►
Description
Cloud Tech Thursday explores the full modern open source cloud stack, from hardware to serverless. Learn about new ideas, projects, and releases around Kubernetes, OpenStack, hybrid cloud enablement, and many other topics.
This week's guest, Dr. Holly Cummins: https://hollycummins.com/
A
A
A
A
B
C
B
A
Yes,
cloud
is
not
as
simple
as
people
think
sometimes
and
that's
surprising
to
them
so
you're
talking
about
how
not
direct
the
planet
today,
specifically
around
kubernetes.
How
did
you
like?
Do
you
want
to
talk
about
like
the
the
premise
of
the
talk
and
then
dive
into
it?
I'm
gonna,
let
you
kind
of
run
the
show
now.
B
B
You
know
cataclysmic
existential
destruction
which
hopefully,
people
also
think
is
important
and
I
sort
of
yeah.
I
started
thinking
about
this
because
when
I
was
learning
kubernetes,
I
kept
finding
myself
doing
things
and
then
realizing
oh
wait
a
minute
that
really
wasn't
very
efficient
and
wait
a
minute.
How
much
is
this
costing
and
wait
a
minute?
Is
it
just
me
who's
doing
things
in
this
slightly
inefficient
way
or
is
it
all
of
us
and
then
I
sort
of
looked
around
and
I
realized
it.
C
B
B
And
you
know
the
earth
is
getting
warmer
and
it's
getting
a
lot
warmer
and
I
think
it's
sometimes
sort
of
hard
to
get
your
head
around
the
the
numbers,
because
when
they
talk
about
the
sort
of
the
warming
they
say,
oh
well,
in
the
next
10
years,
it's
going
to
be
one
and
a
half
degrees
warmer
than
it
was
in
pre-industrial
times.
And
you
think
about
one
and
a
half
degrees.
Like
you
know,
if
you
went
outside
and
it
was
one
and
a
half
degrees
warmer
we'd
be
like
oh,
this
is
nice.
B
I'll,
have
an
ice
cream
today,
like
you,
even
if
you
even
noticed
it
tall
but
at
a
sort
of
a
planetary
scale
that
one
and
a
half
degrees.
You
know
it's
not
just.
Oh
it's
a
little
bit
warmer,
it's
no!
It's
really
uncomfortably
warmer
and
we
see
all
sorts
of
consequences
that
are
pretty
scary.
Like
you
know,
so
we
see
drought.
Obviously,
we
see
floods
because
the
sea
level
rises
and
and
for
some
things
it's
not
just
a
case
of
the
sea
level
rises.
B
B
How
do
we
still
have
a
country
when
the
physical
landmass
that
we
were
all
sat
on
doesn't
exist
anymore
and
they're,
sort
of
like
migrating
in
big
batches
to
parts
of
the
state
so
that
they
can
kind
of
keep
that
national
identity?
You
know
it's
sort
of
really
kind
of
scary
and
and
huge
things
you
know
so
then
there's
you
know
that
the
submersion
and
then
hurricanes
we
see
as
well.
B
You
know
they're
sort
of
becoming
an
increasing
problem
in
a
lot
of
parts
in
the
world
and
they're
quite
directly
related
to
the
sort
of
the
the
rising
ocean
temperature
then
creates
the
conditions
for
hurricanes
and
fires
are
becoming
a
a
big
issue.
Yes,
and
and-
and
so
all
of
that
you
know,
I
think
some
of
them,
it
still
kind
of
seems
quite
abstract
and
it
still
kind
of
seems
like
something
that's
going
to
happen
far
away
to
other
people
and
far
in
the
future.
B
So
we
were
sort
of
doing
various
things
with
them
and
at
one
point
and
we
sort
of
looked-
and
we
thought.
Oh
silly,
us,
you
know,
we've
been
migrating
this
logic
from
one
place
to
another,
and
we've
made
a
mistake,
because
we
were
looking
at
this
flood
graph
for
tokyo
and
it
just
sort
of
went
up
to
the
top
of
the
graph
and
it
just
like
stayed
and
we're
like.
B
Oh
you
know
silly
developers,
we've
got
this
wrong
and
then
the
the
sort
of
the
the
cto
came
by
who
really
knew
what
was
what
was
the
data
and
he
looked
and
he
said
actually.
No,
that's
that's
how
the
graph
looks
the
situation
really.
Is
that
bleak
in
2030
in
tokyo,
which
sort
of
I
think
kind
of
brings
at
home
that
it's
not?
C
A
B
Yeah
they're
doing
them
they're
doing
some
super
interesting
things
in
terms
of
their
flood
defenses.
Actually
they
have
these
sort
of
great
big
underground
cathedrals
that
they,
I
mean
not
literally
cathedrals
but
they're
sort
of
shaped
like
cathedrals
to
absorb
the
flood
water
and
to
be
the
flood
barrier
so
that
they
have
that
kind
of
physical
resiliency
to
compensate.
B
A
C
B
Yeah
yeah,
if
you're,
if
your
underground
cathedral
is
already
filled
with
water,
it
doesn't
help
as
much
as
you
hope.
So
then
you
know
the
sort
of
question
is
well.
That's
you
know
a
bit
scary,
a
bit
surprising.
You
know
glad
I
don't
live
in
tokyo,
but
what
does
it
have
to
do
with
me?
You
know
I'm
just
a
software
developer,
but
the
thing
is.
Our
industry
is
really
quite
as
significant
contributor
to
climate
change,
and
so
then
that
means
like
for
us.
B
Yeah
that
that
too
yeah
it's
sort
of
you
know
and
we're
sometimes
saying
we're
getting
less
bad
less
quickly
than
we
hope
than
we
thought
we
might.
But
you
know
that's
still
we're
still
like
using
more
and
more
energy,
which
is
yeah
like
there's
a
long
way
to
go
from.
You
know,
increase
increase,
increase
to
decrease.
B
So
there's
a
whole
bunch
of
people
on
the
glacier
sort
of
going
and
then
we're
sort
of
looking
at
our
servers
going.
I
don't
see
a
problem
but
but
like
if
you
sort
of
you
know,
think
like
I
think
we
sort
of
always
think
of
like
you
know
flying
you
know,
that's
the
kind
of
the
poster
child
for
being
responsible
in
terms
of
the
climate
right.
But
then,
if
you
look
at
the
actual
numbers,
so
flying
contributes
about
two
and
a
half
percent
of
the
the
worldwide
sort
of
carbon
footprint.
B
A
C
B
Yeah
yeah
and
then
the
sort
of
the
connection
to
kubernetes
is
kubernetes
is
the
operating
system
of
the
cloud.
So
a
lot
of
those
data
centers
now
have
a
lot
of
coopers
kubernetes
in
there.
So
then
we,
you
know
we
need
to
start
thinking
about
it
and,
like
I
think
one
way
that
we
sometimes
think
data
centers
are
different
from
aviation.
Is
data
centers
have
a
lot
more
potential
to
run
on
green
energy
and
in
some
parts
of
the
world
like
iceland,
you
know,
there's
a
huge
industry
of
renewable
energy
data
centers.
B
B
So
but
you
know
going
back
to
the
sort
of
the
where
does
kubernetes
fit
in.
I
think
you
know
where
we
sort
of
start
is
like
I
have
a
container.
I
want
to
run
my
container
because
I've
written
the
best
application
right,
but
then
we
started
thinking.
Oh,
but
you
know,
instead
of
having
one
container,
I
could
have
yeah
yeah.
I
didn't
draw
20
because
I
got
lazy,
but
you
know.
B
B
I
think
when
we
first
started
talking
about
containers,
we
kind
of
imagined
the
container
is
the
unit
of
deployment
and
look
I
put
my
container
in
you're
good,
but
now
a
container,
that's
not
an
application,
that's
just
like
a
small
part
of
it.
So
now,
all
of
a
sudden,
the
cluster
is
the
unit
of
deployment.
B
B
A
B
Of
but
there's
sort
of
two
things
that
I
think
affect
it
and
that
we
sort
of
need
to
think
about
when
we
think
like.
Is
this
an
okay
model,
or
is
this
not
an
okay
model?
So
we
need
to
think
about
the
utilization
and
we
need
to
think
about
the
elasticity,
and
so,
if
you
sort
of
imagine
that
you've
got
your
your
cluster
and
you've
got
your
application,
of
course,
as
soon
as
your
application's
in
the
cluster,
you
don't
just
have
the
application.
B
You've
got
like
a
control
plane
there
as
well,
and
the
you
mentioned,
auto
scaling,
naming
and
like
the
the
elasticity
within
a
cluster
is
really
pretty
good.
So
you
know
I
can
go
up,
I
can
go
down
and
that's
pretty
easy.
The
platform
will
take
care
of
it
for
me,
but
the
problem
is,
is
my:
if
my
application
is
going
up
and
down,
I
still
have
all
that
cluster
provisioned
that
isn't
going
up
and
down.
B
So
you,
like
you,
can
do
cluster
auto
scaling,
but
it
tends
to
there's
sort
of
a
few
problems
with
it.
One
is
it's
a
lot
harder
to
do.
You
have
to
sort
of
go
through
some
hoops
compared
to
the
application,
auto
scaling
and
it
it
they
tend
to
be
optimized
towards
not
starving
your
application
of
resources
and
making
everybody
hate
you,
which
is
a
reasonable
default,
so
they're
much
more
willing
to
scale
up
than
to
scale
down.
B
So
if
you're
sort
of
trying
to
be
really
efficient-
and
you
turn
on
auto
scaling,
you
may
find
it
it.
You
know
it.
It's
always
too
scared
to
shrink
your
cluster
and
the
other
problem
is
even
if
it
does
shrink
your
cluster,
then
all
of
a
sudden
that
control
plane,
that
was
like
a
small
proportion
of
your
overhead,
is
a
huge
proportion
of
your
overhead.
B
C
B
Unless
you're
actually
like
provisioning,
it
and
you're
sort
of
saying
okay,
I
want
a
machine
and
it's
got
four
cpus
and
it's
got
16
gig
of
ram
you're
sort
of
thinking.
It's
just
whatever
it's
just
you
know
it's
all
virtualized,
it's
all
you
know
somewhere,
it's
not
an
actual
physical
machine
and
actually
probably
it
is
a
virtual
machine.
But
you
know
there's
still
like
there's
a
physical
machine
there
and
I'm
using
electricity
yeah
and
they
tend
to
like
the
the
sort
of
the
kubernetes
architecture.
B
Is
that
the
the
nodes
are
really
tight
closely
tied
to
the
machines.
So
at
the
application
level,
it's
all
virtualized
and
fluffy
and
it
just
sort
of
wanders
around
and
is
elastic,
but
the
cluster
itself
is
kind
of.
You
know
it
almost
seems
like
a
gravity.
You
know
that
it's
kind
of
there
sort
of
like
dragged
down
to
these
to
these
machines,
so
yeah
yeah.
A
C
B
All
we
need
to
do
is
go
to
serverless
and
that's
okay
and
you
know
if
we,
but
if
we
go
to
serverless
and
stay
in
the
kubernetes
ecosystem,
then
you
know
we're
looking
at
k
native,
which
is
really
good,
but
it's
still
sort
of
it's
still
in
a
cluster.
So,
like
I
started
to
see
this
pattern,
so
k
native
unit
will
allow
you
to
scale
your
application
down
to
zero
but
scaling
the
application.
Isn't
the
problem,
it's
the
scaling,
the
cluster.
B
C
C
B
Yeah
and
then
I
think
it
sort
of
starts
to
be
like
who
are
you
sharing
it
with
so
like
when
I
was
first
learning
k
native,
you
know
I
started
to
do
it
and
I
started
to
provision
stuff
and
it's
like.
Okay,
great
just
give
me
your
cluster
and
I
was
like
well,
I
don't
have
a
cluster,
I
don't
want
a
cluster.
A
C
A
B
Yeah
yeah
totally
and
yeah
like
multi-tenancy,
is
really
really
hard
and
that's
sort
of
like
you
know.
If
you
think
about
like
why
it's
happening,
and
you
know
why
are
we
wasting
these
things?
You
know
there
you
sort
of.
I
think
you
kind
of
want
to
imagine
that,
like
somewhere
in
your
organization,
there's
dr
malice
and
they're
just
sort
of
going
raw,
I
can
you
know,
use
up
all
my
organization's
money
and
I
can
destroy
the
planet
at
the
same
time.
But,
like
you
know
there
isn't.
B
B
B
Yeah,
like
it's,
it's
so
porous
and
like
so
then
you
sort
of
end
up
with
this
thing
that
organizations
won't
trust
untrusted
workloads
in
another
namespace
in
that
in
that
same
thing
and
trust
ends
up
being
sort
of
a
fairly
limited
thing.
And
then
you
look
at
your
network
topology
and
you
realize,
or
you
know,
your
sort
of
cluster
topology
and
you
realize
it
exactly
measures.
You
know
mirrors
your
organizational
topology
and
you
know
that
team
over
the
corridor.
B
B
A
A
A
I
was
just
gonna
say
right,
like
that:
brings
up
the
sre
model,
where
it's
very
much
like
you
have
your
way
of
doing
things
for
your
team
and
then
your
your
other
team
has
another
way
of
doing
things,
and
but
yes,
they're
all
going
to
have
their
own
clusters
and
if
they
all
have
their
own
accounts,
that
means
they
could
have
up
to
21
clusters
per
account.
That's
pretty
wild
and
we're
talking
about
multiple
application
teams
within
one
organization.
You
know
that's
a
lot
of
infrastructure
underneath
those
clusters
sitting
there.
C
B
Have
you
know
a
cloud
pack
for
integration
and
a
cloud
pack
for
applications
and
when
you
know
you
sort
of
iterate
on
these
things,
so
what
the
the
first
go-round
some
of
the
cloud
packs
could
co-exist,
but
some
of
them
couldn't-
and
you
kind
of
think,
but
you
know.
Surely
I
wanted
to
install
these
things
together,
but
like
the
reason
why
they
couldn't
coexist,
it
was,
you
know,
really
subtle
and
you
sort
of
once
I
understood
I
was
like
okay.
B
Actually,
I
kind
of
get
why
this
happened
because,
like
if
you
make
a
resource,
it's
usually
or
it
can
be
scoped
to
an
individual
name
space,
but
there's
an
opportunity
for
error,
because
someone
can
accidentally
forget
to
do
the
right
scoping
and
then
it's
just
sort
of
leaked
everywhere.
But
if
you
do
a
resource
definition
like
a
crd
that
has
to
have
a
cluster
level
scope.
B
So
if
two
people
have
the
same
bright
idea
for
a
crd
name,
you're
going
to
get
a
collision
and
and
then
you
kind
of
think
about
like
an
organization
like
ibm,
you
know
with
lots
of
different
teams.
And
probably
you
say:
oh
you
just
make
a
naming
convention
so,
but
we're
probably
all
going
to
do
like
com.ibm,
michael
resource
right
and
then
all
of
a
sudden
you've
got
too
many
of
those.
So
then
you
have
to
have
like
you
can
do
it
and
you
know
we
did
make
it
work.
B
B
B
C
B
I
think
there's
probably
like
a
compromise
between
the
sort
of
what
we
do
now,
which
is
I
don't
trust
you.
I
can't
figure
out
my
billing
and
you're
across
the
hall,
so
I'm
not
going
to
share
my
cluster
with
you
and
I've
just
put
loads
of
malicious
workloads
into
one
great
big
cluster,
and
now
I
can't
manage
it
and
we've
got
you
know
weird
subtle,
bugs
everywhere
because
of
scope
collisions,
so
you
can
maybe
say
well
like
prod.
C
A
A
B
C
A
A
A
B
Sometimes
it's
not
the
prod
cluster,
so
we
can
run
build.
We
keep
the
broadcaster
over
there,
but
then,
like
then,
there's
this
sort
of
second
thing
so
say
like
say
you
know
we
do
all
these
hard
things
and
you
know
we
get
our
quotas
and
everything
and
we
have
like
the
multi-tenancy
dream,
and
you
know
we
have
this
cluster.
It's
really
optimum,
you
know,
lots
of
applications
are
running
and
you
know
it's
a
big
cluster
and
the
control
pane
is
minimal.
You
know,
is
this
like
great
for
the
climate?
B
B
B
No
one
knows
you
know,
yeah
and
like
to
sort
of
get
a
sense
of
how
how
big
this
the
scale
of
the
problem
is.
I
saw
a
piece
of
research
and
they
looked
at
16
000
servers
and
a
quarter
of
them
were
doing
no
work
and
I've
seen
another
statistic
that
says
30.
Another
study,
like
that's,
that's
a
lot
and
you
kind
of
think.
Like
imagine
you
know
you
could
take
that
one
to
two
percent.
If
you
could
just
find
your
zombies
and
just
go
right,
flip
flip.
B
Yeah
and
again
you
know
it's
not
malicious
right,
like
in
a
study,
they
said.
Perhaps
someone
forgot
to
turn
them
off
and
it's
like
yeah
and
I
think,
we've
all
totally
been
there.
So
you
know
usually
when
I
show
this
slide
to
people,
they
look
a
bit
sort
of
gray
and
they
say
I'll
be
right
back
and
then
they
sort
of
go
away.
A
B
Yeah
I
saw
I
can't
remember
what
organization
it
was,
but
they
had
it
because
I
yeah,
I
think,
like
there's
no
fun
in
decommissioning.
Unless
you
sort
of
get
your
thing
and
what
they
they
would
do,
I
think
they,
I
think
they
were
moving
to
the
cloud.
So
I
think
it
was
about
sort
of
decommissioning,
their
their
physical
servers
and
their
physical
data.
Centers
and
like
they'd,
have
a
party
so
like
when
they
would
sort
of
get
rid
of
the
last
rack
they'd.
B
B
A
B
So
yeah
yeah
and
like
how
do
we?
How
do
we
manage
that?
So,
like
you
know-
and
I
think
again,
like
all
of
us-
have
done
this
right.
So
I
was
learning
kubernetes.
You
know
my
first
client
project
where
I
was
going
to
use
kubernetes.
So
we
spun
up
the
cluster.
It
was
you
know,
for
a
client
project,
so
it
needed
to
be
a
fairly
well
powered
cluster.
But
then
I
had
too
much
work
in
progress
and
I
got
called
away
to
something
else
and
two
months
later
I
was
like
oh
wait
a
minute.
B
C
A
That
go
yeah,
that's
a
whole
conversation
around
like
hard
limits,
and
you
know
soft
limits
and
account
quotas
matter
right.
You
just
open
the
can
and
let
everybody
say
yeah
this
account's
wide
open
and
take
as
many
things
as
you
want.
You
will
find
that
there's
lots
of
things
that
people
wanted
but
didn't
get
rid
of.
C
B
Yeah
yeah
governance
is
yeah,
I'm
not
monitoring
it's
I
mean,
I
think
the
good
thing
is
that
I
think
it's
an
area
for
innovation,
because
there's
so
many
unsolved
problems
and
such
problems
are
interesting
but
and
and
like
this
sort
of
you
know,
the
impact
of
them
is
big
as
well
because
like
even
if
you
don't
care
about
the
whole
existential
br
dread
bit,
and
you
know
you
don't
care
about
the
carbon,
it's
money
and
right.
You
know
both
both
are
probably
pretty
important.
B
A
B
B
B
Yeah
so
then
the
sort
of
the
question
is
okay.
I,
like
the
idea
of
that
3.8
billion.
How
do
I
do
it
and-
and
you
know
it's
totally
worth
doing-
oh
yeah
so
yeah,
they
sort
of
said
like
if
you
got.
If
you
sort
of
sorted
out
half
of
your
utilization
problem,
you'd
reduce
your
electricity
consumption
by
40
percent,
which
would
be
3.8
billion.
B
A
B
B
Is
we
sort
of
say,
let's,
let's
eyeball
our
estate,
so
I
got
invited
to
this
meeting
and
I
have
to
say
it
was
one
of
the
least
enjoyable
meetings
I've
ever
been
to.
It
was
with
a
uk
bank
and
he
sort
of
was
like
going
through
his
estate,
the
cio
to
sort
of
try
and
figure
like
what
are
all
these
workloads.
It
was
like
just
going
through
this
list.
It's
like.
B
Yeah
and
so
then
you
think,
okay,
you
know
we
are
technologists.
We
can
come
up
with
a
technological
solution
and
let's
use
tags,
and
that
seems
really
promising
right,
because
it's
sort
of
aligned
to
the
capabilities
of
the
platform
and
it's
you
know
it's
a
thing,
but
usually
with
tags.
I
think
it
still
doesn't
totally
work
because
two
things
happen.
The
first
thing
is
that
someone
forgets
to
put
the
right
tag
on,
or
we
sort
of
have
tags
that
only
you
know.
B
B
B
Yeah
and
I
think,
like
a
lot
of
organizations
that
are
aware
of
this
problem
and
they're
aware
that
they're
leaking
money,
so
they
say
well,
a
tag
is
shutting
the
bar
and
then
going
out
and
deleting
it
that's
sort
of
shutting
the
barn
door
after
the
horses
left.
Wouldn't
it
be
better
to
shut
the
barn
door
before
the
horses
left
and
you
think
the
answer
would
be
yes,
but
what
actually
ends
up
happening?
B
B
And
it's
so
frictionless
and
then,
if
you
put
all
this
friction
in,
I'm
still
not
sure
it
actually
helps.
You
remember
to
delete
things
it
just
stops.
You
doing
things.
I
think
you
know
any
solution.
It's
kind
of
got
to
be
based
on
optimizing
for
what
people
are
actually
like,
and
you
know
behavior.
A
B
I
read
an
article
the
other
day
about
what
spotify
are
doing
and
they
have
this
sort
of
cost
insights
platform,
and
the
idea
is
just
if
you
just
give
the
engineers
visibility
of
how
much
their
service
is
using.
They
will
naturally
try
and
optimize
it
because
engineers
are
natural
optimizers.
So
just.
A
A
B
Yeah
and
and
there's
a
cost
to
that
platform
as
well.
You
know
like
we
were
saying:
it's
not
easy
to
get
that
information,
but,
like
I
think
as
well,
you
know.
Sometimes
the
solution
can
be
really
really.
So
that's
like
super
hard
and
you
know
pushing
the
boundaries
of
technology.
Sometimes
the
solution
can
be
really
easy
and
dumb.
So
a
colleague
of
mine,
he
told
me
about
this
thing
that
they
did,
and
this
was
2013,
it's
a
virtual
machine.
B
So
what
they
did
is
you
could
provision
a
machine
and
it
would
just
auto
delete
after
two
weeks
and
they
they
managed
to
save
half
of
their
cpus
so
like
if
you
needed
it
extended,
you
could
extend
it,
but
the
idea
is
optimized
for
what
people
are
bad
at,
or
rather
you
know
optimize
away
the
thing
that
people
are
bad
at,
because
people
are
awful
at
remembering
to
delete
things,
but
they're
really
good
at
provisioning
things.
So.
C
B
B
Yeah
and
then
you
know
you
can
make
a
a
report
saying
you
know
how
you've
implemented.
Chaos,
testing
and
you
know,
reduced
the
utilization
and
you
know
discovered
all
of
these
vulnerabilities,
and
I
mean
I
think
as
well.
Like
I
said
I
mentioned
the
finnops,
I
think
we
probably
are
going
to
see
more
capabilities
coming
into
the
platform.
A
A
B
A
A
B
Yeah
and
so
then
you
know,
the
sort
of
the
question
is
like
all
of
that
is
kind
of
independent
of
kubernetes,
and
then
you
think
well
so
is
you
know
we
should
be
going
forward
with
technology
and
you
know
we
used
to
have
virtualization,
and
now
we
have
kubernetes.
So
are
we
better
off
and
you
know
like
another
way
of
saying
it
is
kubernetes
zombie
proof
which
is
sort
of
saying
you
know
now
is
the
cloud
zombie
proof
yeah
and
I
kind
of
think
it's
really
not
like
it.
It
makes
it.
B
And
you
get
it,
you
know
beautifully
configured
even
if
you're,
not
using
it
day
to
day.
You
think
well,
my
most
might
come
in
two
weeks
and
ask
me
to
do
a
demo
of
this
and
you
know
or
what,
if
I
need
it,
so
you
just
kind
of
leave
it
and
right
like
if
you,
if
you
make
something
like
you,
make
a
cluster
there's.
This
thing
called
the
ikea
cognitive
bias,
which
is
basically,
if
you
make
it
you
like
it
more
so
like
the
more
work
you
put
into
that
cluster
right.
B
And
I
think,
like
I
think
now,
we
are
starting
to
see
a
thing
actually
where
kubernetes
is
helping,
which
is
the
sort
of
part
of
the
thing
that
we
have
to
do.
Is
we
have
to
make
it
so
that
it's
not
a
lot
of
work
to
make
the
cluster
or
you
know,
to
make
the
workload
or
whatever,
because
then
we're
more
willing
to
shut
it
down
and
so
like.
If
we
have
githubs-
and
you
know
by
this-
I
don't
mean
any
sort
of
fancy
framework
or
anything.
I
really
just
mean
you
know
like.
B
If
if
we
are
good
and
we
keep
all
our
infrastructure
as
code,
then
it's
disposable
so
like
we
have
the
confidence
that
we
can
spin
it
down,
because
we
know
we
can
spin
it
back
up
and
then
you
know
we
can
do
this
all
day.
Long
and
you
know
just
apply,
you
know
minus
f
and
we
get
it
back
and
kind
of
as
a
bonus
as
well.
We're
getting
disaster
recovery
because.
A
B
B
If
you
have
good
enough
automation-
and
if
you
have
you
know
your
workforce
in
a
single
time
zone
so
that
you
don't
need
to
you
know
sort
of
support
a
distributed
team,
you
can
do
it
and
I
heard
one
example
and
they
managed
to
shutting
down
their
aws
instances
out
of
hours
and
save
37
of
their
crowd
bill.
So,
like
that's
a
lot.
A
A
You
know
virtual
machine
cluster,
for
you
know,
testing
and
development,
but,
and
that
only
occurred
between
the
hours
of
you
know,
seven
to
seven.
Basically,
so
during
the
nine
hours
shut
it
off
and
save
tons
of
money,
those
dev
environments
are
not
cheap
and
having
them
constantly
running
or
reducing
their
footprint
down
to
where
they
can
spend
back
up
easily
come
you
know,
monday
morning,
or
you
know
the
next
morning,
kind
of
thing
is
invaluable
to
cost
savings,
and
you
know
energy
savings.
B
B
Is
this
idea
of
micro,
optimization
theater,
which
is
something
that
jeff
atwood
used
to
to
talk
about
and
and
I
sort
of
started
thinking
about
it
like
for
me,
because
I
I
sort
of
you
know
I
when,
when
we
traveled,
I
I
used
to
fly
and
you
know
I'd
be
on
the
plane.
I'd
be
like
doing
my
tech,
greeting
and
but
I'd
always
sort
of
I
wanted
to
be.
You
know
sustainable,
so
I'd
say:
well,
I'm
going
to
take
public
transit
to
and
from
the
airport.
B
You
know
I
don't
want
to
take
one
of
those
unsustainable
taxis.
I'm
going
to
you
know,
take
a
train
and
that's
you
know
really
sustainable,
and
sometimes
it
was
really
hard
like
you
know
it
would
cost
more.
It
would
take
longer,
but
I'd
be
like
yay,
I'm
a
hero
because
I'm
taking
the
train,
you
know
so
then
I
had
this
sort
of
model
where,
like
I
felt
like
a
hero,
because
I
would
take
a
train
to
the
airport,
where
I
would
get
on
a
plane
I
was
like
well.
B
I
think
I
was
solving
the
wrong
problem
really
and
I
think
like
what
we
do
as
individuals
is
really
important,
but
we've
sort
of
seen
in
lockdown
as
well,
that
there
is
a
limit
to
it.
Like
the
I
think,
in
the
lockdown,
the
car,
you
know
we
all
stopped
driving.
We
all
stopped
flying
and
carbon
went
down
something
like
six
percent,
so
you
know
we
do
kind
of
need
these
bigger
systematic
changes
as
well.
So
you
know
it's
not
like.
A
Yeah
going
to
the
train
station
yeah,
yeah
yeah-
and
you
know
I
I
live
just
outside
the
motor
city,
so
like
mass
transit
is
not
really
a
thing
here.
Everybody
has
a
car
or
two
because
well
most
of
the
people
here
work
for
one
of
the
big
three
auto
manufacturers
so
having
public
transportation
is
kind
of
a
luxury,
as
it
were.
C
A
A
C
A
B
Yeah,
like
you,
need
the
infrastructure
and
then
once
you
have
the
infrastructure,
everything
else
kind
of
follows
and
it's
sort
of
the
same
like
when
you're
looking
at
at
your
cloud-
and
you
know,
is
this
running
on
renewable
energy
or
not.
You
know
you
kind
of
need
that
renewable
energy
to
be
there,
so
that
you
can
then
make
the
consumer
choice
to
you
know
to
choose
something:
that's
that's
running
on
it,
but
if
it's
not
there,
there
kind
of
is
a
limit.
A
B
Yeah,
so
a
good
question.
I
think
it
would
probably
depend-
and
you
know
again
probably
quite
rightly-
depend
because
it's
that
sort
of
optimization,
like
you
can
imagine-
scenarios
where
that
money
that
you
are
spending
on
renewable
energy
would
actually
allow
your
business
to
do
something
really
way
more
significant.
B
Want
to
be
data
driven
in
those
decisions,
but
we
don't
have
you
know
we
don't
even
have
the
visibility
of
well
what
you
know.
What
what
is
this
running
on,
and
you
know,
is
this
actually
clean
energy
or
is
it
all
just
offset,
which
is
you
know
again
better
than
nothing,
but
quite
quite
different?
Yeah.
C
B
But
I
always
think
about
it
like
the
highway
problem,
so
our
data
centers
are
getting
bigger
and
bigger
and
the
pipe
you
know
the
network
pipes
are
getting
bigger
and
bigger
and
and
and
data
centers
are
also
getting
more
efficient,
actually
they're
getting
significantly
more
efficient
than
they
used
to
be
so
you
sort
of
think.
Oh
that's
all
great.
B
You
know
everything
is
getting
more
efficient,
we're
going
to
be
using
less
energy,
but
you
know
if
you
think
about
it
as
a
road
analogy
when
you
widen
the
road,
you
kind
of
imagine
that
you're
gonna
have
like
this
huge
six-lane
highway
and
there's
gonna
be
like
one
lonely
car
you
know
going
along
with.
You
know,
trees
in
the
background
and
what
actually
happens
is
every
single
car
goes
yay,
there's
capacity,
and
so
we
just
fill
it.
B
B
But
I
think
like
overall,
you
know
you
were
sort
of.
We
were
talking
about
some
of
the
challenges
of
the
monitoring
and
the
real
time
and
stuff,
and
I
think
I
think
there
are
so
many.
There
are
so
many
sort
of
problems
here
where
we
kind
of
know
what
we
need
to
do.
We
just
don't
know
how
to
do
it
like
we
know
we
need
more
information
about
how
to
optimize
our
workloads,
and
we
know
we
nee.
B
B
A
C
B
Yeah
yeah,
like
I
think
I
think
they
there
is
a
consumer
pressure
on
cloud
providers
and
I
think
we
can
increase
that
consumer
pressure
to
say.
I
would
like
to
run
my
workloads
in
a
green
way
and
I
would
like
information
about
my
workloads
and
that
is
going
to
influence
my
buying
decision.
So
you
know
if,
if
you're
running,
you
know
in
virginia-
and
you
don't
give
me
any
information
about
this-
then
I'm
going
to
go
to
a
different
data
center
or
a
different
provider.
B
C
So
as
part
of
this
we're
talking
about
the
infrastructure
and
the
cloud
hosting
providers
to
some
degree,
they're
not
aware
of
what
or
shouldn't
be
really
what
you're
running
on
top.
So
we
go
back
to
that
discussion
where,
during
after
7
00
pm,
the
development
machines
were
turned
off,
but
you
still
have
the
cost
of
running
those
machines,
because
in
a
public
cloud
situation,
there's
going
to
be
other
people
running
on
them.
B
A
B
Think
I
think
this
is
sort
of
one
where,
if
we
get
it
right,
we'll
be
in
a
really
good
place
with
public
cloud,
because
if
the
cloud
provider
will
have
to
have
you
know
sort
of
enough
machines
for
the
maximum
capacity,
but
hopefully
the
maximum
capacity
will
be
or
that
you
know
the
maximum
demand
will
be
different
for
each
user.
So,
like
you
know,
for
wimbledon,
for
example,
they
they
only
have
demand
in
june
and
july.
B
You
know
so
all
of
the
servers.
You
know
that
they're
using
can
be
used
for
someone
else
who
and
then
you
know,
maybe
somewhere
else,
it's
going
to
be
black
friday,
it's
going
to
be
christmas,
and
so
it
kind
of
averages
out
and
then
even
with
an
individual
day
as
well.
You
write
that
like,
if
we
all,
if
we
were
all
in
the
same
time
zone,
we
all
turned
off
our
machines
at
7pm.
B
It
would
save
a
little
bit
of
electricity,
but
it
wouldn't
save
on
the
hardware
and
probably
there's
sort
of
you
know
a
great
big
thrumming
set
of
you
know.
Openstack
or
you
know,
whatever
the
layer
is
underneath,
that's
keeping
it
running,
that's
still
using
electricity,
but
probably
we're
not
all
in
the
time
same
time
zone.
So
it
still
does
sort
of
balance
out
a
little
bit
around
the
clock.
A
C
B
B
B
I
mean
so
sort
of
like
I've
got.
I've
got
a
summary,
but
it's
sort
of,
I
think
I
think
a
lot
of
these
we've
kind
of
talked
about.
But,
like
again,
I
think
it's
just
you
know
it's
sort
of
visibility,
optimized
visibility,
optimized
so
like
if
you're,
you
know,
if
you're
in
the
open
source
community,
if
you're
creating
some
of
these
tools,
then
like
really,
you
want
to
be
doing
what
you
can
to
help
better
utilization.
B
C
A
B
A
B
It
to
a
different
domain
and
then
yeah
just
a
lot,
a
lot
of
automation
about
making
sure
it's
disposable,
spinning
it
down
when
you
don't
need
it
and
as
well,
really
considering
either
chaos
testing
or
you
know
these
kind
of,
like
you
know,
sort
of
sort
of
damocles.
You
know
provisioning
models
where
you
know
it's
going
to
die
after
two
weeks.
Unless,
unless
you
do
something
to
save
it
and.
B
A
A
Right
well,
thank
you
so
much
yeah.
We
really
appreciate
you
coming
on,
but
this
is
very
thought-provoking
and,
like
I'm
already
thinking
about
like
my
internal
like
home
cloud
footprint,
right
like
I
have
computers
running
everywhere
in
this
house
and
it's
kind
of
like,
could
I
shut
any
off
totally.
B
A
Yeah,
I
totally
could
shut
some
off.
You
know
from
you
know,
seven
to
seven
or
whatever,
like
I
was
saying,
but
yeah
there's
a
lot
of
potential
there
for
savings.
Just
looking
at
my
own
stuff,
I
can't
imagine
if
an
organization
looked
holistically
at
their
environment
and
said
what
could
we
do
to
just
get
big
whacks
of
savings
here?
When
I
say
wax,
I
mean
like
just
you.