►
From YouTube: Grafana Agent Community Call 2022-06-15
Description
This call covers usage stats, hardware requirements, and an initial peak at the state of Flow.
A
Hey
hello,
everyone
welcome
to
today's
edition
of
the
graphenizing
community
hall,
I'm
pascalis.
I
will
be
your
host
for
today.
This
talk
will
be
available
on
grafana's
youtube
later
on.
So
if
you
want
to
be
seen
or
heard,
then
consider
this
your
warning
and
in
today's
agenda
we
have
two
main
topics.
A
First,
we're
gonna
present
a
new
way
of
how
we
plan
to
utilize,
like
bi
data,
to
understand
the
the
usage
of
beta
features
in
the
agent
and
how
it
can
help
us
plan
our
next
releases,
plus
some
data
around
the
agent's
hardware
requirements
as
we
scale
up.
We
would
also
like
to
give
a
small
update
on
how
flow
is
going.
A
You
have
no
idea
about
what
flow
is
it's
a
new
way
of
configuring
engagement
that
is
going
to
be
a
beta
feature
in
the
next
few
months
we
dedicated
the
whole
episode
of
the
community,
called,
I
think,
like
the
last
community
call.
So
if
you
wanna,
if
you're
interested
about
that,
you
can
go
there
and
check
it
out.
B
So
this
will
help
us
to
identify
which
feature
flags
are
being
used
more
and
prioritize
if
we
want
to
promote
some
of
these
features
from
experimental
to
like
a
more
stable,
yeah
feature
right.
So
by
default,
we
decide
to
be
this
opt-in,
sorry,
opt-out,
so
by
default
by
default,
it's
enabled
we
follow
the
approach
of
other
projects
like
loki
and
in
this
yeah
in
this
documentation.
B
You
can
use
this
flag
and
it
will
disable
the
reporting.
So
that's
it.
We
encourage
people
to
keep
using
this
reporting,
because
it's
gonna
help
us
to
have
better
insights
of
adoption
of
features
and
maybe
in
the
future
we
will
use
for
other
statistics
yeah.
So
I
think
that's
it.
If
anyone
has
a
question.
B
Right
so
there
wasn't
this
like
an
internal
discussion
about
that,
so
the
loki
team
initially
decided
to
well.
They
also
they
added
this
like
before
us
and
they
did
like
as
opt-in
and
after
the
rollout
of
this.
No
one
enables
the
feature,
so
they
decide
to
to
do
it
helped
out
because
they
didn't
have
any
data
after
a
couple
of
weeks
or
months
of
having
this
feature,
yeah
rather
deployed
right.
So
that's
why
we
yeah
other
people
in
grifana
encouraged
us
to
do
to
follow
the
same
approach.
B
B
C
A
C
B
C
A
A
A
But
we
could
not
extrapolate
that
to
how
the
agent
would
react
when
scaling
up.
So
in
order
to
test
that
we
provisioned
some
environments
where
we
could
deploy
a
standalone
agent
and
stress
it
up
to
like
14
to
16
million
active
series.
That
means
it's
actively
recording
data
and
then
in
a
more
real-life
scenario
of
having
like
400
000
cities.
We
would
never
recommend
you
running
the
agent
with
that
kind
of
load.
You
would
be
much
better
served
by
using
some
clustering
method
from
our
documentation
page,
but
nevertheless
these
are
some.
A
This
was
heavily
inspired
by
what
prometheus
does
with
prompens,
which
automatically
can
not
automatically,
but
using
a
github's
approach
can
serve
data
about
the
performance,
how
a
certain
pr
affects
performance
of
prometheus
and
maybe
in
the
future.
We
could
have
something
like
that
for
the
agent
as
well
like
being
able
to
quantify
a
regression
or
an
improvement
right
there
in
the
pr.
A
Can
you
see
it
now
yeah?
Okay?
So
this
is
the
internal
benchmark
that
we
run
the
first
one
is
the
more
active
one
with
14
to
16
million
active
series,
and
the
second
one
is
the
more
realistic
scenario:
we're
measuring
things
like
os
hardware,
usage
levels
like
memory
and
cpu
disk
space
usage
network
rates
file
descriptors,
as
well
as
how
the
one
size
oscillates
when
it
is
checkpointing
data
or
is
clearing
all
the.
A
Other
entries
how
the
bytes
per
series
metric
runs
over
time.
That
means
how
much
memory
the
agent
consumes
per
active
series,
as
well
as
some
go
specific
metrics
about
how
many
gold
routines
are
running,
to
verify
that
there's
no
leaks
or
if
the
garbage
collection
takes
a
certain
amount
of
time
and
does
not
explode
for
some
reason.
A
We've
come
to
the
conclusion
that
for
a
hundred
thousand
series
incorrect
here,
it
seems
like
we'd
recommend
you
running
with
at
least
0.01
cores
that
might
sound
stupid.
But
if
you
can
configure
that
limit
in
kubernetes
and
it
might
make
sense
about
0.6
gigabytes
of
memory
and
half
a
gigabyte
of
disk
space.
C
A
A
A
The
runner
machine,
the
second
machine
which
was
just
running
the
agent
on-
and
I
would
do
20.4
if
I
remember
correctly
instance,
and
nothing
else-
was
scraping,
five
copies
of
the
first
endpoint
and
then
one
copy
of
the
second
endpoint,
and
it
was
just
dumping
the
data
on
the
fake,
remote
right
and
point
that
always
returned
immediately
with
200k
code
and
to
obtain
this
data.
We
also
enabled
the
the
process
node
exporter
integrations.
A
Let
me
see
if
there's
anything
more
specific,
we
have
recorded
the
commands
used
to
generate
the
avalanche,
metrics
and
the
configuration
for
the
agent.
So
once
this
document
is
public,
then
maybe
someone
could
they
could
replicate
these
results
if
they
wanted
to,
but
I
think
that's
pretty
much
an
overview
of
how
this
data
was
obtained.
C
A
A
Okay,
to
avoid
a
longer
awkward
challenge.
Here,
I
would
like
us
to
move
on
to
the
third
part
and
provide
a
small
update
on
how
flow
is
going
again.
Flow
is
a
new
experimental
feature
that
we're
bringing
into
the
agent
that
will
allow
you
to
configure
the
agent
in
a
different
way
and
allow
us
to
map
the
agent
configuration
more
into
the
mental
model
of
how
a
user
would
like
it
to
work
instead
of
replicating
prometheus,
compatible
jams
in
duplicate
over
and
over
again.
A
So
yeah,
if
that
sounds
interesting
to
you,
I
think
that
there's
more
good
stuff
on
the
way
you
can
either
wait
a
few
more
releases
to
to
really
get
to
see
how
it
would
work
for
you
or
you
could
check
out
the
main
branch
and
see
what
we're
currently
building
there's
work
to
be
done.
So,
if
you
even
want
to
contribute
it's
open
source
and
we'd
love
for
more
people
to
join
in
on
the
phone.
C
The
head,
robert,
all
right
so
right
now
all
the
flow
code
isn't
isn't
in
the
the
the
normal
agent
command.
There's
a
separate
command,
we're
working
with
for
prototyping,
but
when
we're
ready
to
release
it
as
an
mvp
it'll,
be
in
the
bridge
age
command
with
a
flag
to
enable
it.
I
don't
know
when
what
release
that'll
be,
probably
like
20
00
27,
probably
not
probably
not
26,
though
within
the
next
few
months,
is
the
hope.