►
From YouTube: Kubernetes SIG Scheduling Weekly Meeting for 20230126
Description
In this meeting, we brainstormed the idea of preferred topology affinity.
B
B
So
at
least
I
couldn't
figure
out
anything
else
and
the
use
case
is
it's
a
little
bit.
You
know
connected
to
these
Port
groups,
so
suppose
you
have
like
a
rack
which
has
very
fast
interconnections
between
gpus,
but
those
interconnects
don't
span
to
other
racks.
So
you
basically
want
to
have
a
bunch
of
ports
to
go
and
be
scheduled
into
some
rack.
You
don't
want
to
say
which
track
it
is,
but
some
rack
as
long
as
it
has
resources,
and
this
Interpol
Affinity
allows
for
basically
doing
that.
B
A
So,
first
of
all,
I
think,
let
me
clarify
the
requirements
that
I
think
if
I
answer
correctly
is
that
you
want
to
generally
say
I,
don't
want
to
use
the
the
particular
kind
of
resources
by
the
regular
workers.
That
may
not
need
that.
So
so
those
kind
of
expensive
resources
can
live
for
the
real
workflows
which
may
really
need
them.
Is
that
the
the
requirement.
B
You
know,
there's,
like
you
know
many
ways
of
configuring
that
you
can't
do
this
like
in
your
least
allocated
node,
or
you
know
so
forth,
so
I
would
take
want
to
have
some
sort
of
topologic
angle
to
it.
So
I
have
like
a
least
used
rack
prefer
the
best
Note
in
the
least
used
or
rack.
That's,
basically
the
goal
and
the
what
constitutes
as
the
resource.
Well,
that's
configurable
at
the
moment
and
I'm
I
wouldn't
propose
changing
that.
No
I
would
prefer
that
to
be
configurable.
B
A
B
A
B
Exactly
so,
if
you
have
this
kind
of
like
All
or
Nothing,
call
Scheduling
kind
of
a
thing
it's.
This
is
like
orthogonal
to
that
you
might
still.
You
know
if
you
just
you
know,
use
the
current
code,
scheduling
plugin,
for
instance,
it
just
you
know,
tells
you:
can
we
deploy
these
ports
to
the
cluster,
the
whole
cluster,
but
would
interpod
Affinity
help
there
I
mean
it's,
it's
a
basically,
it's
a
preferred
mechanism.
C
A
A
Check
my
is
technically
possible,
but
you
know
the
challenge
here
is
that
so,
basically,
we
are
trading
arbitrary
set
of
nails
as
an
entity,
and
we
just
treat
that
entity
as
a
minimal
unit
when
we
do
scheduling
decision.
That
is
the
purpose
right.
So
it's
similar
like
like
we
before
talking
about
like
we
more
want
to
see
whether
we
have
Cam
created
the
physical
note
like
the
metal
machines,
if
it's
running
a
VM
underneath
to
take
that
into
control
into
their
scheduling
decision.
B
A
Channel
here,
yeah,
the
charger
here
is
topology,
is
nothing
but
a
label
on
node.
So
that
means
it
can
have
as
many
carbonation
you
may
have
it's
like
2
equals
bar
like
bars.
Any
any
level
can
form
a
topology
instead
of
like
no
there's
a
physical
unit.
That
is
just
you
have
5000,
yet
just
five
thousand,
but
for
topology
kid
combination.
A
It's
arbitrary
I
can
be
a
lot
of
that.
You
may
have
spent
a
lot
of
resources
Computing
during
the
scheduling
cycle.
So
that's
the
challenge.
I
I
will
see,
but
technically
I
think
you
can
explore
using
plugin
first
and
I
know
in
the
production
environment
there's
a
lot
of
Labor.
So
that
means
a
lot
of
a
lot
of
topology.
A
A
Yeah
yeah,
basically
yeah.
Basically
the
scheduling
the
input
to
scheduling
is
that
you
have
to
tell
scheduler
what
kind
of
rules
you
want
to
treat
the
scheduling
logic
unit
right.
So
there
are
in
the
scheduling,
plugins
computation
cycle
it
can
just
re
calculate
you
calculate
this
kind
of
information
instead
of
just
trading.
You
know,
that's
the
minimal
scheduling,
unit,
yeah
I.
Think
technically
it's
it's
possible.
But
to
me
to
be
honest,
I
don't
see
a
popular,
a
large
kind
of
requirements
on
this
yeah
other.
A
B
A
A
B
So
suppose
you
just
have
like
not
a
group
of
boats,
but
you
have
a
single
port
and
you
want
to
do
this
pin
packing.
So
why
not?
You
know,
do
the
scoring
for
most
allocated
and
you
know,
run
the
same
logic.
It's
just
a
number
I
mean
scoring
is
just
a
number,
so
you
know
it
would
end
up
in
the
most
allocated
rack
where
it
fits.
C
About
you
know,
but
the
problem
is
that
we
take
the
decisions
for
each
bot.
So
if,
let's
say
it's
a
big
job
with
multiple
thoughts,
then
the
first
pod
might
choose
might
choose
a
particular
a
particular
rack,
then
gets
full
and
then
the
entire
job
doesn't
fit
I,
don't
think
the
the
cost
scaling
plugin
would
be
able
to
retry
in
a
different
drug.
A
B
C
B
I
kind
of
disagree,
in
the
sense
that
if
you
want,
if
you're,
somehow
having
like
multiple
different
kinds
of
let's
say,
Ai
workloads
and
for
some
some
reason
you
happen
to
have
some
of
them
such
that
there's
just
a
single
board
required
you
could,
you
know,
push
those
into
the
cluster
into
those
topologies
where
the
topology
is
not
entirely.
You
know
unused.
B
A
So
yeah
I
agree
yeah.
It's
to
me.
It
doesn't
seems
like
that.
You
related
with
Lisa.
You
said
it's
a
job
and
now
I
you
can't
totally
fit
this
English
Singapore.
It's
just
like
we
do
what
we
do.
Do
the
preference
to
know
you
just
totally.
We
switch
to
another
angle
to
do
preference
to
a
rack
to
arbitrary
topology.
You
can
be
fine.
C
B
C
To
yes,
yeah
one,
one
more
thing
so
way
was
talking
about
how
topologies
are
just
labels.
So
the
way
you
should
probably
start
is
by
having
this
plug
this
as
a
plugin
configuration
where
you
specifically
say
either
just
one
topology
key
or
a
list
of
topology
keys
that
that
the
plugin
will
be
paying
attention
to
during
the
setup
during
at
a
scheduler,
startup
type
or
like
before.
You
start
the
scheduler.
C
I,
don't
remember
the
name,
but
they
referred.
They
are
referred
to
as
zones
and
regions
which,
of
course,
in
a
cloud
environment
they
they
refers
to.
They
refer
to
zones
and
regions
in
cloud
in
the
particular
cloud
provider,
but
a
lot
of
users
in
that
run,
on-prem
on
their
own
servers.
They
already
choose
to
to
map
racks
into
zones
like
that's,
basically
what
what
some
some
people
do.
They
just
take
Zone
as
a
rock
okay.