
of
java
components.
You
know
even
going
back
as
horrific
as
it
is
to
say
you
know,
you
know
using
java
front
ends
against
the
mainframe.
A
Right
is
another
common
scenario,
even
even
today,
which
is
scary
and
one
of
the
things
that
narendev
brought
up
in
the
chat
actually
which
I'd
point
out
too,
is
it.
It
also
allows
for
kind
of-
and
this
is
one
of
the
things-
that's
true-
about
kind
of
a
service
oriented
model
in
general,
whether
you
call
them
microservices
or
macro
services
or
services
or
small
chickens
or
whatever
you
want.
It
allows
for
change
over
time
around
the
feature
set
that
you
want
to
offer
right,
so
he
brought
up
ai.
A
For
example,
you
know
an
ai
for
analysis,
you
know,
so
that's.
A
very
good
example
is,
like
you
know:
how
well
are
your
you
know,
widgets
selling,
when
you're
you
know,
if,
if
you
have
the
price
point
at
x
versus
if
you
have
the
price
point
at
y-
and
we
talked
a
little
bit
about
this
last
episode-
we
were
talking
about
service,
mesh
and
kind
of
red
black,
or
I
keep
doing
this.
A
You
know,
oh
no,
it
is
red
black
red
black
deployment
of
applications,
so
you
can
kind
of
say:
okay,
I'm
going
to
try
this
ui
and
see
how
it
performs
or
try
this
price
point
and
see
how
it
performs
and
try
this
price
point
presented
in
the
same
application,
but
to
different
sets
of
users.
So
you
can
get.
A
A
A
Yeah,
actually,
I
was,
I
meant
to
bring
this
up.
The
last
episode
is
someone's
presidential
campaign.
I
want
to
say
it
was
hillary
clinton,
but
it
could
have
been
somebody
else.
There
was
a
story
about
how
they
did
an
a
b
test
with
two
different
size
donate
buttons,
and
it
made
like
an
astronomical,
like
difference
like
orders
of
magnitude,
difference,
wow
amount
of
donations.
A
C
Yeah,
it's
kind
of
interesting
how
how
you,
how
you
know
the
user
experience
and
ui
can
really
affect
your
decisions
like
even
in
the
in
the
cool
store.
One
of
the
things
that
I
I
found
really
early
on
when
I
first
joined
red
hat
and
I
looked
at
some
of
the
existing
demos-
they
were
like
the
the
the
big
money
shot
was
like
the
log
file
scrolling
by
like
look
it
works.
I
see
the
value
change
from
one
to
three:
isn't
a
fantastic!
C
A
As
a
developer,
log
files
are
the
bomb
right.
I
mean
like
right,
like
you,
wanna,
you
know
see
in
your
own
log.
File
scroll
by
without
errors
is
like
an
amazing
experience,
but
you
know
I
don't
I
get
the
impression
that
nobody
else
cares.
You
know,
for
example,
I
don't
want
to
see
amazon's
log
file.
I.
A
Something
show
up
my
house,
but
yeah.
I
totally,
I
totally
get
you
what
I'm
really
curious
about,
and
you
know
kind
of,
I
think
relevant
to
kind
of
the
audience
and
the
show
is
like.
So
what
was
the
experience,
or
how
did
you
go
about
taking
kind
of
the
monolith
to
the
the
microservice
side?
What
you
know,
what
complexities
were
there?
A
C
C
That
turned
out
to
be
kind
of
hard
to
code
myself
because
of
all
of
the
different
http
verb
rules-
and
I
also
was
learning
camel
at
the
time
and
trying
to
sort
all
that
out
and
and
set
up
the
the
different
rules.
For
you
know
the
different
routes,
essentially
for
the
different
microservices
and
aggregating
those
pieces
back
together,
turned
out
to
be
relatively
challenging.
C
But
at
the
end
of
the
day
it
was,
I
think,
the
right
way
to
do
it,
because
you
kind
of
want
in
a
micro
services
and
containerized
world.
You
kind
of
want
to
hide
the
implementation
detail
of
your
back
ends,
so
that,
if
you
want
to
make
a
change,
you
don't
have
to
go
update
the
client,
because
if
your
client
is
a
mobile
app
on
the
app
store,
for
example,
the
apple
app
store
it.
Is
it
a
massive
pain
in
the
butt
to
update
an
app
quickly?
A
C
A
It
ain't
just
mobile
apps,
so
one
of
the
things
I
wanted
to
comment
on
was:
can
you
expand
a
little
bit
on
what
camel
is
because
you
know
I'm
not
sure
our
audience
has
a
lot
of
familiarity
with
it
yeah
and
you
keep
talking
about
it
and
I
think
personally,
very
cool.
So
you
know
I
think
it's
an
important
thing
to
talk
about
a
little
bit.
C
Sure
yeah,
so,
first
of
all,
I'm
not
a
camel
expert.
I
didn't
know
about
camel
until
I
joined
red
hat,
so
I
probably
won't
do
it
the
justice
that
it
deserves,
but
it
is
a
an
integration
technology.
So
if
you
want
to
glue
one
thing
to
another
thing
and
not
have
to
write
all
the
logic
yourself,
they
have
a
ready-made
set
of
connectors
and
they
also
implement
a
number
of
patterns
that
have
emerged
throughout
the
years
of
doing
distributed,
programming
or
distributed
computing
where
you
can
have
like.
C
If
you
need
to
make
a
call
to
three
microservices
or
three
other
services
and
aggregate
the
result,
they
can
do
that
it
can
do
filtering,
you
can
do
chaining,
you
can
do
all
kinds
of
interesting
architectural
patterns
and
then
it
also
has
the
connector.
So
if
you
want
to
hook
up
your
super
modern,
like
react
front
end
to
a
ftp
server
or
some
other
kind
of
server
that
you
maybe
not
familiar
with,
there's
probably
a
connector
for
it
in
camel.
I
think
they
have
300
or
more
yeah.
C
C
It
is
they're
related
camel
k
is
the
is
the
essentially
a
way
to
run
so
when
you,
when
you're,
do
when
you're
building
a
an
application
with
camel
you
create,
what's
known
as
a
camel
route
and
it's
basically
a
snippet
of
code.
That
says
you
know
if
this
call
comes
in
on
this
address
or
this
endpoint
do
this
other
thing
and
then
return
the
result,
so
that
can
be
expressed
as
a
java
application
using
camel
it
can
run
in
an
app
server.
It
can
run
as
a
you
know.
C
A
runnable
jar
file
or
whatever
camel
k,
takes
it
kind
of
the
next
step
further,
where,
instead
of
you
building
a
container
and
and
and
you
know,
deploying
a
container,
you
know
starting
up
a
pod
and
there
you
have
it.
You
simply
take
your
snippet
of
code
and
you
submit
it
to
the
camel
k,
runtime
and
it
then
chooses
a
runtime
to
actually
execute
that
kind
of
like
in
a
serverless
or
function
as
a
service
model
cool.
So
it's
it's,
but
it
is,
you
can
basically
use.
C
C
That
we're
looking
you
mentioned
ai
there
is,
you
know
you
could
imagine
a
feature
where
it's
like.
If
you
bought
this
thing,
you
might
be
interested
in
these
other
or
maybe
that's
a
machine
learning.
I
don't
know
I'm
not
a
strong
different
change.
I
don't
understand
the
difference
that
much
between.
A
A
C
A
A
Think
of
like
what
do
you
call
it
communication
like
a
message,
bus
right?
It's
like
many
message.
Buses
are
java
world,
but
or
even
written
in
c,
for
example,
for
performance,
but
their
experience
to
a
java
user
is
very
java-esque,
so
you
have
so
it's
it's
similar
to
that.
In
that
you
know
in
the
java
world,
you
see
camel
a
lot
in
the
java
world.
You
also
see
message
buses
a
lot,
but
that
doesn't
mean
they're,
not
in
other
worlds.
I
would
say
it's
more
application
domain.
A
So,
if
you're
doing
true,
you
know
kind
of
in-house
it
or
even
public
facing,
but
like
true
business
software,
you
know-
or
you
know,
b2b
type
software-
that
kind
of
stuff
you'll
see
camel
a
lot
as
well
as
like
message
buses.
You
know
I.
I
did
a
lot
of
work
with
message:
buses
for
example,
because
I
did
a
lot
of
stock
trading
or
stock
company
work.
A
You
know,
which
was
a
lot
of
stock
trading
and
camel
camo
is
also
a
big
integration
layer
as
well,
and
one
of
the
things
I
was
going
to
bring
up
is
to
your
earlier
point
about
kind
of
the
business
logic.
Stuff
is
that's
actually
one
of
the
reasons
like
the
mainframe
stuff
is
often
still.
There
is
not
just
because
the
mainframe
functions
can
perform
so
well,
which
they
really
really
do
right.
A
C
B
C
It's
yeah
exactly
it
kind
of
enables
distributed
integration
where,
like
in
the
past,
you
had
sort
of
the
integration
competency
center
and
when
you
needed
a
new
integration,
you
would
go
to
this
team
and
they
would
take
six
weeks
to
build
it
and
it
might
not
be
exactly
right
now.
You
can
kind
of
essentially
do
client-side
right
with
camel.
A
Well,
and,
and
almost
almost,
as
importantly-
if
not
more
importantly,
your
vendor
can
deliver
them
right.
So
right,
so
your
camel
vendor.
You
know,
red
hat,
for
example,
can
say
here
is
a
slack
integration,
for
example,
you
know,
or
whatever
and
and
give
you
those
pipes
you
know
or
like
a
camel,
and
maybe
I'm
mixing
my
groups,
but
camo
and
kafka,
for
example,
are
a
big.
C
A
Coupling
these
days-
and
you
know
kind
of
like
with
openshift,
for
example-
you
actually
have
a
bunch
of
this
stuff
just
integrated,
so
you
just
can
kind
of
consume
it
rather
than
having
to
build
the
the
bridge
as
well,
which
is
you
know,
because
it's
a
standardized
way
of
doing
these
things
all
that
stuff.
Then
you
can
only.
You
only
have
to
build
that.
You
know
slack.
A
I,
the
reason
I'm
thinking
of
slack
is
just
because
I
was
in
a
like
future
of
open
shift
kind
of
meeting
the
other
day,
and
slack
was
one
of
the
things
that
is
in
the
pipe
so
and,
as
chris
often
says,
we
live
in
the
future
on
this
show
and
the
future
may
or
may
not
happen,
so
take
it
with
a
grain
of
salt,
but
we
did.
I
did
hear
that
slack
integration
was
one
of
the
things
they
want
to
see
coming
through
to
open
shift.
A
C
A
B
A
C
A
C
A
C
Let
me
I'll
go
ahead
and
share
my
screen
and
see
what
I
got
for
you
here.
Let's
see,
okay,
so
let
me
switch
to
my
desktop
here,
so
I
had
just
a
couple.
I
have
a
screenshot
and
then
I
have
the
actual
running
app
on
openshift
that
daniel
also
daniel
feel
free
to
chime
in.
If
you
want
on
the
on
running
on
openshift.
So
this
is
the
original
cool
store.
This
is
the
the
genesis
of.
C
What's
the,
what
we
consider
to
be
the
modern
course
cool
store
demo
from
red
hat
today
you
can
see
it's
a
retail
app.
You
can
choose
some
some
products
on
the
left.
You
click
add
to
cart.
Then
you
click
and
you
see
your
shopping.
Cart
totals
get
summed
up
over
there.
The
promotion
and
shipping
gets
calculated
through
that
business
rules
thing
I
was
talking
about
and
then
you
can
check
out
and
so
that's
sort
of
the
that
was
the
basic
demo.
C
It's
a
monolithic
demo,
you
you
build
a
a
war
file,
a
web
archive
file
which
has
the
vrms
guts
in
it,
and
then
you
deploy
it
to
an
app
server
like
jboss,
eap
or
wildfly,
and
so
that
was
the
original
monolith.
So
that's
just
a
screenshot,
it
is
still
available.
You
can
still
run
it
on
the
I
can
I
can.
I
can
throw
a
link,
I'm
not
sure
where
I
would
throw
a
link
if
I
wanted
to
throw.
C
Okay,
yeah
yeah,
so
I'll
throw
a
link
to
that
in
a
second.
But
this
is
the
original
cool
store
and
then
so
we
took
that
and
one
of
the
one
of
the
ideas
was,
as
you
mentioned
earlier,
langdon
the
mono
to
micro,
the
migration.
This
is,
we
red
hat,
has
tons
of
customers,
I'm
sure
there's
many
others
out
there
that
have.
C
You
know
existing
apps
that
they
have
no
idea
what
to
do
with
them,
but
they
just
know
they're
old
and
slow,
and
they
want
to
make
them
fast
and
awesome
and
compete
in
their
whatever
industry.
They're
in
so
digital
transformation
is
the
name
of
the
game
and
that
what
that
boils
down
to
in
in
reality
is
you
know,
taking
applications
and
either
kind
of
lifting
and
shifting
them
over
to
a
different
platform
that
has
some
features
like
open
shift
or
refactoring
or
rewriting.
C
C
C
C
A
B
C
Yeah
wrangler
pattern
is
it's
good
in
in
theory,
but
there's
and
language
we
talked
about
this
earlier,
like
you
know
from
nexcloud,
is,
is
from
what
I
understand
an
actual
production
app.
This
is
never
should
ever
be
used
in
production,
and
so
because
we
take
a
lot
of
shortcuts
when
we're
doing
this
right
and
so
like,
for
example,
when
we
move
to
micros.
So
this
is
the
model
of
running
here.
C
C
So
you
can
add
to
your
cart
and
you
can
check
out
your
shopping
cart
and
you
can
check
out
and
buy
things
and
it's
all
good
notice.
I
never
logged
in
you
know
so,
there's
no
single
sign
on
there's
single
sign-on
support.
We
haven't
added
in
this
particular
demo,
but
we
also
took
a
lot
of
shortcuts
as
far
as
migrating
a
monolith
to
a
microservices,
because
you
have
in
this
case
a
single
database.
C
In
the
other
case,
we're
going
to
have,
like
eight
databases,
you
know,
they're,
the
challenge
of
of
migrations
is
not
necessarily
the
code.
It's
in
the
data,
because
that's
where
the
that's,
where
the
value
is
for
companies
and
that's
what
they
really
care
about
and
if
you
blow
that
up
you're
indeed
trouble
so
taking
a
monolithic
database
and
converting
it
to
microservices,
now
number
one
you
no
longer
can
do
joins
right,
like
database
joins
like
sql
joins
and
number
two.
You
can
have
potential
for
corruption.
C
So
we
sort
of
hand
wave
over
all
that
in
the
in
the
workshop
and
say
you
know
a
true
mono
to
micro,
you're,
going
to
be
hiring,
you
know
or
doing
either
in-house
or
some
expensive
consultants
to
come
in
and
do
things
like
event,
storming
and
domain
driven
design
and
yeah.
Exactly
and-
and
do
it
right
instead
of
just
what
we
do
in
the
workshop,
which
is
we
go
from
monolith
to
microservice
like
magically
so.
A
I
will
say,
though,
if
you,
if
you
want
a
good
example
of
where
it
is
done,
with
a
production
application,
even
if
that
application
is
not
terribly
complex.
Although
I
think
data
storage
is
always
a
challenge,
the
next
cloud
actually
does
have
both.
So
they
have
a
monolithic
version
and
they
have
a
service
based
or
or
service-ish.
B
A
Version
and
seeing
all
the
changes
between
those
two,
because
they
they
ship
both
these
days
is
really
really
interesting,
so
yeah.
I
would
definitely
recommend
that
for
anybody
who
wants
to
kind
of
learn
how
to
do
it
as
a
kind
of
another
example,
but
I
think
the
nice
thing
about
a
demo
version
is
that
is
that
you
do
skip
over
some
of
the
complexities,
because
the
the
complexities
are
like
kind
of
unique
to
the
application
that
you're
working
with
usually
anyway.
A
C
C
If
you
look
at
the
source
code
of
the
original
monolith
versus
the
source
code
to
some
of
the
services
in
the
microservices
one
they're
not
drastically
different,
because
the
logic
is
more
or
less
the
same,
so
it
wasn't
that
much
of
left
and
so
the
tooling
that
we
have
to
do
this
sort
of,
I
won't
say
automated,
but
assisted
migrations
kind
of,
looks
at
the
source
code.
This
is
a
migration
toolkit
for
applications.
It's
an
open
source
product
from
red
hat.
C
It
looks
at
the
source
code
and
it
kind
of
makes
recommendations.
The
easy
stuff
is
like
yeah
you're,
using
this
proprietary
api
from
oracle.
You
really
probably
should
be
using
the
standard
one
from
the
java
ee
world.
Those
are
easy,
but
the
harder
ones
are
like
doing.
You
know
refactoring
of
large
chunks
of
code,
and
so
we
kind
of
walk
the
user
through
doing
that.
In
the
workshop
so
yeah,
but
we
do
take
shortcuts
and
we
we
call
them
out
we're
not
trying
to
say
that
it's
magic
but
yeah.
C
So
so
this
is
the
monolith
and
then,
in
the
workshop
we
kind
of
walk
through
creating
the
different
services.
So
we
have
an
inventory
service.
You
can
see,
there's
a
little
number
here.
It
says
like
500
and
something
left
or
734
left,
there's
a
little
icon
for
a
location
and
then
there's
the
products
themselves
like
the
descriptions
and
the
and
the
images.
C
A
C
Yeah,
so
so
that's
that's
the
monolith
and
then
over
time.
We
we
take
them
through
the
microservices
journey
and
we
not
only
do
the
transformation
of
the
of
the
business
logic,
but
we
introduced
some
of
the
some
of
the
concepts
in
the
ilities
of
a
microservice
like
you
know,
reliability
and
fault,
tolerance
and
scalability
and
so
forth,
and
we
end
up
with
I'll
switch
over
to
the
other
namespace
in
this.
C
In
this
open
shift,
cluster
called
user
one
dash
cloud
native
apps,
and
this
is
the
the
sort
of
the
the
end-all
be-all
micro-service
version.
There's
a
lot
of
stuff,
there's
lots
of
stuff
going
on
here,
but
you
can
see
the
individual
services
like
we
have
a
cart
service
which,
which
is
backed
by
an
infinite
span:
data
jboss,
red
hat
data
grid,
which
is
an
in-memory
data
grid.
C
There's
the
order
service
which
handles
ordering
and
it's
backed
by
database,
there's
the
payment
gateway,
which
is
using
serverless
technologies
with
kafka
to
respond
to
orders
that
have
when
an
order
is
placed
something
is
pushed
into
the
kafka
stream.
And
then
that's
responded
to
by
this
serverless
component
here
the
payment
service,
and
then
we
have
our
kafka
cluster
and
we
have
an
inventory
service
which
a
lot
of
these
have
little
mini
uis
on
them,
which
we
use
throughout
the
workshop.
C
To
kind
of
give,
you
know
it's
it's
it's
hard
to
get
your
head
around
all
this
at
one
time,
so
we
kind
of
build
up
slowly,
so
we
say:
okay,
build
the
inventory
service
and
go
make
sure
the
info.
The
fake
inventory
ui
is
okay
and
you're,
seeing
the
the
locations
and
you're
seeing
the
quantity
and
the
item
id,
and
then
we
also
do
things
like
we'll
kill
off
the
the
pod,
and
this
thing
will
go
dead
and
then
come
back
to
life
automatically
through.
C
You
know,
self-healing
of
pods,
which
we
kind
of
demonstrate
some
of
the
health
probes
and
kubernetes.
So
that's
kind
of
a
simple
example:
we
have
some
others.
We
also
have
a
spring
boot
catalog
service,
which
shows
you
the
different
things
available
in
the
catalog.
If
I
can
click
properly
I'll
show
you
the
catalog,
which
is
kind
of
like
basically
the
ui
but
boiled
down
to
a
table-
name
description,
price
inventory
or
a
quantity,
so
yeah.
C
A
B
D
C
So
here's
the
front
end
so
the
so
the
big,
the
big
finale
here
is
you
go
to
in
your
cart.
You
you
add
something
to
your
cart.
You
head
over
to
your
cart,
you
check
out
and
then
we
ask
you
for
payment
information.
So
I'm
like
don't
copy
this
down
or
buy
anything
all
right
exploration,
I'm
just
making
stuff
up
here.
1940.
C
nice
just
put
in
junk
you
check
out
and
then,
when
you
check
out
that
kind
of
fires,
everything
off
and
you'll
see,
this
payment
starts
to
come
alive
because
the
order
was
posted
to
kafka.
The
kafka
or
serverless
payment
gateway,
responded
to
that
notice
that
got
an
event
from
kafka
and
it
came
alive
and
processed
that
payment
and
then
with
some
built-in
delays
to
simulate
sort
of
real-life
delays.
And
so
then,
if
I
had
oversight
orders,
you
can
see
my
order
here
has
now
been
completed.
C
A
So
actually,
just
because
you
know
we
keep
mentioning
it
or
whatever-
and
I
I
have
this
weird
history,
but
can
you
explain
a
little
bit
about
kafka
is
because,
what's
funny,
at
least
for
me,
is
that
when
kafka
came
out,
it
was
essentially
real-time
hadoop
and
almost
nobody
talks
about
its
ability
to
do
that
anymore,
which
was
you
know.
Basically,
a
map
reduce
functionality,
but
that's
what
it
kind
of
originally
launched,
as
so.
A
D
Yeah
so
sure
so,
cop
card
is
based
on
address
your
distribution
messaging,
so
you
can
actually
use
the
just
simple
message
broker
to
handle
your
topic
message
about
payload
from
your
application
or
some
client
specific
site.
But
sometimes
you
got
a
lot
of
tons
of
the
the
payload
or
messaging
from
1000
of
your
microsoft
application,
so
copycat
cluster
definitely
can
handle
their
distribute,
metrics
and
distribute
payload
on
your
cluster.
D
A
Well-
and
we
know
it's
like
super
scalable
right
because
it
came
out
of
twitter
right
originally
and
it's
how
they
used
to
do
exactly
what's
referred
to
as
the
twitter
fire
hose,
which
is
actually
a
very
hard
license
to
get
where
you
can
kind
of
get
all
of
twitter's
feed,
which
you
know,
I
think
it's
limited
to
like
six
companies
in
the
world
or
something
one
of
them.
Oddly
enough,
I
don't
know
if
they're
still
around,
but
they
there's
a
boston
company
called
crimson
hexagon,
which
tells
you
about.
A
B
A
And
sorry
and
crimson
is
harvard's
colors,
so
the
cr
you
see
crimson
in
the
boston
area,
a
lot
more
often,
I
think
than
you
see
it
kind
of
elsewhere
in
the
world
just
because
of
harvard
but
yeah.
So
I
I
used
to
have
some
friends
who
worked
over
there
and
I
was
just
like
that
is
the
best
company
name
if
you
are
super
evil.
A
Yeah
anyways,
so
all
right
cool.
Thank
you
for
that
kind
of
little
kind
of
sojourn
around
kafka.
You
know
and
yeah.
So
this
is.
This
is
kind
of.
What
I
wanted
to
show
is
that
you
know
here
we
have
kind
of
a
put
together
fully
kind
of
micro
services,
sized
app
right
that
we
can
do
experiments
with
right.
So
we
can
actually.
C
A
About
how
can
we,
you
know
hey,
we
want
to
do
our
payment
gateway.
We
want
to
switch
from.
You
know:
payment
gateway,
a
to
b.
I
actually
used
to
know
the
list
of
four,
but
I
can't
think
of
them
right
now,
but
maybe
it's
just
like
stripe
to
you
know
to
somebody
else,
and
you
can
do
that
with
something
like
a
canary
migration.
For
example,
you
know,
and
you
can
have
kind
of
in
parallel
accounts
with
them
while
you're
running
and
then
you
know,
and
just
basically
farm
your
traffic
across
yeah.
B
C
Oh,
that's
a
good
question.
I
mean
it's
true,
it's
a
generic
challenge.
I
mean,
without
with
or
without
openshift,
it's
challenging
to
do
that,
like
safely
in
a
production
environment,
to
replace
one
service
with
another
or
move
it
from.
You
know
a
developer's
desktop
to
a
test
environment
to
production.
C
C
So
if
you,
if
you
want
to
you,
know
bring
in
a
new
version
of
the
payment
gateway,
maybe
you
want
to
only
expose
it
to
10
of
your
users
and
see
if
that
thing
blows
up
instead
of
exposing
it
to
all
100
and
it
blows
up
and
you're.
You
know
you're
out
of
business
yeah
those
kinds
of
features.
I
mean
they're
they're
great
features,
but
you
know
still
there's
some
challenges
in
setting
that
up.
A
On
developer
tools,
one
of
the
things
that
you
see
over
time
is
developer
tools,
get
better
as
the
people
developing
developer
tools
start
to
understand
the
problem
better
and
kind
of.
By
way
of
example,
one
of
the
things
that
I
read
that
was
really
really
interesting
about
why
ides
are
useful
versus
text.
Editors
is
basically,
if
you
have
a
highly
dynamic,
changing
language
like
a
language
that
is
kind
of
changing
how
its
constructs
happen.
C
Yeah,
there's
so
you're
absolutely
right
about
the
language
stability
leading
to
you
know
more
feature-rich
ides,
but
that
also
can
apply
to
the
intersection
between
the
developers
ide
and
like
the
deployment
target.
So
if
you
know
once
you're
done,
writing
the
code,
then
what
like
normal
in
a
in
a
very
efficient
production
environment,
you
would
push
code
to
git
or
github
or
wherever
and
then
that
that
would
set
off
some
pipeline.
That
would
go
off
and
do
it,
but
for
a
developer.
Who
is
who
wants
to
kind
of
do
that
ahead
of
time?
C
They
want
to
be
able
to
deploy
on
their
own
desktop
right,
the
the
tooling
for
getting
a
an
app
defined,
it's
dependencies
defined
and
deployed,
and
then
running
the
app
in
sort
of
a
production
like
environment.
I
think
that
tolling
is
still
in
its
infant
stages
and
I
think
it's
getting
better
with
some
of
the
work
in
the
eclipse
project,
eclipse
j
and
which
is
a
web-based
ide,
but
they're,
also
working
on
defining
how
a
production-like
environment
can
be
instantiated
by
a
developer.
So
they
can
run
this
code
after
they
after
they're
done.
C
Writing
it
in
what
would
look
like
a
production
environment.
So
you
have
a
fake
database
and
it's
a
real
database
with
fake
data,
but
it's
using
the
same
schemas
as
production.
You
have
the
same
services
as
production
and
you
can
kind
of
test
your
code.
So
those
are
that's
a
really
important
advancement
that
we're
seeing
that
I'm
seeing
personally,
the
other
one
I
found
really
interesting
is
istio.
We
didn't
talk
about
service
mesh
much
today.
We
do
use
service
mesh
in
this
application,
but
it
was
a
interesting
article.
C
Someone
posted
on
one
of
the
internal
istio
boards
about
the
title
of
the
blog
post
was
is
essentially
the
paraphrasing
it
is
like.
Istio
should
fade
into
obscure,
not
obscurity,
but
fade
into
the
background.
It
should
not
be
something
developers
have
to
care
about
today,
and
so
I
think
that
as
technology
sediment
into
the
underlying
platform,
I
think
they
should
you
know,
be
essentially
transparent
when
they're
intended
to
be
transparent
and
not
have
to
have
a
developer,
write
some
crazy,
gamol
or
understand
even
what
a
service
mesh
is.
C
B
C
I
yeah,
I
don't
think,
and
so
mq
is
like
a
message
queue
in
general,
like
the
durable
messaging
concept.
I
think
they
share
some
things
in
common
right
kafka
has
you
know,
topics
and
subscribers
and
pub
sub
and
that
kind
of
stuff
it
doesn't
aim
to
solve
the
same
set
of
problems
that
a
message
queue
would
solve.
Kafka
is
very
good
at
storing
large
amounts
of
data
very
quickly
and
sort
of
a
time
series.
You
can
then
go
back
and
replay
it,
and
things
like
that.
You
can
cluster
it.
C
It's
very
highly
highly
scalable
and
message
queues
are
more
about
like
if
you,
if
you
take
money
from
one
account,
you
better
it
better
land
in
another
account
or
that
operation
should
fail
together.
It
shouldn't
be
where
you
take
the
money
from
one
account
and
then
maybe
the
other
one
happens
at
some
point
in
the
future.
But
nobody
really
knows
so
message
queues.
Have
these
kind
of
guarantees
about?
You
know
delivery
mechanisms
that
that
kafka
really
doesn't
have
as
a
as
a
as
a
design
goal.
If
you
will
so.
C
A
Capital
r
and
it's
a
reliable
messaging,
so
it's
guaranteed
to
go
through
often
item
potent,
so
you
can
actually
rerun
the
same
message
multiple
times
and
it
will
not
trigger
the
same
event
again,
whereas
kafka
is
way
more
like
pipeline,
and
so
it's
like
you
know
we're
talking
about
the
twitter
firehose
right.
It's
like
if
you
drop.
A
On
the
floor,
it's
not
that
big
a
deal
right.
You
know,
whereas,
like
a
message,
queue
will
never
drop
one
on
the
floor,
it's
much
more
like
a
database,
so
it's
in
some
ways
similar
to
like
storing
something
in
you
know
like
a
database
versus
you,
know,
kind
of
storing
things
on
a
file
on
disk
or
something
it's
it's
kind
of
hard
to
compare.
But
kafka
is
generally
much
more
about
speed
of
pipe
rather
than
guaranteeing
every
message
gets
through.
D
A
C
B
A
So
yeah
we
wanted
to
bring
it
up.
You
know
in
our
chit
chat
at
the
beginning
of
the
show
we
tend
to
you,
know
kind
of
talk
about
stuff,
that's
going
on
and
as
many
of
you
are
aware,
it
was
martin
luther
king
jr
day
on
monday
and
and
we
wanted
to
kind
of
shout
out
to
one
of
the
practices
that
red
hat
does
for
a
bunch
of
years
now
and
run
by
an
organization
called
build,
is
which
we
we
figured
out.
A
This
day
of
service
during
mlk
day,
and
so
where
we
basically
organize
a
bunch
of
different
activities
that
people
can
participate
in
and
you
know
if
you
participate
in
these
you,
you
can
kind
of
take
the
day
off
from
work
without
actually
kind
of
treating
it
as
a
vacation
day
and
work
on
this
service
stuff,
and
there
was
a
hackathon
in
particular
that
that
took
place
that
maybe
we'll
cover
the
results
of
in
a
couple
weeks.
I'm
not
sure
I
know
I
know
it
was
a
24-hour
hackathon.
A
B
A
A
B
A
Sorry
and
then
points
let's
see
if
we
can
find
the
window
all
right.
So
for
our
guests,
one
of
the
things
we
like
to
do
in
the
level
of
hour
is
we
give
out
what
we
refer
to
as
sweet
sweet
internet
points
and
the
sweet
sweet
internet
points
are
think
back
to
slashdot
old
school.
What
they
used
to
call
karma
same
kind
of
idea.
A
And
so,
as
I
explained
last
episode,
we
have
been
messing
with
the
numbers
a
little
bit
except
this
should
make
most
people
happy.
The
numbers
largely
went
up
versus
last
week.
They
largely
went
down,
but
I
think
I
think
I'm
done
futzing
with
the
numbers,
and
this
is
all
in
support
of
making
these
sweet
sweet
internet
points
having
a
value
beyond
intrinsic.
B
A
A
A
A
A
You
know
when
we
really
appreciate
y'all
participating.
You
know
james
and
daniel.
If
you
want
to,
all
you
have
to
do
is
go
to
the
link
there
and
you
can
get
your
own
internet
points.
Debt
is
short
for
detective,
I
thought
so,
but
then
I
wasn't
sure
I
think
it's
a
it's
a
a
pop
culture
reference
that,
because
I'm
too
much
of
a
nerd,
I
don't
get.
A
Yes,
so
thanks
again
for
everybody
for
participating,
we
really
appreciate
it
and
we
would
like
to
see
more
internet
points
in
the
future
and
you
know-
and
I
will
I
I
continue
to
try
to
convince
other
people
on
the
channel
to
give
out
internet
points
as
well
and
maybe
we'll
we'll
get
there
someday
and
but
yeah.
That's
that's
what
I
got
do
we
have
any
kind
of
closing
questions
or
comments
or
thoughts
or
anything
else
that
you'd
want
to
kind
of
add.
B
B
A
C
A
C
Yeah,
okay,
that's
cool
yeah
thanks
a
lot
for
having
us
on
very
fun
to
to
kind
of
reminisce
a
bit
about
where,
where
where
it
came
from
and
where
we're
going
with
it.
So
hopefully
we'll
find
some
additional
new
features
to
add
and
more
compelling
tech
to
add
to
it
to
kind
of
showcase
that
stuff
lots
of
interesting
things
happening
to
add
to
that.
B
Thanks
again
and
islam,
there
is
a
quick
question
found
here
about.
You
know,
open
shift,
cluster
sizing
and
everything
reach,
I
would
say,
potentially
it
depends
on
the
size
and
your
needs
of
that
production
cluster,
but
it's
always
nice
to
have
a
backup
cluster.
Just
in
case,
you
need
like
to
upgrade
an
upgrade
goes
bad
right,
so
it
really
depends
on
your
scenario.
Work
with
your
red
hat
account
team
to
figure
out
what's
best,
for
you
is
what
I
would
tell
you,
because.