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From YouTube: SIG Usability 20200901
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A
Okay,
hello.
Welcome
to
our
site
usability
meeting
today
on
the
agenda.
We
have
carl
who
will
be
going
over
quantitative
data
from
our
survey
readout.
I
will
be
going
over
an
update
on
our
jobs,
discussion
guide
and
we
have
one
or
two
new
members
who
will
be
introducing
themselves
as
well.
So
carl
do
you
do
you
want
to
kick
us
off
here.
B
Yep
there
we
go
all
right,
you
see
in
a
survey
slide,
yes,
okay,
cool
yeah,
so
I
kind
of
came
in
late
to
the
the
survey.
So
I
actually
don't
know
a
ton
about
the
survey
background,
but
I
think
it
was
mainly
to
get
some
high
level,
demographics
and
screens
and
participants
for
the
jobs
to
be
done.
Interview
research,
that's
going
on,
so
I
essentially
just
took
all
of
the
quantitative
questions
and
plotted
them
out
here.
So
we
can
get
a
view
of
who
answered
the
survey.
B
I
know
there
is
a
lot
of
in-depth
qualitative
questions,
but
I
just
did
the
quantitative
pieces
here
and
all
the
code
is
available
in
the
link
on
this
slide
deck.
If
you
want
to
see
on
github
so
first
for
location
of
respondents,
it
was
pretty
much
mostly
europe
and
north
america.
We
had
a
few
people
from
other
continents,
but
by
far
and
away
it
was
europe
and
north
of
america
for
the
organization
type
of
the
respondents.
B
Most
people
were
not
consultants
or
managed
service
providers,
but
we
definitely
still
had
a
few
in
there,
the
least
between
consultants,
so
not
exactly
sure
what
none
of
the
above
is
but
yeah.
That
was
interesting
to
see
that
most
people
were
not
part
of
the
other
two
categories:
job
function.
We
had
a
lot
of
spread
here,
a
lot
of
different
names
that
people
identified
most
closely
with
software
architect
and
devops
management
were
the
highest
and
back-end
developer
kind
of
drops
down
a
bit
more
here.
B
I
think
a
lot
of
these
titles
make
a
lot
of
sense
for,
for
who
we're
seeing
and
even
got
a
one
ux
researcher
or
a
designer
in
there
as
well.
It
was
kind
of
interesting
to
see
only
one
data
scientist.
B
I
guess
I
didn't
really
know
if
that
was
going
to
be
more
or
less
but
kind
of
cool,
to
see
some
representation
from
a
lot
of
different
titles
for
the
role
most
people
were
individual
contributors,
a
good
number
of
people
were
professional
services
or
consultants,
and
then
a
good
chunk
were
also
managers
or
directors
only
a
handful
of
researchers
or
scientists.
B
B
A
lot.
Fewer
people
were
actually
doing
hybrid
cloud
that
took
the
survey.
One
person
wrote
in
bare
metal,
cube
adm,
so
I'm
gonna
just
say
they
actually
should
probably
be
in
private
cloud
on
premise,
if
they're
running
on
bare
metal,
but
they
felt
like
that
was
different.
I
don't
really.
I
don't
know
if
I
would
consider
it
different,
but
that's
what
they
wrote
in
for
other
for
a
number
of
machines.
B
We
had
a
a
big
number
of
people
that
were
over
5
000
machines
by
far
and
away
the
biggest
category
and
then
kind
of
even
even
spread
throughout
everything
else.
Everything
from
you
know
2000
to
one
machine.
It
was
pretty
pretty
even
in
there,
so
it
was
interesting
that
so
many
people
are
in
this
5
000
plus
category.
So
a
lot
of
really
really
big
operations
going.
B
So
these
were
activities
that
the
respondents
were
involved
with,
so
the
green
means
they're
very
involved,
they're
green
teal,
the
red
means
they're
somewhat
involved,
and
then
orange
is
not
involved.
B
So
the
things
that
people
weren't
very
involved
with
was
was
working
with
ai
and
machine
learning
systems.
We
only
had
one
data
scientist,
so
I
guess
that
you
know
kind
of
makes
sense.
People
also.
That
was
the
one
that
people
were
the
least
involved
with
by
a
good
margin,
and
I
think,
related
to
that
managing
data
processes.
People
were
less
involved
with
a
lot
of
somewhat
involved,
but
also
a
good
amount
of
not
involved
at
all
and
then
cost
management.
B
People
were
strongly
involved
with
infrastructure
resources,
which
I
think
is
really
what
you
know.
Kubernetes
does
in
a
lot
of
ways,
so
that
makes
sense,
researching
evaluating
new
technologies,
monitoring,
troubleshooting
applications,
managing
deployment,
pipelines
managing
cloud
platform,
developing
software
architecting
software.
These
were
all
the
things
that
really
stood
out
as
being
the
most
involved
for
our
users.
B
I
did
try
and
do
some
more
advanced,
like
cluster
analysis
on
these,
but
I
didn't
really
get
a
lot
of
separation,
so
it
seems,
like
everybody
was
mostly
part
of
kind
of
one
one
big
group.
I
didn't
get
a
lot
of
separation
into
the
factors
there
when
I
tried
to
split
this
out
for
people's
container
use,
so
we
don't
have
every
bar
on
every
type
of
deployment.
B
So
this
would
be
that
people
using
containers
in
production
in
tests
in
their
development
or
in
proof
of
concept,
so
pretty
much
everybody's,
just
always
using
containers
across
everything,
maybe
a
little
bit
more
future
plans
for
production
and
tests
than
development
and
proof
of
concept.
But
that's
pretty
small,
it's
interesting
to
see
that
you
know
how
many
people
are
using
it
in
production
are
also
using
it
in
proof
of
concept.
B
B
Specifically,
once
again,
we
I
mean
it's
kind
of
the
same
thing,
except
maybe
that
people
have
moved
past
the
proof
of
concept
piece,
because
they've
used
that
in
the
past
more
that
stands
out
a
bit
but
again
just
a
lot
of
people
that
are
using
it
across
everything,
from
poc
to
production.
B
This
is
kubernetes
related
resources
that
people
have
used
when
interacting
with
kubernetes
the
biggest
one
is
documentation
by
a
pretty
good
margin,
a
lot
of
people
on
twitter,
a
lot
of
people
using
youtube
and
local
events.
A
good
amount
of
people
going
to
to
kubecon
to
think
about,
like
a
third
of
their
respondents
and
yeah.
C
B
B
B
This
is
the
last
slide
so
that
we
did
a
net
promoter
score
which,
if
you're
not
familiar
with
it,
is
a
question.
You've
probably
seen.
How
likely
are
you
to
recommend
blank
to
a
friend
or
colleague,
and
it's
kind
of
used
as
a
general
sentiment
about
how
people
feel
about
a
product
or
service,
and
you
break
it
into
three
categories.
B
So
you
have
a
detractor
as
anyone
that
is
zero
to
six
and
when
they
respond
on
that
that
eleven
point
scale
from
zero
to
ten
and
then
anyone
in
seven
and
eight
is
kind
of
neutral,
they're,
considered
passive
and
then
nine
to
ten
is
a
promoter.
B
So
the
way
that
we
calculate
this
score
is
essentially,
we
remove
all
the
passive
scores
and
we
just
look
at
the
ratio
of
the
detractors
to
the
promoters
and
the
score
goes
from
negative
100
to
positive
100
and
we
are
at
a
62.5
with
the
responses
from
our
surveys.
This
is
really
really
high.
Most
most
consumer
software
is
closer
to
like
30
or
40,
if
it's
doing
really
well.
B
So
I
thought
that
was
kind
of
interesting
that
this
is
like
would
be
an
exceptional
nps
score
by
a
lot
of
industry
standards,
especially
for
like
enterprise
software,
but
I
also
don't
know
if
people
have
used
the
net
promoter
score
as
much
on
open
source
projects
which
are
probably
markedly
different
and
that
it's
kind
of
a
co-created
software,
so
they
feel
some
ownership
over
it
as
well.
So
there
hasn't
really
been
enough
research
to
benchmark.
B
How
good
is
this
for
open
source
software,
but
I
mean
this
could
be
kind
of
the
first
peek
at
how
open
source
software
differs
on
net
promoter
norm
so
either
way.
I
thought
that
was
kind
of
a
little
interesting,
quant
piece
as
well
so
yeah
that
was
all
of
the
quant
questions
that
I
pulled
so
yeah.
Let
me
know
if
you
have
any
any
questions
or
thoughts
about
this.
A
This
is
super
awesome,
carl.
I
I
feel
like
yeah.
It's
super
awesome,
seeing
just
like
all
of
the
everything
laid
out.
These
are
the
people
that
we
are
planning
on
reaching
out
to.
As
far
as
our
jobs
study
like
the
the
interviews
so
super
pumped
to
just
see,
you
know
a
little
bit
about
their
background
and
I
feel
like
we
got.
A
You
know
some
like
pretty
like
interesting
responses.
You
know,
as
far
as
like
cont
use
of
containers,
all
across
the
board
and
kubernetes
as
well,
and
even
like
the
net
promoter
square
here
so
yeah.
Thanks
for
doing
this.
B
Yeah
absolutely
is
there.
Maybe
this
would
be
getting
a
little
ahead
of
ourselves
if
we
want
to
report
this
out
with
more
of
the
jobs
to
be
done
work,
but
is
there
any
kind
of
avenue
that
might
be
interesting
to
just
kind
of
do
a
play-by-play
like
write-up
of
of
what
we
we
got
in
this
score?
Is
there
any
like
blog
avenue
or
anything
like
that.
A
Yeah
I
mean
I
personally
don't
have
never
done
that
before,
but
I
know
tasha
would
definitely
have
some
like
thoughts
when
she
comes
back
from
pto,
but
I
know,
for
example,
there
there
is
the
kubernetes
blog
and
I've
seen
some
surveys
published
through
that
in
the
past.
I
don't
know
if
there's
also
like
an
opportunity
to
do
like
a
playback
to
like
a
larger
like
contributor
audience
just
for
the
people
that
are
interested.
A
B
A
Do
you
want
to
take
like
a
midpoint
break
and
do
introductions?
I
realize
that
we
probably
should
have
done
those
at
the
beginning
a
little
backwards.
I
don't
know
if
anybody
on
the
call
wants
to
introduce
themselves
you're
more
than
welcome
to.
If
you
want.
D
Oh,
I
guess
I'll
start
hi,
I'm
ellen
I'm
working
at
vmware
and
I
actually
only
started
about
two
months
ago
right
off
of
an
internship.
I
did
last
summer
with
tasha's
team,
so
she's
the
one
who
introduced
me
to
this
community
and
I'm
interested
in
kind
of
catching
up.
I
guess
on
what
we've
been
doing
here,
carl.
The
presentation
was
very
helpful.
I
feel
like
it
gave
me
a
good
sense
of
I
guess
where
we're
headed.
So
thank
you
and
yeah.
C
Hi
everyone,
so
my
name
is
sushmita.
I
work
as
a
pm
at
a
startup
in
the
bay
area,
so
it's
I've
had
some
experience.
I've
gone
to
I've
worked
on
some
work
on,
like
enhancement,
release
enhancement
and
I'm
curious,
to
know
how
I'll
be
able
to
contribute
to
sync
usability.
I
just
want
to
like
start
getting
like
getting
to
like
understand
more
of
kubernetes
and
how
I
can
like
start
contributing
to
the
community.
A
D
Well,
I
guess
I'm
trying
to-
I
think
I'm
just
like
I
guess
so
far.
I've
worked
a
lot
with
the
ux
team
within
vmware,
so
I
just
kind
of
wanted
to
like
apply
some
of
that
to
the
community
as
well
as
like
kind
of
get
into
the
kubernetes
community.
So
I
felt
like
this
would
be
a
good
place
to
start
yeah
and
it
just
seemed
kind
of
like
approachable,
I
guess,
as
a
community,
so
cool.
A
Cool
well,
they
welcome
to
both
of
y'all,
and
I
guess
with
that
I
have
some
stuff
I
could
share.
As
far
as
the
discussion
guide,
it's
kind
of
like
on
the
next
steps
for
for
our
job
study,
so
I'll
go
ahead
and
share
my
screen
for
that.
A
Okay
can
y'all
see
my
screen.
A
So
in
continuation
of
our
phase,
one,
the
survey
that
we
sent
out
was
kind
of
like
a
screening
but
also
obviously
data
collection
survey,
and
you
know
thank
thanks,
carl
for
giving
us
such
great
background
on
the
on
the
people
that
responded
just
to
kind
of
recap.
From
last
meeting
of
the
people
that
responded,
those
18
118
responses,
34
of
those
agreed
to
be
contacted
for
details
on
their
answers.
A
A
So
what
I've
done
is
I've
started
putting
together
a
discussion
guide,
that's
linked
to
that's
linked
here
and
I
wanted
to
share
it
on
the
call
and
also
just
like
get
some
feedback
from
y'all,
especially
I
don't
know
if
anybody
here
has
done
like
a
jobs
to
be
done.
Interview
process
before,
but
basically
I've
collected
here.
A
What
I
think
are
some
pretty
like
standard
jobs
to
be
done,
questions
and
I'm
kind
of
hoping
to
just
like
get
some
feedback
on
that,
and
also
just
kind
of
like
if
we
feel
like
some
of
these
are
extra
or
we
can
trim
this
down
or
if
we
feel
like
we're
like
missing
detail
somewhere.
I
can
also
send
this
out
on
the
email
group
and
get
feedback
that
way,
but
I'll
go
through
it
real
quickly.
A
Examples
are
tbd,
but
I
feel
like
it
would
be
like
useful
to
kind
of
like
if
anybody
wants
to
help
out
with
interviews
I'll,
be
sending
out
a
schedule
later
and
also
reaching
out
to
to
these
people,
but
we'll
definitely
include
examples
here
of
kind
of
like
the
type
of
content
that
we're
looking
for,
like
what's
a
high-level
job
to
be
done,
a
step.
What
and
what's
an
example
of
something
like
functional
versus
emotional?
A
So
here
we
have
some
basic
kind
of
like
intro
intro
things
I
sent
out
a
message
via
a
contributor
experience,
just
to
see
if
there's
any
guidelines
or
if
anybody
has
done
this
type
of
process
before
like
interviewing
people
in
open
source,
I
didn't
get
back
people
that
had
done
this
before
or
guidelines,
so
maybe
we'll
just
kind
of
like
double
check.
A
If
there's
any
other
place
that
we
can
post,
but
we
may
have
some,
we
may
have
to
determine
that
ourselves,
like
you
know,
if
we
record
these
interviews
kind
of
like
what
do
we
do
with
that
or
you
know,
should
we
record
and
kind
of
like
how
this
data
is
stored?
A
A
Specific
necessarily,
you
know
what
how
do
we
frame
these
interviews
like
we
would
like
to
talk
to
you
today
about
you
know
this,
so
me
would
love
some
feedback
on
that.
A
If
you
have
any
ideas,
we
have
the
basic
kind
of
like
to
tell
us
a
little
bit
about
yourself,
your
background
day-to-day
responsibilities
and
whatever
it
is
that
we're
kind
of
like
that
job
that
we're
going
in
to
ask
them
about
what
it
might
be
like,
like
building
a
development
platform,
for
example
like
what
is
it
that
you're
doing
related
to
that
now,
when
was
the
last
time
you
did
it.
A
How
are
you
going
about
doing
that,
and
so
you
know
if
we
take
building
a
development
platform
as
an
example
of
that
kind
of,
like
investigation
that
we're
doing
being
able
to
kind
of
like
break
that
down
into
into
the
steps
that
they
have
taken
in
the
past
so
like?
What
are
you
trying
to
accomplish?
A
What
are
those?
Oh,
what
are
those
problems
that
you're
trying
to
prevent
or
resolve?
What
is
helping
you
to
achieve
this
goal?
What
would
be
the
ideal
service
that
would
help
you
get
the
job
done?
A
What
else
are
you
trying
to
do
in
addition
to
this?
Are
you
using
any
services
or
tools
in
relation
to
this?
What
are
they
did?
You
use
multiple
products
and
what
is
that
for
your
output,
you're,
seeking
we
have
some
questions
here
for
kind
of
understanding
like
what
they
did
to
prepare,
what
they
did
to
make
sure
that,
like
this
got
up
and
running
also,
how
do
they
know
as
far
as
that?
A
It
worked
for
example,
how
do
they
track
progress
towards
this
kind
of
like
end
goal
that
they're
seeking
what
kind
of
modifications
have
they
had
to
to
make,
especially
you
know
what
are
some
examples
of
things
that
have
gone
wrong
during
this
process
and
also
how
do
they
know
when
they're
done
and
if
there's
kind
of
like
a
next
cycle,
do
they
have
to
do
anything
to
kind
of
like
prepare
for
that
next
cycle?.
A
As
far
as
needs,
you
know
we
can
kind
of
prove
into
like
success.
Metrics,
like
you
know,
what's
time-consuming
what
are
you
trying
to
avoid
what
what
are
kind
of
like
the
unpredictable
parts
of
this
process?
What
makes
you
know
this
solution
more
attractive
than
this
other
solution?
A
What
are
you
dread
doing?
What
could
be
easier
and
annoying,
and
how
do
you
feel
when
the
job
is
complete,
putting
it
to
circumstances
critical
incidents
if
we
need
to
get
specific
or
like
get
some
specific
stories
from
them,
and
I
think
that's
it.
These
are
just
extra
down
here.
A
I
linked
to
some
online
resources
that
I
found
as
well
for
jobs
to
be
done
and
yeah
some
like
sample
recordings
that
I
found
as
well
just
to
like,
listen
to
kind
of
like
how
these
typical
interviews
go.
B
B
A
Yeah
cool,
oh
and
I
should
say
carl
that
you
recommended
that
jobs
to
be
done
book
by
rosenfeld,
and
I
should
source
that
because
that's
where
a
lot
of
these
questions
came
from.
So
thank
you
for
that
recommendation.
C
Cool,
so
let
me
go
back
to
the
oh.
I
had
a
question
here
like
so
I
was
wondering
if
we
are
like
going
to
kind
of
do
this
interview
on
an
iterative
process
or
just
ask
all
these
questions
in
one.
Go.
A
I
think
we'll
be
iterative
with
it,
especially
and
and
that's
also
why
we're
aiming
to
speak
with,
like
10
10
to
15
people.
You
know
we'll
we'll
kind
of
like
use
the
first
people
to
understand
these,
like
initial
sections,
like
understanding
what
it
is
exactly
that
they're
trying
to
achieve
with
kubernetes
and
maybe
like
the
the
rest
of
the
people
that
we
speak
to
to
like
once.
C
Oh
okay
got
it
yeah
and
also
do
we
know,
like
so
carl
had
mentioned,
like
the
categories
that
who
are
these
people
who
are
using
it
right.
So
do
we
like
kind
of
know
what
categories
we
are
targeting
or.
A
Yeah,
so
the
data
that
carl
presented
are
the
people
that
responded
to
our
screening
survey,
so
the
idea
would
be
to
reach
out
to
those
same
people
and
speak
to
them.
A
I
I
think
that,
as
far
as
like
you
know,
deciding
like
people
that
we
want
to
speak
to
or
does
not
speak
to,
like
carl
correct
me
if
I'm
wrong,
but
it
feels
like
the
you
know,
we
we
could
compare
the
individual
people
that
we
reach
out
to
to
the
data
that
came
back
and
also
to
cncf
survey,
which
is
kind
of
what
this
smaller
survey
aligns
to
just
to
make
sure
that
we're
getting
some
like
representative
people.
B
Yeah
I'd
agree,
I
mean,
I
think,
in
some
ways
they're
monolithic
like
they
do
tend
to
have
a
lot
of
the
same
traits
but
yeah.
We
want
to
make
sure
there's
a
good
enough
spread.
I
don't
think
we
probably
have
the
like,
like
resources
right
now
to
do
like
multiple
persona
comparisons,
especially
since
we
don't
really
know
what
those
are
we
just
have
to
be
interviewing,
like
you
know
twice
as
many
people,
so
I
think
we'll
probably
start
with
sort
of
like
who
we
imagine
kind
of
the
core.
Core-Ish
person
is
using
kubernetes.
A
Yeah,
I
mean
all
right
all
great
questions
so
also
from
the
book
that
we've
been
referencing.
Here's
an
example
of
a
sample
note
document
that
we
could
use
just
to
kind
of
be
able
to
capture
observations
and
then
do
interpretation
on
top
of
those.
So
I
went
ahead
and
included
that
here
and
what
I
will
also
be
doing
is
I'll
be
kind
of
like
bootstrapping.
A
This
template
here
I
haven't
had
too
much
time
to
go
in
and
kind
of
like
tweak
it
to
us,
but
I'll
definitely
bootstrap
it
and
send
it
out
just
to
get
organized
and
if
anybody's
interested
in
kind
of
like
helping
out
with
these
interviews,
you
can
sign
up
here
and
just
kind
of
like,
but
for
a
time
that
works
for
you
and
will
kind
of
like
coordinate
that
way.
But
we
are
definitely
looking
for
help
in
conducting
them.
A
B
I've
used
otter,
ai,
which
is
like
a
free
transcription
service
and
takes
a
little
bit
of
work
to
finalize,
but
would
be
a
nice
way
to
to
kind
of
have
all
of
the
data
to
go
over
after
and
so
those
those
two
approaches
could,
I
think,
help
the
analysis
out
a
lot.
A
Yeah,
I
think
that's
awesome
that
aiming
for
at
least
two
people
per
interview
at
a
minimum
would
would
be
ideal,
and
I've
also
just
got
introduced
to
otter
this
year
by
our
researcher
so
yeah,
it's
super
awesome,
so
yeah
we'll
definitely
try
to
use
it.
If
we
can
cool.
A
Awesome
so
I
think
that's
it
as
far
as
agenda
topics,
we
have
a
working
sessions
set
up
for
for
the
jobs
to
be
done,
effort
we'll
try
and
kind
of
like
post
to
our
slack
channel
if
y'all
are
part
of
that,
just
if
anybody
just
to
keep
people
updated
yeah
any.
B
Cool,
I
just
want
to
say
that,
if
anyone's
been
reaching
out
to
me
via
ibm
or
redhat
channels,
I'm
actually
going
to
be
leaving
ibm-
or
I
mean
red
hat-
will
look
kind
of
the
same.
In
a
few
weeks,
I'm
going
to
be
working
at
userzoom
starting
in
october,
but
even
though
they're
not
at
all
kubernetes
related
I'll
still
be
sticking
around
here,
but
just
just
for
general
awareness.