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From YouTube: MetaMask interview with Aaron Davis
Description
The MetaMask crew brought a tool that proved invaluable in their network connectivity diagnostics: a DHT visualizer. Following some wireless network trouble (a real-world scenario to be sure), we were treated to some beautiful visualizations of network connectivity. Learn more: https://blog.ipfs.io/2019-10-03-ipfs-camp-sci-fi-fair-videos/
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B
Over
yes,
so
right
now
we're
trying
well
minimus
lets
you
hold
your
own
keys
for
the
etherium,
we're
trying
to
digitize
our
infrastructure
right
now.
You
do
all
your
reads
about
the
blockchain
state
from
centralized
infrastructure,
but
we
want
it
to
be
a
proper
likely
now,
that's
non-trivial,
because
we
can't
access
the
main
network.
We
don't
have
the
tcp/udp.
We
need
in
the
browser
to
do
that.
B
So
we
have
to
do
this
much
larger
engineering
project,
which
involves
creating
a
second
Network
black
clients,
and
that
also
led
us
to
realize
that
there's
going
to
be
orders
of
magnitude
more
like
clients
than
full
nodes,
and
so
we
need
to
really
redesign
how
like
clients,
work
and
how
they
share
data
and
how
they
find
each
other.
So
they
can
share
the
data
they
have
the
idea.
So
here
we've
got
a
little
data
visualization
of
a
of
a
test
net
in
real
world
networking
conditions.
B
A
B
So
our
telemetry
server
is,
you
know,
running
in
a
cloud
in
much
easier
access.
Then
maybe
these
other
peers
yeah,
which
are
running
on
people's
laptops.
So
what
I'm,
especially
interested
right
now
is,
is
the
DHT
and
some
performance
characteristics
of
the
DHT,
especially
running
on
top
we're
TC
and
running
in
the
browser.
Mm-Hmm.
B
So
I
have
some
other
views
here.
We
can
look
at
it
and
based
on
their
like
X
or
position
their
ie
yeah.
Let's
have
a
look
at
that,
so
this
is
putting
them
into
circle
here.
The
lines
are
showing
again
their
connectivity
mm-hm.
So
we
can
also
look
at
something
like
the
DHT
routing
table
yeah,
which
is
going
to
look
very
similar
because
they're
connected
to
their
peers
in
the
routing
table
right
so.
A
This
is
showing
us
the
shape
of
the
network
according
to
like
basically
the
kunia
distance,
essentially
the
Khedive
Miyake
space-
and
these
are
this-
this
these
lines
are
actually
showing
us
the
membership
right
in
routing
table.
So
what
peers
hold
other
peers
in
their
routing
tables?
That's
right,.
B
B
A
B
B
A
This
is
actually
showing
us
that
the
DHD
in
a
way
is
like
is
showing
us
churn
right
and
the
DHT
the
want
the
nose
that
have
stayed
that
a
greener
are
have
been
on
the
DHT
for
less
time,
which
means
that
they
might
have
it
that
might
not
be
so
stable.
That
might
not
be
providing
that
stability
to
the
DHD.
That
is,
you
know,
a
desirable
property
in
a
tasty.
B
B
B
A
B
A
B
A
A
great
a
great
platform
agreed
in
our
experiment
to
actually
run
experiments
on
the
network
itself
right
so,
as
you
are
able
to
visualize
the
network,
and
you
are
able
to
instruct
particular
peers
to
run
a
particular
operation
that
and
you're
able
to
like
inspect
how
that
operation
actually
unraveled
in
the
network.
That
is
pretty
awesome
visualization
because
it
appeared
to
be.
Our
networking
is
very
hard
to
understand.
So
having
visuals
like
this,
make
the
whole
thing
a
lot
more.
B
A
Right
so
what
actually
I'm
wondering
like
for
meta
mask
itself
and
for
the
projects?
You
know,
because
you
said
that
you
are
building
these
visuals
and
this
technology
to
actually
gain
insight
into
how
the
foundation
is
works
of
the
networking.
So
how?
Why
did
you
actually
pick
Libby
to
be
itself
as
a
networking
stack
to
build
upon
so.
B
A
Course,
with
transport
transparency,
you're
able
to
use
WebRTC
with
the
same
business
logic
such
that
it
can
seamlessly
switch
to
TCP
UDP
in
the
future.
If
you
know
browsers
what
implemented,
which
there
are
some
efforts
to
go
in
that
direction
like,
for
example,
the
Deep
Web
yeah.
So
have
you
been
working
with
them
or.
B
A
Socome
obvious
I
think
this
demo
was
amazing.
This
kind
of
tooling
is
exactly
what
we
need
for
to
be
able
to
understand.
What's
going
on
and
peer-to-peer
networks,
we
particularly
I'm
from
the
Lippe
to
be
team,
and
we
have
to
evolve
a
lot
to
get
to
a
place
like
this.
We're
probably
going
to
continue
working
with
Kamali's
to
like
get
some
of
his
learnings
and
get
kind
of
some
of
his
insights
and
to
how
to
build
these
tools
so
that
we
can
make
them
available
to
the
entire
Lippe
to
Bierko
system
and
I.