►
Description
We will be discussing a use case for utilizing drones to make deliveries to warehouses, as well as looking at the technologies used to build an end to end IoT pipeline on Kubernetes that allows you to gather and visualize your fleet in real-time. We will be demonstrating how this data can be utilized to send real-time instructions to drones in cases such as collision avoidance, no-fly zone avoidance, and heavy wind avoidance. All of the code from this talk is 100% open source and can be tested by anyone in attendance.
B
A
Sorry,
red
dot
I
was
looking
for
where
that
was
so
yeah
I'd
like
to
thank
everyone.
Who's
joining
us
today.
Welcome
to
today's
CN
CF
webinar
use
open
source
bare
metal
and
5g
to
achieve
autonomous
drone
delivery.
That's
exciting
I'm,
Paul,
Burt
I'm,
a
technical
product,
marketing
engineer
at
net
app
and
cloud
native
ambassador,
so
I'll
be
moderating.
Today's
webinar
I'd
like
to
welcome
our
presenter
today,
Cody
he'll
fill
field,
CTO
a
tacit
and
a
couple
housekeeping
items
up
top
here
during
the
webinar
you're
not
able
to
talk
as
an
attendee.
A
There
is
a
Q&A
box
at
the
bottom
of
your
screen,
though.
Please
feel
free
to
drop
your
questions
and
then
we'll
get
to
as
many
as
we
can.
Cody
sounds
like
he's
up
to
the
challenge
of
answering
things
as
they
come
in,
but
if
your
question
doesn't
get
answered,
live
I'll,
sift
through
them
and
make
sure
he
gets
a
glance
at
them
at
the
end,
and
this
is
an
official
webinar
of
the
CNC
F
and
as
such,
it
is
subject
to
the
CNC
F
code
of
conduct.
A
So
please
do
not
add
anything
to
the
chat
or
questions
that
would
be
in
violation
and
etco2
conducts
basically
just
be
respectful
to
your
fellow
participants
and
presenters.
The
recordings
and
slides
will
be
posted
later
today
on
the
CNC
F
webinar
page,
that
is
CN
CF
dot,
IO,
slash
webinars
and,
with
that
I'll
hand
it
over
to
Cody
to
kick
off
today's
presentation.
B
Yeah,
thank
you
very
much.
Paul
really
appreciate
it
mm-hmm
so,
as
Paul
said,
I'm
Cody,
Hill,
a
packet
field
CTO
and
we'll
be
talking
about
the
work
that
we've
done
today
that
we've
done
with
Sprint
on
their
IOT
curiosity
platform
and
kind
of
diving
into
a
use
case
that
we
have
with
drone
delivery.
So
a
little
bit
about
me
is
that
classic
slide
that
all
presenters
give
I've
been
in
the
tech
industry
for
15
years
started
out
at
an
ISP
I.
B
So,
as
Paul
mentioned,
I
encourage
you
to
ask
me
questions
right.
The
QA
inside
zooms
there
so
go
ahead
and
drop
questions
in
and
I'll
go
ahead
and
try
to
answer
them
as
I
go
yeah
I'm
going
to
get
somewhat
deaky
and
techie
on
some
of
this
stuff.
So
if
you
have
questions,
I
want
to
make
sure
we
catch
everybody
yet
before
we
we
move
forward
so
go
ahead
and
do
that
so
here's
the
agenda
for
today
right.
B
And
then
we
want
to
talk
about
how
you
could
deploy
physical
servers
on
the
edge
of
Sprint's
curiosity
Network
right,
so
you
get
extremely
low
latency
to
the
end
devices
there
and
then,
once
you
have
these
these
servers
right.
Nobody
really
cares
about
physical
servers
right
they
care
about
the
applications
that
run
on
those
servers.
So
what
does
it
take
to
turn
a
normal
server
into
an
IOT
warehouse
and
analytics
tool
so
that
you
can
start
analyzing
your
data
from
all
your
iOS
devices
and
then
we're
going
to
basically
show
you?
B
You
know
how
to
put
that
software
on
the
hardware
and
do
a
live
demo,
and
then
everyone's
gonna
leave
today
with
the
github
link
to
all
of
the
code.
I'll
be
demoing
today,
as
well
as
a
promo
code
to
get
into
packet
and
get
some
free,
compute
credits
and
try
it
out
yourself.
Okay,
it's
a
little
bit
about
packet
right.
B
So
as
of
last
week,
we
have
just
been
acquired
by
Equinix
right,
so
we're
no
longer
a
small
startup
company,
we're
now
part
of
Equinix
and
we're
really
excited
about
that,
and
we
have
about
20
plus
cloud
locations
about
130
members
and
on
the
packet
side
of
the
house.
We
were
founded
back
in
2014
by
our
CEO
and
a
few
others
that
are
been
in
the
infrastructure
space
for
quite
a
while
and
the
cool
thing
about
our
platform.
B
Is
it's
it's
bare
metal
you
that
you
can
spin
up
just
like
a
cloud
right,
so
you
get
a
server
in
as
little
as
60
seconds
and
we
have
over
60,000
servers
being
deployed
and
destroyed
every
month
right.
So
quite
a
bit
of
you
know
where
we're
on
chair
in
that
hardware.
Spinning
about
tearing
it
down
so
it's
pretty
cool
one
of
our
marquee
customers
is
sprint
right
and
spread.
Had
the
opportunity
to
say,
let's,
let's
throw
out
everything
that
we
know
about
a
cellular
network
and
let's
start
from
scratch,
and
really
build
a
network.
B
So
they
came
out
with
what
they're
calling
their
curiosity
core
and
they
could
have
gone
to
any
of
the
public
clouds
or
try
to
build
their
own
data
centers
and
do
all
of
that
right,
because
there's
friends
of
massive
they
can
do
it
and
what
they
realized
is
that
their
core
competency
isn't
hosting
data
centers
you're
dealing
with
servers
their
core
competency
is
that
networking
side
of
things,
so
they
partnered
up
with
packet
and
what
packet
is
allowing
them
to
do?
Is
they
put
their
finger
on
a
map
anywhere
in
the
US?
B
And
they
say
I
want
to
have
a
5g
network
in
this
city,
and
packet
will
do
all
the
things
necessary
to
deliver
them.
A
REST
API
with
physical
servers
that
they
can
provision
with
all
the
networking
they
need
in
less
than
90
days
right,
so
they
can
go
into
any
market
anywhere
in
the
US
and
and
pack
it
on
the
hook
to
deliver
that.
So
it's
become
a
great
partnership
and
I
think
we're
in
live
in
22
cities
around
the
u.s.
now
and
and
more
to
come
in
2020
right.
B
So
that's
that's
what
Sprint's
doing
with
packet,
and
so
we
decided-
let's,
let's
show
some
people
how
to
utilize
this
IOT
network
and
leverage
packet
and
all
of
that
right.
So
this
is,
you
know
you
can
have
it.
However,
you
like
right,
so
you
can
create
your
own
servers
on
packet.
We
have
a
nice
web
UI
off
to
the
right
here.
You
can
use
a
REST
API,
that's
an
actual
kernel
command
that
will
spin
up
a
server
for
you
or
use
the
automation,
framework
or
language
that
you
want.
B
Terraform
ansible
doling
python
right,
whatever,
whatever
language
or
truehl
you're
comfortable
with
you,
could
spin
a
physical
servers
on
the
edge
of
the
sprint
curiosity
network
that
will
get
you
extremely
low
latency
access
to
your
end
devices
right
whether
those
are
drones
that
are
transmitting
a
lot
of
data
or
standard
warehouse
machinery
that
are
sending
temperature
and
things
like
that
right.
So
you
could
spin
up
those
servers
on
the
edge,
but
servers
aren't
like
I
said
earlier.
Aren't
the
most
exciting
thing
about
this
right?
A
server
without
an
application
is
useless
right.
B
So
it's
really
about
the
IOT
software
that
goes
into
it.
So
we
work
with
some
some
friends
of
packets
and
really
smart
folks,
and
we
put
together
what
we
think
the
best
of
breed
open-source
technologies
that
will
allow
you
to
build
an
end
to
end
IOT
pipeline
and
really
capture
store,
visualize
all
of
that
data,
so
that
you
can,
you
know,
really
leverage
the
all
of
the
data
coming
off
of
in
this
case
drones
right.
So
you
can
see
the
drones
at
the
bottom
and
really
what
what
they're
doing
is.
B
They
are
transmitting
a
JSON
payload
to
emitter,
which
is
an
open
source
again.
Kuchiki
broker
that
is
then
tied
into
the
open,
faz
and
Alex
Ellis
helped
us
out
with
this
from
open
Fez
and
it's
tied
in
two
different
topics.
Inside
of
that,
and
then
certain
functions
inside
of
open
fast
are
doing
inserts.
In
the
databases
we
have
functions
to
render
a
map.
B
So
we
can
see
where
these
drones
are
on
a
map
and
I'll
show
you
that
in
a
demo
in
a
minute,
and
then
we
can
actually
read
the
data
out
of
out
of
the
Postgres
database
as
well
and
then
kind
of
for
free
some
of
the
things
that
you
get
with
open
fast.
As
you
get
Prometheus
monitoring
of
all
of
your
functions
and
all
of
that.
So
every
time
you
ingest
something
that
goes
into
Prometheus.
B
You
get
some
nice
graph
on
of
charts
to
show
you
how
that
ingestion
rate
and
all
of
that
is
working,
and
then
we've
we've
layered
on
meta
base,
which
is
a
business
intelligence
tool
and
Matt
box,
which
is
a
visualization
tools,
and
this
is
all
kind
of
layered
together
to
kind
of
get
you
a
lot
of
visualization
and
some
intelligence
into
that
data.
So
it's
kind
of
break
these
things
down
for
a
minute
right.
So
the
first
piece
of
this
is
kubernetes
rights.
All
of
this
runs
on
top
of
kubernetes.
B
In
this
example,
we
chose
k3s
because
k3s
was
specifically
designed
to
be
the
kubernetes
at
the
edge
very
minimal
installation
of
Cooper,
Nettie's,
very
lightweight.
So
we
said:
hey,
that's
that's
a
great
use
case
to
deploy
that
right.
So
I
assume
everyone
on
this
call
is
familiar
with
kubernetes
right,
but
we
can
cover
it
a
little
bit
right.
B
So
kubernetes
is
an
open
source
container
orchestration
framework
right,
so,
whether
you're
using
docker
or
just
container
d,
it
basically
orchestrates
deploying
your
container
workloads
across
one
or
multiple
servers
and
then
handles
all
of
the
plumbing
from
getting
used
certain
services.
Your
services
delivered
to
it,
you
know
ingress
access,
it
can
handle
scaling
those
in
an
automated
fashion
and
really
allows
you
to
care
less
about
your
physical
infrastructure
and
and
kind
of
like
kubernetes
orchestrate.
All
of
that
for
you
right.
B
So,
a
pretty
cool
application
framework
works
really
good,
with
all
the
components
that
we
have
here
and
it's
really
the
way
the
industry
is
going.
Everything
is
being
built
to
run
on
top
of
kubernetes.
So
why
not
large
that
way
as
well?
Okay,
so
so
the
next
piece
of
code
that
we
need
is
emitter
route.
So
the
emitter
is
an
open
source
in
QT
key
broker,
and
one
of
the
things
that
we
really
liked
about
emitter
was
that
it's
horizontally
scalable,
which
you
don't
get
in
a
lot
of
in
PTT
brokers
right.
B
So
as
you
need
to
scale
up
the
amount
of
ingestion
points,
you
can
just
create
more
and
more
replicas
of
emitter
and
it'll
it'll
handle
that
that's
scaling
for
you,
and
then
it
was
built
from
the
beginning
to
be
super
fast
and
secure
right.
So
every
single
topic
inside
of
the
MQTT
broker
has
the
ability
to
be
protected
by
an
authentication
token.
So
it
really
keeps
you
from
you
know,
making
sure
your
data
secure
and
your
Indian
points
secure.
B
So
you,
like
we
likee,
mitr
and
then
kind
of
the
galloon
kind
of
the
heart
of
this.
That
kind
of
puts
everything
together
was
open
files.
We
said
you
know
we
can
possibly
write
some
custom
code
and
build
our
own
containers
and
you
know
build
our
application
to
ingest
the
data
from
emitter
and
dump
it
into
a
sequel
database.
B
And
then
you
know
build
some
some
code
inside
of
our
app
to
render
a
database
mount
format,
box
and
stuff
like
that,
and
we,
you
know
why
not
use
a
service
framework
such
as
open
fast
and
so
that
that
worked
out
really
well
and
and
with
open
faz.
It
kind
of
office
skates
all
of
the
complex
things
inside
of
kubernetes
and
allows
you
to
just
kind
of
focus
on.
You
know
your
code,
the
functions
that
you
want
to
deploy
and
and
distills
everything
down
to
the
docker
container
level
right.
B
B
Next
is
prometheus
and
we
kind
of
talked
about
that
right.
So
if
you're
not
familiar
with
Prometheus
right,
it's
cloud
native,
compute
foundation,
project
right
so
go
see,
SPF
and
it's
a
a
monitoring
system
that
will
basically
scrape
your
data
endpoint,
so
it
actually
reaches
out
and
collects
data
for
you
right
under
than
you
having
to
shove
data
or
push
data
into
it.
So
all
you
have
to
do
is
host
a
REST,
API
and
it'll
start
scraping
that
REST
API
for
for
information
right.
B
So
it's
going
to
be
pulling
in
your
metrics
and
it's
underneath
it.
Ultimately,
it's
a
time
series
database,
so
it's
very
efficient
to
store
all
of
the
metrics
that
are
coming
in
and
then
display
them
on
a
graph
and
do
those
types
of
things
right
so
Prometheus
is
probably
I
think
has
won
the
format
war
for
modern
monitoring
systems,
and
it's
it's
great
in
this
scenario
and
we'll
kind
of
show
a
little
bit
of
that
in
a
minute
and
then
graph
on
ax.
B
If
there
there
was
a
war
for
visualizing
all
of
this
data
in
an
open
source
way
graph
on
a
definitely
won.
That
and
Griffin
is
a
great
visualization
analytics
engine.
It
allows
you
to
tie
in
almost
any
data
source.
In
this
case
reason
Prometheus.
We
could
use
Postgres,
but
almost
any
data
source,
and
then
you
could
build
beautiful
graphs
and
charts
and
all
of
the
things
to
kind
of
visualize
that
data
and
kind
of
do
trends
and
in
all
of
those
things.
B
So
it's
it's
really
great
to
store
all
of
this
data
we
chosed
Postgres
and
we
chose
Postgres
because
it's
been
around
for
a
long
time.
It's
really
stable
and
we
didn't
want
to
get
extremely
creative
on
that
aspect
of
it.
We
could've
chose
cockroach
DB
or
you
debate,
or
some
of
the
new
newer
cloud
native
scale
out.
B
You
know
databases,
but
we
just
wanted
to
keep
it
simple
in
this
example,
so
he
shows
just
a
standard
helmet
art
for
Postgres
and
we
went
and
deployed
that
and
if
you're
not
familiar
with
post
press,
that's
been
around
for
a
long
time.
It's
an
open
source
relational
database
and
has
has
come
a
long
way
and
has
been
adopted
by
quite
a
few
cloud
thinking
and
scale
out.
Database
companies
such
as
cockroach
and
and
yoga
by
DB
they've
standardized
on
PostgreSQL
in
that.
So
in
this
example.
B
If
you
did
need
to
spread
this
data,
you
know
into
multiple
geographic
locations.
All
of
this
code
would
be
easily
replaced
by
just
replacing
that
database
with
yuka.
By
now
you
have
a
distributed
system
as
well
right,
so
Postgres
is
a
good
option
here,
and
then
we
have
map
box
right.
So
matte
box
is
a
really
cool
piece
of
software
and
really
what
it
allows
you
to
do
is
visualize
any
type
of
geographic
map
data,
and
you
know
it
kind
of
overlays
it
on
top
of
Google
Maps.
B
You
can,
then
you
know,
put
different
types
of
points
and
things
on
that
map.
So
in
this
case
we
have.
We
want
to
visualize
where
our
drones
are
going
right.
So
our
drones
are
starting
at
the
hangar,
there's
a
going
to
make
their
deliveries
at
a
couple
separate,
warehouses
and
they're
going
to
come
back
to
the
hangar,
and
you
kind
of
want
to
see
see
what
that
looks
like
in
real
time
and
where
those
drones
are
and
matte
box
really
helps
out
with
that
so
great
tool
there
and
then
lastly
is
meta
base.
B
So
meta
base
is
a
business
intelligence
tool.
It's
open
source
and
one
of
the
cool
things
about
it
is
that
it
starts
making
some
intelligent
decisions
for
you
right,
so
it
search
correlating
data
says
hey.
This
looks
like
coordinates
data.
Let
me
build
a
map
and
put
that
on
there
is
this
map
look
good
deal
yeah!
Oh
yeah!
That's
great
I
need
to
build
that
map
right
and
it's
gonna
start
seeing
different
trend
data
with
you
know.
Maybe
the
battery
is
starting
to
deplete
automatically
on
these
drones
and
it
sees
the
same
pattern.
B
It's
like
hey.
You
probably
want
to
see
this
on
a
chart.
Next
to
all
these
drones
and
it'll
build
that
chart
automatically
for
you.
It's.
You
just
need
to
tweak
a
couple
things
here
and
there,
but
it's
actually
an
intelligent
business
intelligence
tool
right.
So
you
don't
have
to
be
the
only
one
bringing
intelligence
to
the
party.
So
we
really
like
meta
base
for
this.
It
was
great
cool,
so
mm-hmm
now
we
talked
about
the
software.
We
talked
about
deploying
servers
at
the
edge
in
the
past.
B
So
how
do
you
actually
get
this
thing
deployed
altogether
and
marry
this
stuff
together
right?
So
what
we
did
is
we
built
a
git
repository
right?
You
guys
can
all
go
to
this
thing.
It's
github.com
slash
packet,
labs,
slash,
iot,
okay
and
in
there
there's
a
case
directory
right
so
inside
that
cait's
directory
there's
some
Kara
form
scripts
and
off
to
the
right
screenshot
of
what
it
looks
like
when
the
terraform
playbook
is
finished.
B
So
basically,
you
go
in
and
say:
terraform
apply
it
to
fill
out
a
couple
variables
right,
but
tariffs
won't
apply
it
kicks
this
thing
off
in
the
end,
you
now
have
the
exact
stack
I'm
talking
about
up
and
running
ready
for
you
and
you
can
start
sending
metrics
to
it
and
start
visualizing
it.
So
anybody
wants
to
play
or
test
with
this
after
the
call.
I
can
definitely
do
this
and
at
the
end,
we'll
be
giving
out
a
free
promo
code
on
packet.
That'll
get
you
one
of
our
small
servers
for
about
sixty
days
right.
B
So
it's
a
decent
amount
of
money
to
go
play
with
some
of
these
servers
right.
So
we
actually
jump
into
a
live
demo
now
and
kind
of
show
you
what
all
this
looks
like
and
I
don't
see
any
questions
yet.
So
if
you
guys
have
any
questions
so
far
right
make
sure
using
the
Q&A
Channel
I'm,
not
looking
at
the
chat
drop
any
of
your
questions
into
that
Q&A
box
and
I'd
be
happy
to
to
answer
them.
Okay,
all
right
live
demo.
B
Let's
do
it
so
the
first
thing
I'm
going
to
do
is
I'm
going
to
deploy
a
new.
A
new
software
stack
right.
So
this
is
our
our
software
stack.
We
have
chair,
foam
employ
and
the
question
I
just
got
a
question
in
the
chat.
Is
why
use
traffic
instead
of
sto?
And
the
short
answer
is
that
trait
that
gets
built
into
K
through?
Yes,
it
fit
all
of
our
needs
and
completely
worked,
so
we
didn't
decide
to
deploy
k3s
without
an
ingress
controller
and
replace
it
right.
B
It's
do
is
great,
but
traffic
work
good
for
our
our
use
case
cool.
So
let's
go
ahead
and
deploy
terraform
apply
and
we're
going
to
do
an
auto
approve
here.
So
this
thing
is
going
to
spin
up,
create
a
new
system
and
we're
going
to
flip
over
to
the
packet,
UI
and
kind
of
watch.
This
thing
happen
right.
So
here's
our
CN
CF
project
inside
a
packet
and
we
should
see
a
new
server
pop
in
here
in
just
a
second
there.
B
Let's
see
correctly
and
his
self
defending
since
there's
no
mention
of
security
yeah,
so
I
didn't
really
dive
into
the
security
aspect
of
this.
We
do
have
certain
on
so
you
can.
You
know
we
do
have
TLS
encryption
over
this
thing,
but
yeah
we
didn't
really
dive
into
protecting
this.
This
pipeline
right
there's
a
lot
of
things
that
you
can
do
you
know
it's
do
from
a
service
pressure.
B
Standpoint
would
be
great
really
we
inside
of
the
presentation
we
threw
in
the
the
cert
bot
and
all
of
that
to
keep
the
edge
kind
of
secure
and
released
SSL
encrypted,
but
yeah
there's
definitely
a
lot.
You
can
do
from
a
security
standpoint
to
keep
this
app
more
secure.
No
question
is
that
there,
as
well
as
the
emitter
we
chose
the
emitter
that
all
of
your
impute
et
data
is,
is
authenticated
as
well
great.
So
we
have
this
system
up
and
it's
it's
spinning
up.
B
So
we
have
another
environment,
that's
already
up
and
running
and
I
kind
of
want
to
drop
you
through.
All
of
all
of
these
things
right.
So
first
is
the
open,
fast
portal
right
so
jumping
into
open
fast.
You
could
see,
we
have
the
render
map
function.
We
have
our
database
reader
function.
We
have
our
database
insert
function.
We
also
have
our
in
qgt
publisher
function,
that's
bringing
the
data
from
emitter
and
shoving
that
into
the
database
or
into
the
queue
so
that
we
can
insert
it
into
the
database.
So
that's
great!
B
You
can
see
that
you
know.
Some
of
these
functions
have
been
called
the
m24
x
database
readers.
You
can
call
it
quite
a
bit
more
than
that
and
then
all
of
this
data
goes
into
Prometheus
and
can
then
be
visualized
right
here
right.
So
you
can
see,
we've
had
almost
72,000
total
requests
through
open
files
right,
and
so
we
allow
the
quick
visualization
you
get
this
for
free
using
open
files.
What's
your
function,
execution
rate,
how
many
replicas
do
you
have?
How
long
does
it
take
to
the
duration
of
this?
B
All
of
that,
and
we
have
another
question
in
the
chat:
have
you
put
your
remote
boot
edge
hosts
with
an
operating
system
right?
So
that's
what
packet
does?
The
entire
company
was
based
on,
let's
build
a
bare-metal
cloud,
and
so
there's
really
no
secret
sauce.
You
know
provisioning
a
physical
server
right.
You
need
to
connect
to
it
via
IP,
MI
and
power
it
on.
B
It's
then
going
to
get
a
DHCP
IP
address
and
in
the
DHCP
tags
it's
going
to
send
it
to
connect
to
a
pinke
server
right
in
our
case,
I
pick
C
at
that
point.
Everyone
knows
how
to
do
that
and
you
can
then
load
up.
You
know.
Red
Hat
has
instructions
I'm
going
to
has
instructions.
All
those
folks
have
instructions
on
using
an
image
from
them
and
using
a
kickstart
file
to
deploy
an
operating
system.
What
we've
really
done
is
put
a
lot
of
our
intelligence
in
to
that
boot.
B
Environment
that
comes
in
we've
basically
made
it
a
docker
eyes
debarment.
That
would
allow
you
to
make
a
lot
of
really
smart,
intelligent
decisions
at
that
point
to
deploy
the
server,
and
then
we
built
a
metadata
service
that
coincides
with
that,
so
that
you
can
use
things
like
cloud,
init
and
user
data
to
actually
turn
bare
metal
into
a
cloud
right.
So
that's
kind
of
the
secret
sauce
behind
packet.
What
we
do
and
that's
how
we
provision
those
servers
on
the
edge.
B
So
once
you
have
your
graph
on
up
and
running
hey,
we
have
a
lot
of
cool
stuff.
We
can
actually
jump
in
here
and
visualize
what
we
have
format
box
right.
So
you
can
see
here
we
have
North
West
Vegas.
We
have
a
warehouse.
We
have
a
warehouse
over
here
in
North
East
Vegas,
and
we
have
a
cluster
of
drones
here
on
top
of
the
hangar
right.
That's
where
all
those
guys
are.
So
if
we
wanted
to
send
those
drones
on
their
mission,
let's
go
ahead
and
kick
this
guy
off
right.
B
So
we're
going
to
kick
off
our
test
pipeline
to
deploy
these
probes
and
we're
gonna,
see
in
just
a
minute.
It
takes
a
minute
to
build
the
flight
plans
and
send
all
the
instructions
out,
but
these
drones
are
going
to
start
taking
their
flights
over
to
their
respective
warehouses
to
make
their
deliveries.
Ok,
so
that
takes
just
a
just
a
second,
so
we're
going
to
come
back
to
that.
B
B
B
It
does
not
okay,
so
that's
great,
so
this
is
supposed
to
be
showing
drones
flying
from
from
this
hangar
to
the
northwest
Vegas
deal,
and
then
from
this
hangar
to
the
Northeast,
you
can
enclose
the
warehouse
and
all
these
drones
will
come
back
home
or
you
can
grab
an
individual
drone
click
on
it.
You
can
see
the
battery
life
where
it's
going
its
speed
where
it's
coming
same
and
you
can
send
it
back
to
the
warehouse
if
you
needed
to
it's
unfortunate
that
this
isn't
working
so
it
says
they'll
return
to
hangar.
B
While
that's
going
on
we'll
check
on
it
in
a
minute,
this
is
all
the
visualization
data
from
when
the
drones
are
making
their
run
right.
So
this
is
what
Matt
box
our
meta
Base
does
for
you.
The
previous
deal
was
Matt
box
and
it
basically
shows
it
starts
building
graphs
for
you
that
are
pretty
smart
right,
so
this
is
one
that
we
didn't
have
to
really
really
mess
with,
and
it's
just
a
any
warnings
or
errors
that
drones
are
sending
out
and
where
they
were
when
those
errors
or
warnings
happen
right.
B
You
can
see
the
average
payload
vs.
battery
drain
right.
So
if
the
payload
is
much
higher
than
the
battery
drain-
and
they
you
know,
they
might
end
up
running
out
of
out
of
battery
life
before
they
can
make
their
your
delivery
right.
So
this
is
part
of
part
of
understanding,
understanding
these
and
we
that's
why
the
the
controller
is
a
bi-directional
communication
right,
so
it's
sending
information
again,
the
Maps
still
not
working,
and
so
we
can
actually
with
that.
With
that
data
we
can
make
that
quick,
analytics
and
say
hey.
B
This
drone
is
not
going
to
make
its
delivery,
because
it's
batteries
training
way
too
quickly.
Let's
bring
it
back
to
the
hangar
before
it
has
an
issue,
one
of
the
other
things
that
the
controller
does
is
say.
These
two
drones
are
on
a
collision
course.
Let's
avoid
that,
let's
move
them
out
of
the
way,
so
they
don't
collide
with
each
other.
Okay,
and
so
you,
you
get
all
of
that,
and
so
basically
comes
for
free
with
very
little
work
inside
of
meta
base
right.
So
you
can
see
all
of
this
pretty
cool
charting.
B
There's
a
few
other
things
that
you
can
dive
into
here
right.
You
can
go
directly
into
Postgres.
Look
at
the
drone
position
table.
Sorry,
I,
shouldn't
click
on
that.
There's
this
lightning
bolt
to
x-ray
this
table,
that's
something
that
they
call
and
so
there's
just
more
analytics
if
you're
building
on
the
fly
on
just
a
database
right,
so
you
can
start
seeing
the
drones
position
by
bearing
drones
position
by
battery
drain.
All
of
these
things
are
just
charged
that
they
they're
just
building
for
you
thinking.
This
might
be
useful.
B
I
see
some
some
trend,
data
here
and
they're,
putting
them
on
a
chart
in
an
automated
way
for
you,
so
pretty
cool
stuff
that
that
meta
Base
does,
and
you
can
see
that
this
environment
is
now
done.
We've
we've
spun
up
a
brand
new
environment.
If
I
jump
over
to
pack
it,
you
can
see
the
servers
online
and
let
me
cross
my
fingers
for
the
demo
gods.
Hey.
We
have
a
new,
a
new
map
rendered
for
that
new
endpoint.
B
B
Well,
I
want
to
do
too
much
of
this
live,
it
looks
like
I
might
be
having
an
issue
with
some
of
my
environment.
So
that's
great
it's
up
here,
though
so
I'm,
not
sure
why?
Oh
and
now
it's
not
great,
so
it
looks
like
I'm
having
an
issue.
We
can
figure
that
out
later,
I
would
like
to
go
back
to
any
questions
you
guys
have
and
back
to
the
slide
deck
here.
B
B
Basically,
the
end
of
the
demo
there
right,
so
what
we
do
want
to
do
is
for
anybody
else
to
try
this
out
and
we
might
need
to
do
a
couple.
Pull
requests
to
get
this
thing
up
and
running
is
go
over
to
bare
metal,
bare
metal,
slash,
IOT
that'll.
Take
you
to
that
same
github,
repo
that
I
was
showing
and
when
you
sign
up
for
your
packet
account
to
deploy
this.
B
If
you
use
promo
code,
curiosity
100,
it's
going
to
give
you
$100
and
free
cloud
credits
so
that
you
can
either
try
this
or
any
other
project
that
you're
working
on.
You
can
actually
spin
up
some
free
free
compute
credits
and
there's
some
free
servers
and
test
them
out
hundred
dollars
worth
and
do
your
thing.
So
that's
that's!
All
I
have
for
today
any
other
questions
go
ahead
and
throw
them
into
the
Q&A
window.
Yeah.
A
Thanks
Cody
the
great
presentation,
so
we
do
have
some
time
for
some
questions.
So
there's
a
Q&A
tab
at
the
bottom
of
your
screen
there
and
you
can
enter
your
questions
in
there.
I
see
one
question
or
more
statements
that
are
questions
like
demo
gods,
exclamation
point
so
since
that
came
up
multiple
times
during
the
the
talk
here.
Well,
people
think
of
real
questions.
What
what
are
the
traditional
sacrifices
that
you
make
to
the
demo
gods?
Cody.
B
B
A
B
So
that's
a
good
question
and
there's
a
lot
of
different
thoughts
out
there.
So,
in
my
opinion,
I
think
my
best
efforts
are
spent
higher
up
the
application
stack
than
managing
kubernetes
itself,
so
I
would
go
with
a
vendor
supported
model
right.
So
folks,
like
Rancher
folks,
like
platform
9,
anybody
else
in
the
communities,
ecosystem
and
kind
of
participating
I
would
go
with
those
guys
to
help
me
kind
of
manage
those
clusters
around
the
globe.
So
I
don't
have
to
build
a
huge
Operations
team
to
do
that.
I
think
a
different
question
might
be.
B
How
do
you
interconnect
those
clusters
together
and
how
do
you
allow
them
to
communicate
inside
of
kubernetes?
So
hto
is
a
great
option
for
a
service
mesh
and
they
now
have
the
ability
to
I
think
it's
called
from
Sto
gateways,
or
you
can
have
multiple
separate
clusters
that
are
then
you
can
then
map
pods
so
that
they
can
talk
to
each
other
across
through
that
SEO
gateway
and
a
chair
service
discovery
across
that
hashey
core
console
Connect
can
do
that
as
well
right,
so
they
have
a
great
option
there
to
do.
B
Multi
cluster
kubernetes
to
allow
your
services
from
both
of
them
to
talk
in
a
secure
fashion
and
then
a
new
project
that
Rancher
just
came
out
with
is
submariner,
which
is
really
cool
and
interesting.
I
like
it
a
lot
and
submariner
basically
creates
I,
can
set
tunnels
between
an
IPSec
match
between
one
to
many
clusters
and
allows
service
discovery
and
pod
every
across
all
of
them.
B
So
it's
a
pretty
cool
tech
out
there
to
help
you
interconnect
these
clusters
actually
doing
the
day-to-day
operations
and
doing
upgrades,
and
all
of
that
I'd
be
looking
for
a
two
Nettie's
control
plane,
which
there's
quite
a
few
of
available
out
there
and
the
rate
other
ones
free
paper
support.
That's.
B
B
A
B
Yeah,
so
so
k3s
isn't
what
really
cares
or
manages
the
AMPT
broke.
Our
QPR
in
PTT,
that's
more
of
a
plugin
to
open
files
and
to
be
honest,
I,
don't
know
for
sure
is
open.
Fast.
Has
an
amputee
broker
off
the
top
of
my
head.
We'd
have
to
Google
open
faz,
AMQP,
I'm
sure
it's
there.
I
do
know
for
sure
that,
like
another
server
list
framework,
that's
called
station
fissioned
at
I/o,
which
is
a
kubernetes
based
server
list
platform.
That's
totally
open
source
I
do
know
they
have
an
AMQP
broker
for
sure.
B
A
B
It
gives
you
a
much
more
grated
way
to
get
into
consuming
kubernetes,
where
you're,
really
just
caring
about
the
functions
that
you're
writing.
This
is
my
code
I'm,
going
to
write
that
code
I'm
going
to
deploy
to
open,
fast
and
open
the
path
is
going
to
figure
out
how
to
just
distribute
it.
For
me,
it's
going
to
give
me
an
ingress
point.
So
I
can
execute
that
code.
I
could
do
all
of
those
things
and
I
don't
need
to
figure
out
how
kubernetes
specifically
does
all
that,
for
you.
A
B
So
it
obviously
depends
on
the
distance
from
the
drone
to
the
tower
and
then
from
the
tower
to
the
server
right.
So
that's
that's.
The
big
thing
that
we're
that
packet
and
sprint
are
shoring
up
is
we're
putting
these
servers
as
close
to
the
tower
as
possible,
so
that
you
can
really
get
you
know
sub-millisecond
latency,
from
the
the
termination
of
the
tower
over
to
your
server.
B
Now
the
drones
transmitting
data
you're,
probably
dealing
with
a
couple
milliseconds
there
cube
depending
on
you
know,
are
they
a
mile
away
from
the
tower
or
five
miles
from
the
tower?
That's
gonna
change
things,
but
not
dramatically
so
round
trip
we're
definitely
talking.
You
know,
sub
five
milliseconds
right,
which
is
which
is
pretty
good
right
and
in
a
lot
of
cases,
your
sub
three
milliseconds.
B
A
Is
very
cool:
well
I
need
to
prep
my
scripts,
but
you
had
a
code
at
the
end
there
for
everyone
to
go
check
this
out
and
get
some
credits
on
packet.
I
love
stuff
like
this,
where
we
get
to
see
tech
kind
of
interact
with
the
real
world
and
I'm
actually
personally,
in
a
bookmark
this
code,
because
I'm
excited
about
the
the
arm
64
stuff
packet
has
available
for
me
to
tinker
with
so
I'll,
be
using
it
on
that.
A
So
with
that
we'll
be
closing
things
out
here,
so
great
Thank,
You
Cody
for
the
great
presentation
and
all
right.
That's
all
the
questions
we
have
time
for
today,
thanks
for
joining
us
today,
the
webinar,
recording
and
slides
will
be
on
later
today
on
the
CNC
F
website
and
we're
looking
forward
to
seeing
you
at
a
future
CN
CF
webinar
have
a
great
day
everyone.