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From YouTube: GitOps Guide to the Galaxy (Ep 27) | Argo Workflows
Description
Want to understand how Argo Workflows works? In this episode, we're joined by Alex Collins, Principal Software Engineer at Intuit and Technical Architect of the Argo Workflows project, to talk about Argo Workflows. We'll discuss the why and the what around Argo Workflows and how to best use Argo Workflows with Argo CD. New to Argo CD? Do you need declarative and version-controlled application definitions, configurations, and environments? Argo CD is a declarative, GitOps continuous delivery tool for Kubernetes that can help make your application deployment and lifecycle management more automated, auditable, and easy to understand. Join us to learn more and get started with Argo CD.
Learn more:
https://argoproj.github.io/cd/
Follow us:
Christian Hernandez https://twitter.com/christianh814
Alex Collins https://twitter.com/alex_e_collins
What is GitOps Guide to the Galaxy?
Every other Thursday at 3pm ET hosts Christian Hernandez and Chris Short sit down to discuss everything in the GitOps universe, from end-to-end CICD pipelines to creating Git workflows.
Subscribe to Red Hat's YouTube channel: https://www.youtube.com/redhat/?sub_confirmation=1
About OpenShift:
Red Hat OpenShift is an open source container application platform based on the Kubernetes container orchestrator for enterprise application development and deployment.
Openshift.com https://red.ht/33Fh6uV
OpenShift on github https://github.com/openshift/
OpenShift on redhat.com https://red.ht/2o4ccDk
#RedHat #GitOps #Kubernetes
A
A
And
we're
live.
Thank
you
everyone
for
joining
on
another
episode
here
on
github's
guide
to
the
galaxy.
I
will
be
your
captain
in
this
journey
here.
My
name
is
chris
hernandez
and
today
I'm
happy
to
be
joined
by
my
co-captain
here
by
by
alex
collins
here
alex.
Can
you
give
a
just
kind
of
like
a
brief
introduction
of
who
you
are?
Where
are
you
coming
from
and
kind
of
what
you
do
there
hi
christian.
B
So
hi
good
morning,
my
name
is
alex.
I
am
a
principal
software
engineer
into
it
where
myself
my
team
work
on
effectively
the
kind
of
enterprise
kubernetes
platform
for
the
company
and
amongst
the
kind
of
tools
and
products
and
capabilities
we
produce
for
them.
We
work
on
a
suite
of
open
source
products
called
argo,
and
I
am
responsible
for
argo,
workflows,
nargo
events
or
anything
that
kind
of
deals
with
data
within
the
argo
world.
A
Nice,
nice
awesome
and-
and
I
tweeted
this
out
a
couple
days
ago-
I
was
really
excited
to
have
you
on
and
really
excited
about
today's
subject,
because
I
actually
kind
of
had
to
hunt
alex
down
a
little
bit
in
kubecon.
I
was
hunting
him
down.
I
was
like
hey
alex.
I
need
to
talk
to
you.
I
need
you
to
come
on,
come
on
my
stream,
so
very,
very
excited
to
have
alex
alex
come
on,
because
I
I've
been
wanting
to
do
a
stream
about
argo
workflows
right.
A
So
here
at
red
hat,
we
use
a
lot
of
argo.
Our
our
enterprise,
offering
get
ups
offering
is
based
on
argo,
so
our
argo
cd.
So
we
use
a
lot
of
argo
cd
here
and
a
lot
of
our
a
lot
of
our
users.
A
lot
of
our
customers
are
always
asking
about
workflows
he's
like
well,
you
know
what
do
you
think
about
workflows?
A
From
the
from
the
source
here
is
and
get
get
alex
on
here,
so
so
yeah
alex
what
what
did
you?
What
did
you
think
about
going
going
back
to
kubecon
so
like
we
were
both
kind
of
there
at
kubecon?
It
was
a
little
weird
coming
back
right
after,
like
being
you
know,
not
having
to
do
the
things
and
doing
everything
virtually
now
in
person.
I
thought
it
was
a
kind
of
nice
that
it
was
kind
of
scaled
down.
There
wasn't
a
lot
of
people
there.
B
It
felt
like
the
first
normal
thing:
I've
done
in
a
very
long
time.
Yes,
it
felt
like
it
was
the
first
time
getting
on
a
plane
in
a
year,
the
first
time
kind
of
being
in
an
environment
with
a
lot
of
other
people
for
for
for
a
time,
but
it
felt
really
good
to
kind
of
be
able
to
spend
some
time
with
my
colleagues
and
meet
with
other
people
from
the
kubernetes
community.
That
was
really
good
and
it
was,
it
was
definitely
different.
B
A
Yeah
yeah,
it
wasn't,
I
thought
I
thought
so
as
well.
It
didn't
feel
so
crowded
right.
It
was
kind
of
nice.
You
know,
I
think
it
was
a
good
first
step
back
into
like,
like
you
said,
kind
of
like
it
felt
like
being
back
normal,
so
so
anyways
again,
thank
you
for
for
for
coming
on
and-
and
I
always
like
having
the
intuit
folks
come
on,
I
mean
we've
had
hendrick
on
before
we
had
another
alex
on
before
there's
a
lot
of
alex
alex's
into
it.
B
A
A
A
What
what
is
workflows
right,
just
kind
of
from
a
high
level
right,
there's,
there's,
there's
the
argo
city
that
that
sits
under
the
umbrella
of
article
project,
a
lot
of
people
say
argo
and
they
actually
what
they
mean
is
argo
cd,
not
knowing
that
argo's,
actually
a
project
with
with
a
lot
of,
I
guess,
sub
projects
a
lot
of
products
under
it.
I
don't
know
what
to
call
it,
but
but
yeah
can
you
talk
about
like
what
is
our
goal?
Workflows.
B
B
B
The
the
default
model
is
that
you
run
a
number
of
pods
on
kubernetes
and
they
can
be
killed
at
any
point.
It's
fine,
it's
kubernetes
makes
one
promise
and
it
is,
it
will
kill
your
product
at
some
point.
That's
the
promise
it
makes
yeah
and
it
will
give
you
no
warning
of
that
which
is
great
for
like
a
web
application,
a
status
web
application,
but
but
a
workflow
is
typically
there
can
be
a
lot
longer
running.
B
You
typically
want
the
pods
within
your
workflows,
the
processes
within
your
workflows
to
run
to
completion,
and
if
they,
if
they
take
an
hour
to
run,
then
you
don't
necessarily
want
kubernetes
to
kill
them
during
that
procedure
and
that
they
are
so
they're
not
typically
irreplaceable,
but
they
do
tend
to
run
for
a
specific
period
of
time.
So
that's
that's
kind
of
really
what
one
of
the
things
that
workflows
brings
to
the
table
is
the
ability
to
kind
of
run
short-lived
control
processes
there.
B
The
other
thing
that
workflows
does
is
because
it
leans
on
how
kubernetes
does
scaling
it
can
scale
out
to
very
large
workflows,
yeah,
very
large,
workflows
and
just
kind
of
step,
just
just
to
kind
of
step
back
in
the
conversation
a
bit
just
to
define
what
a
workflow
is.
I
mean
the
workflow
is
just
defined
as
a
series
of
processes
that
may
or
may
not
run
on
a
schedule.
So
kubernetes
provides
like
built-in
job,
but
it's
very
simple.
B
Often
there
you'll
have
a
workflow
where
you
have
a
first
step
which
goes
and
pick
what
actual
work
needs
to
be
done,
and
then
it'll
fan
out
running
one
process
for
each
of
those
pieces
of
work,
and
then
maybe
it'll
fan
back
in
later
on.
To
do
it,
that's
kind
of
what
a
workflow
is
and
argo
workflows
allows
you
to
do
that,
but
you
don't
need
to
use
kind
of
any
scheduling
system
because
you
can
use
this.
B
You
can
just
install
it
straight
in
your
clusters,
there's
no
kind
of
special
setup
for
it.
It's
very
easy
to
get
started
compared
to
other
similar
pieces
of
software,
and
it
can
do
kind
of
very
it's.
You
know
it's
just
designed,
and
it's
also
tuned
and
optimized
to
do
very
large
scale.
Workflows,
and
you
know
people
today
are
running
workflows
with
you
know.
Twenty
thousand
thirty
thousand
individual
steps
within
those
workflows
and
I've
heard
people
talking
about
hundreds
and
steps
and
actual
kubernetes
itself
can
only
do
300
000
steps
like
by
design.
B
So
we
provide
that,
so
you
can
specify
your
workflow
as
a
you
know:
kubernetes
custom
resource
and
when,
when
it
executes,
then
you
can
use
all
the
kubernetes
apis
to
interact
with
it.
You
know
all
those
standard
apis
that
the
very
similar
ones
use
for
kind
of
pods
and
deployments,
and
so
you
can
review
the
logs
of
the
different
steps
and
because
it
you
know,
workflows,
is
kind
of
a
general
workflow
execution
engine.
It
is
pretty
popular
for
building
platforms
on
top
of.
B
So
if
you
need
to
build
some
kind
of
batch
processing
platform
on
kubernetes,
something
that's
running,
you
know
tasks
and
you
want
an
api
and
say
you
know,
please
run
these
tasks
and
I
want
you
to
run
any
of
them.
The
workflows
works
really
well
for
that,
and
so
it's
pretty
popular,
it's
very
popular
inside
the
machine
learning
community.
B
So
google
pipelines
uses
argo
workflows
as
its
workflow
execution
system,
and
I've
spoken
to
quite
a
few
different
people
about
how
they
use
it
and
it
in
into
it.
We
kind
of
it's
the
execution
component
of
our
batch
processing
platform
and
of
our
machine
learning
platform
where
it's
used
to
perform
kind
of
model,
training
and
execution
for
it.
B
A
Yeah
well,
it
sounds
all
I
think
I
think
you
I
think
you
hit
a
very
interesting
point
here.
Right
is
like
their
kubernetes
itself
does
have
effectively
is
what
you're
describing
as
a
batch
system
right
like
it's.
Basically,
it's
like
you
run
a
job
and
it,
but
it's
very
simplistic
right.
If
you
either
run
a
job,
if
you
need
it
to
run
at
regular
intervals,
you
have
like
the
cron
job
right,
which
is
like
you
have
that,
but
it's
it's.
A
It's
super
simplistic
because
you
know,
although
it
has
retries
it's
very
simplistic
in
retry,
because
it's
either
like
it'll
retry,
when
it
fails
right,
you
can
set
it
up
to
say
hey
when
it
fails
retry
but
but
like
if
you're,
if
you're
some
things
are
more
complex
than
that
right.
Sometimes
I
want
to
retry,
even
if
it
succeeds
like
there's,
there's
certain
conditions
and
things.
A
So
what
you're,
effectively
saying
what
workflows
is,
is
putting
like
an
intelligence
around
running
things
that
need
to
run
in
batch
right
and
things
that
not
long-lived
containers,
something
like
like,
like
you
mentioned
like
like
a
web
server
right
or
maybe
like
a
a
a
stateful
application,
or
something
like
that.
That
has
a
long
live
lifetime.
A
But
if
you
look
at
it,
argo
workflows
has
more
stars
on
it
on
github.
So
there's
like,
if
you
know
it's
not
a
competition
or
anything,
but
it's
you
know
it's.
A
lot
of
people
are
using
our
workflows
and
a
lot
of
you
know,
especially
our
users
at
red
hat,
are
starting
to
ask
about
workflows.
So
so
it's
so
it
seems
that
workflows
came
about
inside.
A
B
A
B
B
A
B
A
Get
you
gotcha
what
what's
what's
really
interesting
and
I'd
like
to
hear
kind
of
like
that,
the
usage
of
of
of
workflows,
insight
into
it
and
into
it,
and
I
think
you,
you
alluded
to
a
little
bit
right,
like
a
lot
of
people
doing
like
batch
work,
a
lot
of
doing
like
aiml
work
right
like
when
you
have
to
do
something
a
lot
of
batch
work
at
scale.
It
sounds
like
you
guys
that
into
it
are
doing
a
lot
of
that
in
ai.
You
know
in
machine
learning
and
artificial
intelligence
work.
B
No,
we
we
so
it
I
mean
we.
Basically,
it
is
installed
like
by
default
in
into
it
clusters.
So
it's
just
it's
just
there
and
running,
and
so,
if
you
want
to
run
a
workflow,
you
can
just
run
one
the
same
way.
You
can
just
run
a
deployment.
This
is
it's.
You
know,
there's
no
setup
for
you
to
do
that,
so
people
use
it
for
for
all
sorts
of
different
assets,
all
sorts
of
different
things,
so
we
it
could
well
be
that
the
people
are
using
it
for
ci
cd.
B
We
we
it's
not
it's
kind
of
an
interesting.
I
always
think
it's
quite
interesting.
We
don't
ever
really
target
ci
cd
use
cases
or
more
ci,
obviously,
but
people.
You
know
that
is
a
popular
use
case
for
for
workflows.
You
know
triggering
triggering
a
build
offer
off
that
yeah.
That's
fine!
I
think
it's
quite
hard
to
build
a
generic
workflow
engine
without
making
it
work
quite
well
for
ci.
A
Yeah
yeah
good
good.
That's
a
that's!
That's
a
very
good
point.
Right,
like
you
inadvertently,
create
something
that
right
like
if
you're
gonna
do
a
workflow
inadvertently
people
say
hey.
This
might
be
a
good
ci
system
because-
and
it's
always
interesting
when
you
build
something
and
and
like
people
start
using
it
for,
like
other
things,
you're
like
oh
interesting,
I
never
thought
about
that,
but
yeah.
I
guess
you
could
use
it
for
for
for
something
like
that,
so
the
ci
yeah,
so
a
lot
a
lot
of
people.
A
I've
talked
to
using
it
for
ci
for
at
least
for
testing
like
something
like
a
like
a
feature
branch
right
like
they
would
they
they
can
set
up
something
really
quick
to
test
a
feature
branch
using
workflows,
and
I
think
that's
that's
that's!
That's
that's
really
cool
so
so
yeah.
So
the
the
some
of
the
work
that
you
guys
done
inside
it
sounds
like
a
lot
of
the
projects
that
came
up
insight
into
it
with
the
argo
project
are
basically
just
out
of
necessity.
A
A
Yeah
yeah
good
cool
cool,
so
I
think
I
think
in
case
you
guys,
I'm
gonna
drop
some
links
in
the
chat
here
case.
You
guys
want
to
read
more
about
workflows
right,
there's,
there's
a
link
there.
You
can
definitely
go
to
the
read
the
docs
there's
great
video
there
right
by
the
way,
I
think,
alex
you
did
that
video,
so
you
can
see
that
there
is
as
well
some
good
good
things
there.
A
So
I
think
if
anyone
has
any
questions
by
the
way
go
ahead
feel
free
to
drop
it
in
the
chat
I'll
I'll
feed
it
through,
but
I
think
I
think,
alex
hopefully,
let's
cross
our
fingers
with
the
demo
gods.
Here
I
think
alex
is
going
to
show
us
a
little
bit
about
kind
of
like
a
use
case.
You
would
use
or
kind
of
just
kind
of
just
show
what
what
what
our
workflows
looks
like
or
what
it
can
do.
Yeah,
let's
cross
our
fingers
here,
demo
guides,
hopefully
it'll-
be.
A
B
There
it
goes
so
what
I'm
gonna
do
is
I'm
gonna,
I'm
gonna,
I'm
gonna
avoid
the
cli,
I'm
just
gonna
stick
with
the
user
interface,
and
actually
you
can
go
and
check
this
out
yourself,
I'll.
Just
I'll
share
the
url
here
in
the
chat.
Can
I
do
that?
Oh
yeah,
the
yeah,
the
test
system
there
you
go.
This
is
a
public
test
system.
A
B
So
this
is,
this
is
kind
of
like
our
demo
system
workflows
to
apps
to
arc
approach
to
io,
and
this
is
kind
of
there
to
showcase
some
of
the
user
interface
features
of
it
and
I'm
just
going
to
go
through
a
couple
of
features
here
to
kind
of
talk
a
little
bit
about
them.
So
this
is.
This
is
the
main
page.
This
is
the
page
that
most
people
will
spend
their
time
in
here,
and
this
page
basically
allows
me
to
have
a
little
look
at
kind
of
running
and
completed
workflows.
B
We
have
a
chron
workflow
which
allows
you
to
specify
a
workflow
that
runs
on
a
period
of
time,
so
we've
got
one
here
running
this
particular
tempeh,
every
five
minutes,
so
you
can
see
that
provides
the
information
there
about
that.
When
it's
going
to
run
and
inside
that
template,
I
think
we
will
find
that
it
specifies
a
particular
template
to
run
afterwards
called
coin
flip,
and
basically
this
this
template
is
a
template
that
we'll
do
a
flip
of
coin.
That'll
run
every
five
genji.
B
So
for
a
little
look
at
the
templates
here
we
can
have
a
little
look
at
the
coin.
Flip
template
here,
I'm
just
going
to
kind
of
get
straight
to
the
spec.
Okay,
let's
go
straight
to
spec,
so
basically
inside
a
workflow
you'll
specify
a
series
of
templates.
The
templates
will
execute
in
order,
and
in
this
example,
we've
basically
got
a
template.
That'll
flip
a
coin
step.
One
then
step
two
is
conditional.
B
So
if
the
output
of
step
one
was
heads,
then
it'll
run
that
one
otherwise
it'll
run
tails.
So
basically,
this
is
a
simulation
from
running
a
conflict
then
further
down
in
this,
we
have
a
kind
of
a
script
here
that
shows
you
what's
actually
going
to
flip
the
coin,
so
I'm
basically
specifying
a
script
here,
a
python
script,
that's
executed
that
imports,
the
random
library
and
then
it
just
does
flips
a
coin
and
prints
out
the
result
of
that
yeah
and
then
also
in
here.
B
B
Let's,
if
it's
there,
let's
try
again
sorry
there
we
go
there,
we
go
so
previous
examples
are
on
there
and
you
can
see
here.
I've
just
gone
through,
and
this
is
kind
of
a
visual
representation
of
that
particular
workflow,
showing
that
it's
flipped
a
coin
and
then,
as
a
result
of
it,
being
heads
it's
from
the
head
step
there
and
I
can.
I
can
click
on
the
heads.
I
hope
this
works.
This
was
broken
earlier
today.
Fingers
crossed
it
should
shut
her
against
the
logs.
This
is
what
it's
like.
B
B
What's
going
on
with
your
workflow,
I
think
maybe
you
just
look
at
the
ci
cd
use
case
kind
of
a
really
common
thing
that
people
need
to
do
is
they
need
to
actually
go
into
their
system.
They
don't
tend
to
worry
too
much
about
when
things
have
been
successful,
but
what
is
typically
a
lot
more
interesting
is
when
something
has
been
unsuccessful,
which
doesn't
appear
to
be
the
case
today.
B
It
allows
you
to
go
into
that
into
that
same
user
interface
when
you
click
down
into
that
particular
workflow,
then
problems
with
it
are
highlighted
in
red
and
it's
very
easy
to
get
in
in
there
as
well.
So
what
I
was
going
to
do
is
I'm
just
going
to
submit
a
new
workflow
here
and
I'm
going
to
just
copy
and
paste
it
from
this
document.
I
have
here
it
goes
and
so
being
a
being
a
kind
of
kubernetes
object
that
appears
in
the
kubernetes
api.
B
Obviously,
my
workflows
get
a
name
and
they
run
in
a
namespace
and
so
that
namespaces
allows
me
to
isolate
different
teams
and
each
different
team
and
user
can
have
a
different
name
space.
They
tend
to
run
under
a
specific
service
account
following
their
permissions,
and
this
one's
got
some
parameters
here.
So
the
parameter
I've
got
here
is
it's
got
a
message
and
it's.
The
value
is
hello.
Argo!
That's
going
to
print
out
hello
ago
and
there's
I
got
a
template
here:
that'll!
Take
that
input
that
parameterized
input.
B
So
in
this
example,
that
parameter
is
a
message,
but
you
know
that
could
be
a
git
branch
or
it
could
be
pretty
much
anything
else.
And
then
it's
going
to
run
this
container
here
and
that's
going
to
print
that
message
out
onto
the
console,
there's
some
kind
of
additional
configuration
about
ttls
and
so
forth.
So,
let's
just
create
that
okay,
so
there
it
goes
now
you
can
see
in
this
graph
again.
This
is
a
very
simple
one.
This
is
a
single
node
here,
so
it
doesn't.
B
B
Let
me
open
this
up,
so
I'm
just
going
to
bring
up
a
couple
of
examples,
see
if
I
can
pop
these
in
these
tabs
yeah
there
we
go.
So
this
is
just
kind
of
a
pretty
common
example
of
a
workflow.
You
know
it
starts
out
with
a
step
that
map
step
going
to
get
some
data
from
a
database,
splits
it
up
and
sends
it
elsewhere.
So
that's
one
example.
B
This
is
a
slightly
larger
example.
This
came
from
a
community
member
I
should
attribute.
So
this
is
kind
of
the
kind
of
thing
you
can
do.
So
you
know
I
can
do
a
big
fan
out
and
they
can
have
a
lot
of
steps
there.
So
you
can
see
it's
probably
about
20
steps
across
by
about
40
steps
down
so
they're
probably
running
about
you,
know
2
000
pods
in
that
one,
and
then
we
can
have
a
look
at
this
one
here
there
we
go.
That's
an
even
larger
one.
B
Quite
pleasurable,
to
see
that
so
there's
that
aspect
of
kind
of
running
them,
you
can
also
kind
of
create
a
thing
called
a
binding
that
allows
you
to
trigger
a
workflow
based
on
a
message
and
I'm
hoping
we'll
have
some
examples
here.
Yes,
we
do
have
loads
of
examples
here,
so
so
in
this
example,
this
one
has
been
triggered
by
a
github
event,
so
something's
happening
in
github.
Maybe
it's
a
pull
request
or
a
new
issue,
or
something
like
that.
We
have
a
very
busy
repository.
I
think.
B
Otherwise
we
wouldn't
see
this
and
we
can
see
this
is
now
running
a
container
and
then
I
don't
know
what
it
will
do.
Oh
it's
just
going
to
print
out
a
message.
So,
let's
see,
if
that
appears
in
the
logs
here
we
go,
and
you
can
see
that
it's
basically
printed
out
and
the
message
that
comes
from
from.
B
B
Yeah,
so
this
one's
failed,
but
that's
fine.
We
can
just
have
a
little
look
and
it
should
should
show
information
about
that.
If
it
does
doesn't
do
that,
I
can
kind
of
go
in
here
and
investigate
here
only
why
it
failed.
So
it
tells
me
this
pod
ran
for
for
too
long
so
pods
on
this
particular
cluster
have
to
run
within
a
minute
of
30
seconds,
maybe
otherwise
they
get
terminated.
That's
going
to
prevent
any
particular
workflow
consuming
too
many
resources.
B
We
weren't
actually
informed
about
this
and
the
comp
the
security
company
just
went,
didn't
didn't
speak
to
us
about
it
at
all
beforehand.
They
just
published
that
people
were
mining
monero
on
on
secure
workflow
instances.
Actually
they
were
also
at
the
same
time,
doing
it
on
github
actions.
So
github
actions
have
people
doing
monero
mining.
B
B
B
A
B
Of
a
new
visual
representation,
that's
been
in
the
user
interface
for
about
six
months
now.
This
just
allows
you
to
see
your
your
execution
here
of
of
your
code,
so
this
one
kind
of
just
shows
you
the,
which
is
like
a
cron
job,
and
that's
triggering
a
couple
of
things
in
here,
and
you
can
see
that
one
of
the
outcomes
of
that
is
it's
running
a
workflow
every.
B
B
So
I
mean
that's,
I
think,
that's
kind
of
it.
If
you
want
to
try
out
workflows,
it's
you
can
go
to
our
github
repository.
We
have
a
quick
start
guide
there
and
the
quick
start
guide
will
install
in
a
test
namespace
for
your
go
workflows,
controller
and
the
which
actually
runs
the
workflows
and
the
user
interface,
and
also
a
piece
of
software
called
mineo
which
allows
you
to
kind
of
pretend
you're
interacting
with
s3,
which
is
kind
of
a
useful
component
to
have
installed.
Okay,
so.
A
B
Great
piece
of
software,
one
of
the
kind
of
like
common
things
that
people
do
with
workflows
is
one
step
in
the
workflow
will
download
a
pretty
large
file
from
s3
or
in
the
gcp
in
the
gigabyte
range
and
then
perform
some
processing
before
uploading.
That
back
so
that's
kind
of
one
of
the
nice
features
about
it
makes
it
really
easy
to
get
that
data
out
of
those
systems
and
perform
processing
on
it.
A
Yeah,
what
would
I
and-
and
I
actually
went
through
some
of
those
examples-
and
it's
actually,
you
know
pretty
cool
some
of
the
things
that
you
can
do
with
workflows,
especially
the
the
dag.
You
know
how,
like
people,
build
those
trees
for
the
dependencies
right
so
like,
especially
if
you
have
workflows,
depending
on
other
workflows
that
depend
on
other
workflows
right,
like
you
know,
you
have,
you
know
a
depends
on
b
b
depends
on
you
know.
A
Oh
no
b
depends
on
a
c
depends
on
both
a
and
b
right,
and
you
can
kind
of
have
like
this
logic
tree
that
you
built
out,
which
is
definitely
you
know.
I
put
the
link
in
the
chat
for,
for
argo.
Workflows,
definitely
check
that
out.
It's
actually
really
easy
to
get
started,
especially
for
testing
purposes.
You
can
just
spin
up
a
kind
cluster
locally
and
test
that
out.
There's
a
lot
of
really
cool
features,
really
neat
features.
What
what
I?
A
What
I
actually
really
so
you
mentioned
earlier
about
how
like
events,
is
kind
of
like
a
a
sibling
right
or
or
something
that
came
out
of
a
necessity
that
you
found
in
workflows?
Can
you
talk
a
little
bit
more
about
what
events
does
for
you
with
respect
to
workflows
right
so
like
what
is
what
is
that
problem
that
was
was
being
solved
with
the
event.
B
B
We
call
them
event
sources,
but
I
think
more
commonly
they're
called
connectors
that
allow
you
to
connect
your
software
to
another
software
and
it's
kind
of
a
big
market
for
kind
of
moving
data
from
one
kind
of
event
queue
to
another
kind
of
kind
of
system.
You
know,
and
so
argo
events
kind
of
can
sit
in
front
of
argo
workflows
and
provide
you,
those
various
options
and
it's
interesting
pretty
popular
with
the
infrastructure
automation.
B
So
that's
like,
like
a
kind
of
a
hidden
use
case,
that
the
argo
workflows
allows
you
to
do
if
you
want
to,
if
you're
doing,
automation
on
your
clusters-
and
you
want
to
perform
various
bits
of
upgrades-
actually
algo
workflows
works
really
well
with
that.
Actually
can
work
extremely
well
with
argo.
Cd
actually
combine.
Those
two
together
use
argo
cd
to
determine
which
clusters
the
things
run
on
and
use
argo
workflows
to
define
the
actual
job.
B
That
needs
to
be
didn't
it
be
done
on
those
ones
so
yeah,
argo
events
has
gained
a
lot
of
popularity
over
the
last
year
as
well.
It's
not
hugely
popular,
like
argo
workflows,
but
it's
getting
a
good,
a
good
amount
of
momentum.
I
think
we're
seeing
some
good
great
new
features,
such
as
the
addition
of
support
of
redis
streams,
which
is
pretty
new
as
well,
which
we
didn't
have
that
before.
So
that's
pretty
exciting.
A
A
Yeah
it
and
it's
and
it's
actually
pretty
cool,
and
I
think
a
lot
of
again.
I
go
back
to
that
that
ci
use
case
where
it's
like.
Well,
how
do
I
trigger
ci?
You
know
it's
like
well,
you
can
use
you
know,
events
to
trigger
a
workflow
that
does
kind
of
like
your
ci.
You
know
build
system
again
kind
of
like
a
weird
people
are
using
the
software
kind
of
like
hey.
I
never
thought
that
they
would
be
using
it
that
way,
but
a
lot.
B
A
B
Yeah,
you
can
do
it
yeah.
I
I
will
write.
You
know
I
talk
about
a
bit
about
these
kind
of
broad
categories
of
what
people
use
it
for
these
bits
of
software
for,
but
I
actually
often
get
surprised
you
know
find
out
that
people
are
using
it
for
something
we
didn't
know.
So
you
know,
workflows
is
being
used
at
cern
for
orchestration
of
some
of
their
kind
of
particle
physics,
experimentation.
B
B
B
B
People
doing
all
sorts
of
machine
learning
everybody's
building,
the
machine
learning
platform
is
using
it.
I
think
we
always
have
interest
people
always
come
along
with
new
demos.
Oh
so
here's
one.
I
had
no
idea
that
people
were
using
it
for
litmus
chaos,
which
is
a
chaos
testing
framework.
Oh
okay,
yeah.
B
It
would
have,
it
would
have
just
completely
caught
me
by
surprise
and
we
so
we
run
a
monthly
community
meeting
third
wednesday
if
you
want
to
put
it
in
your
calendar
and
the
kind
of
cool
thing
about
that
is
people
come
along
and
demo
their
kind
of
products
and
it's
kind
of
the
most
popular
thing
for
it's
kind
of
almost.
What
makes
that
community
meeting
people
come
along
and
they
get
to
see
what
other
people
are
doing.
Yeah.
A
A
Yeah
and
it's
all,
it's
always
really.
What
I
found
interesting
about
just
like
the
argo
project
in
general,
is
that
the
a
like
the
data
science
community
has
really
latched
on
to
argo
project
like
those
the
software
a
lot,
because
I've
seen
a
lot
around
argo,
cd
and
workflows
when
it
comes
to
data
science
right,
and
so
I
think
it's
always
interesting
to
see
those
use
cases
as
well,
because
I'm
like
really
far
removed
right
from
more.
A
You
know
deployment
aspect
of
it
using
it
for
like
application
deployment.
You
know
using
you,
know,
argo
cd
for
get
ops
and
you
know
application
deployment,
maybe
for
workflows,
and
but
I
never
see
like
that
side
of
it
right.
It's
always
interesting
to
see
the
the
what
other
people
that
aren't
doing
necessarily
doing
software
delivery,
because
you
know
there's
there's
a
ton
of
use
cases
right,
especially
for
you
know.
A
B
So
so
like
we,
I
mean
you
can
go
and
look
at
our
users
file,
but
there's
there's
quite
a
few
automotive
manufacturers
in
there
companies
in
inside
that
file,
which
is
kind
of
kind
of
interesting,
but
it's
kind
of
hard
to
know
what
they're
using
it.
For
I'm
sure
our
is
probably
not
the
execution
engine
for
self-driving
cars.
I.
B
A
A
So
if,
if
you
want
to
check
out
the
the
the
upstream,
what's
what's
going
on
there
what's
coming
up
next
and
speaking
of
what
what's
coming
up
next,
so
are
there
anything
anything
that's
coming
in
in
workflows
that
you
guys
kind
of
like
that
you've
been
working
on
for
a
while
and
it's
and
then
you're
about
to
release?
Maybe
something
you're
excited
about.
B
B
B
I
kind
of
think
that
there
are.
There
are
kind
of
three
things
I'm
actually
really
excited
about
in
in
our
kind
of
you
know
in
the
future.
For
us
the
first
one
is
we've
just
you
know
a
lot
of
our
users
love
python,
but
we
we
haven't
kind
of
given
them
the
best
experience.
Yet
they
don't
really
want
they
don't
really
like
they
don't
love
yaml,
I
wouldn't
say
so.
We
are
now
gonna.
B
We
we
had
a
community
maintained
python
sdk,
but
what
we've
now
done
is
bring
that
kind
of
client
library
and
the
java
client
library
into
the
main
code
base.
So
those
are
all
going
to
be
updated
and
published
automatically.
So
that
would
be
a
better
experience
for
them
and
there's
been
a
new
joiner
in
argo
labs,
called
hero,
workflows.
B
So
people
who
want
to
write
workflows
in
python,
there's
kind
of
there
were
two
ways
of
doing
it,
which
one
was
to
use
kubeflow
pipelines,
and
then
they
have
a
transpire
that
transpiles
kubeflow
pipelines
into
into
workflows.
Then
there
will.
There
is
cooler
project
which
is
kind
of
a
python
sdk
that
that
transpiles
from
python
into
the
intention
is
to
transparent
to
the
airflow
and
argo
workflows
and
other
other
kind
of
systems,
and
now
there's
a
new
one
called
hera,
which
I
think
is
very
nice.
B
B
B
I
just
I
think
multi-cluster
in
general
is
you
know
a
big,
a
big
topic,
and
so
the
idea
of
a
multi-cluster
workflow
is
one
workflow,
where
the
steps
within
the
workflow
run
in
different
clusters
and
different
name
spaces,
and
that
has
loads
of
kind
of
interesting
use.
Cases
such
as
you
know,
my
workflow
is
a
full
end-to-end
deployment
because
yeah
the
start
of
the
workflow
builds
my
application
tests
it.
B
B
So
I
think
that's
going
to
be
really
neat
for
that
kind
of
use
case,
but
also
the
same
kind
of
thing
with
machine
learning.
You
know
the
first
part
of
the
of
builds
my
model
and
then
maybe
this
gate
step
in
the
middle
of
an
approval
step,
and
then
it
goes
into
another
cluster
and
stores
that
more
than
that
in
that
class,
I
think
that
would
be.
I
mean,
that's
just
a
very
popular
feature:
yeah
yeah
and
a
feature
I
don't
know.
B
B
B
Have
we
demoed
this
okay,
you
demoed
this
and
the
the
thing
I
like
about
this
is
when,
whenever
I
speak
to
somebody
about
it,
they
tell
me
oh,
I
could
do
this
or
I
could
solve
that
problem
like
this
and
I
demoed
it
to
my
vp
earlier
this
week
we
did
a
little
demo
session
and
he
came
up
with
a
great
idea.
I
hadn't
even
thought
of.
A
B
And
so
that
was,
that
was
a
really
great
aha
moment
I
was
like.
Oh,
we
could
do
that.
You
know
we
don't
we
don't
need
to
do
this.
This
could
be
super
simple,
but
the
downside
possibly
is
that
occasionally
I'm
seeing
features
that
if
we
had
had
a
plug-in
framework
at
the
time
we
maybe
wouldn't
we
wouldn't
have
built
those
features.
B
Yeah
yeah
yeah
and
I
think
they'll
be
neat
for
users
because
they
will
be
able
to
write
their
own
templates
around
plug-ins,
build
in
features
and
capabilities,
but
they
don't
need
to
wait
for
a
software
release
for
that
they
can
just
do
it
themselves.
You
know
you
know
today
if
they
want
to,
if
it
doesn't.
A
B
A
B
A
Exactly
yeah,
exactly
it
right
and
so
for
for
those
for
those
who
don't
who
don't
know
is
argo
con
is
is
coming
so
let
me
let
me
give
you
that
link
for
actually
because
registrations
are
still
open,
is
happening
december,
8th
right
I'll,
be
there
right.
I
actually
have
a
presentation
there,
so
shameless
plug
alex
you'll.
Be
there.
I
don't
know
if
you
have
a
presentation,
but
if
you
do
check
that
out.
A
We
do
have
a
question
in
the
chat,
though
here
about
workflows,
so
it
says
stefan
says
I
notice
that
argo
workflows
doesn't
support.
Processing,
multiple
resources
in
one
file,
ie
cubeapply.f,
manifest
file.
Is
that
something
you've
seen
a
workaround
for
to
be
more
specific
within
the
manifest
field
in
a
workflow
template.
B
Interesting
yeah,
so
I
think
the
probably
the
short
answer
is
we
don't
tend
to.
We
don't
really
cater
for
that.
I
think
he's
probably
talking
about
the
cli.
The
cli
tends
to
focus
on
a
single
workflow
at
a
time
and
operate
on
a
single
one,
so
it's
kind
of
hard
to
like
submit
two
workflows
from
it.
But
often
you
know
you
can
use
cubectl
to
do
this
so
cubectl
create
and
if
you
give
it
a
final
it'll
create
those
workflows
for
you.
Yeah.
A
Yeah,
so
I
I
guess
yeah
so
multi,
I
guess
multi,
I
guess
you
can
try
to
serve
a
side,
apply
that
I'm
not
sure
or
do
it
like
an
item
list.
I
don't
know
if
I
don't
know
if
you've,
stefan,
who
asked
the
question,
I
don't
know
if
you
tried
an
item
list
or
if
you
just
tried
the
standard
yaml
the
triple
dash
right
sort
of
thing,
so
I
would
try
either
a
server
side
or
a
or
an
item
list.
I
think
that
would
be.
A
B
A
A
B
A
A
I
guess
slack
for
everyone
right
for
everyone,
who's
who
is
in
the
cncf
and
has
a
project
there.
I
dropped
the
the
link
in
the
chat.
There
is
argo
channels
there
for
those
channels,
I'm
looking
looking
at
it
now
for
workflows
for
argo
cd,
there's
an
argo
con
channel
by
the
way
there's
there.
So,
if
you're
interested
about
our
argo
con,
there's
there's
one
in
there
as
well,
so
I'm
I'm
active
on
there.
I
think
a
lot
of
the
stuff.
A
I
bug
a
lot
of
the
alex's
from
from
intuit
there,
so
as
well
yeah
many
alex
it's
it's
one.
It's
one
of
one
of
you,
many
here
so
so
here
so
in
the
closing
minutes
here
looks
like
we
have
about
five
minutes
left
here
until
the
top
of
the
hour.
I
don't
know
if
you
guys
have
any
more
questions
out
there
to
to
round
this
out.
A
I
do
have
a
you
know,
other
than
argo
con,
that
we
just
we
just
mentioned
again.
Remember
that's
december
8th,
I
am
running
a
survey,
so
the
the
survey,
if
I
can
get
my
bitly
link,
I'm
running
a
survey
about
how
your
see
here
linked
in
the
chat.
Yes,
so
the
service
is
linked
in
the
chat,
so
you
see
there,
we've
been
doing
the
show
for
a
little
over
a
year
almost
two
years
now.
A
This
is
the
second
in
december,
we're
going
to
take
our
second
winter
break
that
we
have.
So
it's
almost
so
it's
about
two
years.
We've
done
a
lot
of
things,
so
we
want
to
check
if
you
want
to
check
it
out
what
you
like,
what
you
don't
like
about
the
show,
if
you
want
it
to
be
different
same
b,
I'm
the
type
of
person
I
don't
know
about
you
alex,
I
guess
working
in
software
is
like
give
me
all
the
feedback
you
have.
A
Even
the
the
nasty
feedback,
like
don't
don't
be
afraid
about
being
too
mean,
like
I'll
filter,
that
out
in
my
head,
because
I
I
want
to
hear
like
actually
what
you
think,
because
a
lot
of
times
you
know
frustration
can
be
good
right.
So
you
know
it's
you.
I
look
at
it
as
like.
Okay,
this
is
feedback.
This
is
a
point
of
frustration.
So
again
go
ahead.
Fill
that
fill
that
survey
out.
I
want
to
see
how
how
we're
doing
and
what,
what
kind
of
shows
you
guys.
A
You
guys
want
here,
see
here
doing
a
check
here
in
the
in
the
chat.
There
is
there's
no
more
questions
coming
down
here,
so
so
yeah
so
alex
where
I
don't
know.
If,
if
you
have
anything
to
plug,
I
don't
know
if
you
have
like.
If
you
want
people
to
follow
you
on
twitter,
I
don't
know
if
you
have
a
twitter
account
or
if
you
just
want
people
to
just
join
the
community.
Let
us
know
yeah,
you
know
where
we
can
find
you.
B
It's
I
think,
some
of
the
stuff
you
said
it's
great
to
kind
of
get
feedback
from
people.
Don't
you
know
if
you
have
you
comments
or
feedbacks
or
bugs
it's
kind
of
great
to
hear
about
that
sooner
rather
than
later,
you
know,
I
will
be
speaking
at
argo.
Con
I'll,
be
doing
like
a
maintainers
update
rather
than
the
presentation
so
I'll,
be
able
to
give
you
an
update
on
that
as
well.
A
Yeah
yeah
well,
actually,
that's
pretty
cool.
The
the
maintainers
update
is
always
really
cool
so
I'll.
I
actually
I'll
look
forward
to
that.
I'll
I'll
probably
be
attending
that.
So
so
here
yes,
so
follow
me
on
twitter
right.
So
that's
my
twitter
handle
is
somewhere
on
the
screen.
It
it's
kind
of
hard
to
see
because
it's
like
mirrored
on
my
site.
So
my
I
guess
it
would
be
that
side
all
right
so
yeah,
I
guess
exactly
follow
me
on
twitter,
make
sure
to
like
and
subscribe
right.
A
So
just
kind
of,
like
all
influencers
are
saying,
click
the
subscribe
button
make
sure
you
click
that
it'll
help
us
out
a
lot
so
yeah.
So
I
think
with
that
next
week
is
there's
no
there's
a
show
every
other
week.
So
I
guess
the
fact
that
we're
on
holiday
here
in
the
us
worked
out
for
me
because
we
don't
have
to
show
that
anyways,
but
so
just
everyone
who's
in
the
us
have
a
good
holiday
good
thanksgiving
here.