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Description
Weekly demo issue link - https://gitlab.com/gitlab-org/incubation-engineering/apm/apm/-/issues/8
A
A
A
I'll
just
show
you
here.
So
this
is
the
first,
the
first
environment,
variable
or
bit
of
conflict
that
this
part
of
the
agent
supports.
There
are
lots
of
other
parts
like
process
and
log
monitoring
things
like
that.
We
aren't
going
to
analyze
at
the
moment
until
we
till
we
need
to
so
documenting
this.
I've
started
putting
these
this
documentation
this
issue
and
we've
got
the
sort
of
request
that
we
expect,
like
validation,
requests
there
and
links
to
parts
of
the
documentation.
A
There
are
some
potentially
slightly.
You
know
unusual,
non-documented
parts
of
the
agent
here
so
there's
this
intake
endpoint
that
we
need
to
have
a
look
at
a
bit
more
where
there
are
a
couple
of
requests
here,
for
example,
it
sends
through
a
lot
of
metadata
about
the
host
that
it's
running
on,
so
it
will
send
through
information
about
the
hardware
specs,
the
operating
system
host
names,
install
method,
all
sorts
of
useful,
useful
stuff
that
we
could
use
for
auditing.
A
We
probably
aren't
looking
to
capture
this.
What
we
might
do
for
the
time
being
is
just
log
this
information
out,
so
we
can
check
logs
and
see
what's
going
on,
but
we
probably
won't
save
this
initially,
unless
we
actually
need
to
refer
back
to
this
and
really
if
we
need
this
for
end
users
to
be
able
to
sort
of
see,
make
sense
of
what
agents
are
being
used
for
examples.
There's
an
initial
one
there.
A
It
shows
you,
for
example,
what
what
other
processes
are
running
in
this
environment
and
then
the
second
one
gives
you
a
lot
more
information
I've
yet
to
really
break
this
down.
It
seems
to
give
sort
of
container
error
states
and
things
like
that,
and
then
we
get
a
check
run
endpoint,
which
is
events
about
service
checks
that
the
agent
is
performing
so,
for
example,
here
we're
blocking
external
traffic
when
we're
testing
this
agent.
A
So
this
ntp
in
sync
check
is
failing
with
this
somewhat
cryptic
status
code,
which
I
believe
means
critical
in
this
case,
because
zero
one,
two
three
so
zero
is
okay.
One
is
warning:
two
is
error.
Three
is
critical
and
other
checks.
For
example.
Here,
like
you
know,
the
actual
agent
itself
is
okay
and
so
on
and
so
forth.
So
that
might
be
useful.
But
again
we
won't
look
to
take
that
straight
away.
What
we
want
to
focus
on
is
the
series
data.
Initially
it's
where
we
actually
have
things
like
system
metrics
and
I've.
A
A
It's
got
quite
nice
service
boundaries,
so
we
don't
have
to
host
it
in
the
same
environment
as
gitlab.com.
We
can
have
it
in
a
separate
google
cloud
project
and
a
separate,
obviously
separate
kubernetes
cluster,
for
example,
so
that
will
make
it
easier
to
isolate
and
understand
the
costs
around
running
this
service.
So
that's
that
the
other
thing
I'm
looking
at
right
now
is
the
schema
evaluation
for
click
help.
A
I'm
going
to
use
a
this
time
series
I'll
drag
the
link
over
here
time,
series
benchmark
suite,
which
I
think
was
created
by
influx
db.
Initially
and
now
it's
been
sort
of
taken
up
by
time,
scale
db
to
do
a
bunch
of
comparisons
between
time
series.
Specific
databases
see
click
houses
in
here
and
a
timescale
db
and
a
few
others.
So
what
I'm?
I
don't
want
to
benchmark
against
all
of
them,
but
what
I
want
to
do
is
compare
a
potential
more
generic
schema
that
we
might
use
against.
A
The
click
house
schema
that
this
benchmark
uses,
because
this
is
a
very
s,
sort
of
hard
coded,
very
specific
schema
for
certain
series
data.
So,
like
one
schema
for
cpu
one
schema
for
memory,
for
example,
we
don't
really
want
to
do
that,
so
I'm
going
to
see
if
we
can
get
a
sort
of
equivalent
or
a
decent
enough
performance
with
a
more
generic
schema
I'll
also
be
comparing
those
results
against
some
of
the
other
competitors
based
on
whether
we
think
they're
applicable
or
not.
A
A
So
it's
not
just
time
series,
but
we
can
put
all
the
data
in
there,
so
we
can
work
with
logs
when
we
get
there
work
with
traces,
so
only
a
few
of
those
come
out
of
that,
so
I'll
be
doing
a
comparison
with
a
few
of
those
to
make
sure
that
we're
going
in
the
right
direction.
Obviously,
we
don't
have
time
to
compare
every
single
database
on
the
market,
but
it's
a
bit
of
due
diligence.