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Description
Don’t miss out! Join us at our upcoming event: KubeCon + CloudNativeCon North America 2021 in Los Angeles, CA from October 12-15. Learn more at https://kubecon.io The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects.
Automating Your Home with K3s and Home Assistant - Eddie Zaneski, Amazon Web Services & Jeff Billimek, The Home Depot
Hey Google, turn off all the lights. Hey Siri, set the thermostat to low. Alexa, restart the nginx deployment. You may have dreamt (or had nightmares) about automating your home and connecting all things smart together. You probably haven't longed for doing all of that on top of Kubernetes. In this session you'll learn why you should and the benefits of having a homelab running Kubernetes. With everyone spending more time at home there has never been a better time to grab an old PC or a few Raspberry Pi's and install K8s. Eddie and Jeff will share their journeys of deploying Home Assistant, open source home automation software, on top of K3s, a lightweight K8s distribution. They'll cover unique solutions like building Device Plugins and using Node Feature Discovery to use external USB antennas for wireless smart home protocols. Ending with tying all of it together with Helm and using Flux for CICD. If you're looking for a personal project to learn Kubernetes this session is for you.
A
B
A
Have
one
goal
today
and
that's
to
inspire
you
to
start
a
home
lab
when
a
lot
of
folks
want
to
learn,
kubernetes
or
a
lot
of
the
cloud
native
technologies
that
are
out
there?
They
don't
really
have
a
personal
project
to
get
started
with
it's
much
easier
to
throw
yourself
in
and
really
learn
all
the
things
when
you're
actually
managing
something,
and
so
we
don't
obviously
want
you
to
run
and
play
in
your
production
environment.
If
you
can
help
it,
and
so
that's
where
the
software
we're
going
to
show
today
really
shines.
B
Home
labs
can
be
very
addicting
just
so
you
know
before
long.
You
might
find
yourself
looking
for
used
servers
on
ebay
late
at
night,
but
but
all
seriousness
home
labs
are
a
really
safe
way
to
experiment
with
new
technologies,
either
for
your
own
personal
use,
or
maybe
something
related
to
your
your
job
as.
A
B
Starters,
it's
a
really
great
way
to
learn.
Kubernetes
kubernetes
provides
really
great
features
for
like
resiliency
and
redundancy
like,
for
example,
just
the
other
day.
This
week
my
power
went
out
for
about
three
hours.
The
ups
has
all
failed,
and
so
everything
turned
off
and
when
the
power
finally
came
back
on
and
everything
powered
back
up,
kubernetes
basically
ensured
that
everything
was
running
without
incident
like
everything
just
came
back
automatically,
thanks
to
the
kubernetes
scheduler
and.
A
Kubernetes,
just
kind
of
gives
you
a
place
to
put
things,
maybe
that
one-off
cron
job
that
you
have
running
that
alerts
you
when
there's
a
90s
dance
party
at
the
venue
around
your
apartment,
like
I
used
to
once
your
cluster
gets
full.
You
can
always
just
you
know,
grab
another
raspberry
pi,
for
example,
toss
it
in
and
grow
it
out.
One.
B
A
A
You
know
here's
my
thermostats
that
I
can
control
a
couple
security
sensors
like
if
the
windows
opened
or
closed,
there's
that
cam
feed
from
my
ring
doorbell.
I
can
trigger
off
nice
things
like.
It
knows
my
wife
and
I
are
home
because
our
phones
are
connected
to
the
wi-fi
here.
You
can
take
a
look
at
some
of
the
integrations
that
I
have
installed.
A
Here's
my
chromecasts,
my
robot
vacuum
thermostats
doorbells,
all
the
different
bits
that
plug
together
along
with
a
huge
list
of
other
ones,
that
I
can
install
what
ties
all
these
things
together
are
automations,
and
so
here's
a
quick,
simple
one.
This
one
turns
the
lights
on
in
my
kitchen
after
the
sun
goes
down,
so
you
can
see
it's
got
a
trigger
for
sun
20
minutes
before
sunset
checks.
If
the
lights
are
currently
off
and
then
it
turns
them
on
right-
and
this
is
of
course
represented
via
yaml-
which
we
all
love.
B
In
this
automation,
I'm
going
to
show
how
the
motion
sensor
and
my
alarm
system
will
trigger
the
lights
in
the
hallway
to
automatically
turn
on
when
it
detects
motion.
Everyone
in
my
family
loves
this
automation
because
the
lights
just
magically
turn
on
and
off
when
they,
when
they're
walking
through
the
hallway.
A
So
one
of
my
favorite
home
automations
that
I
have
is
these
smart
z-wave
light
switches,
and
so
they
work
like
a
regular
light,
switch
they're
dimmable.
You
know
I
can
hold
it
up
or
down,
but
one
of
my
favorite
bits
about
it
is
that,
depending
on
how
many
times
I
push
the
button,
it
fires
off
a
different
event,
and
so,
for
example,
we
have
this
night
light
here,
and
so,
if
you
tap
twice,
it
actually
controls
the
night
light.
Instead
of
the
regular
lights.
B
I've
set
this
up
to
kind
of
demonstrate
how
the
different
components
running
in
kubernetes
kind
of
work
together
or
in
particular,
the
very
specific
person
object,
detection
feature
of
one
of
the
workloads
that
I'm
running
called
frigate.
It's
running
as
a
helm
chart.
That's
the
thing.
That's
using
the
coral
tpu
usb
device,
the
tensorflow
processing
unit
and
basically
its
whole
job,
is
to
offload
a
small
video
stream
to
that
device
to
apply
a
machine
learning
model.
B
In
this
particular
case,
it's
object,
detection,
and
so
what
we're
about
to
see
is
my
assistant,
my
daughter,
she's,
going
to
walk
by
and
we'll
see
that
frigate
detects
her
as
a
as
a
person.
Here
we
go
and
it's
going
to
draw
a
box
around
her
and
when
the
box
turns
blue,
that
means
it
detected
basically
person
and
if
you
look
below,
we
see
an
event
fired,
it
showed
they
detected
a
person
and
so
now
anything
subscribing
to
that
can
act
appropriately.
B
A
Let's
start
by
talking
about
hardware
right,
the
best
hardware
that
you
can
possibly
run
in
your
home
lab
is
what
you
already
have.
You
know,
maybe
that
old
pc.
Maybe
you
bought
a
raspberry
pi
three
years
ago
and
it's
still
sitting
in
the
box,
because
you
don't
know
what
to
do
with
it.
You
know
I'm
running
a
four
raspberry
pi
cluster.
B
I'm
running
a
a
collection
of
pc
and
raspberry
pi
devices,
they're
all
different
types
of
compute
devices.
I
have
an
old
laptop.
I
have
an
old
desktop.
I
have
a
couple
of
things.
I
got
off
of
ebay,
just
a
bunch
of
different
little
things,
plus
three
raspberry
pi's.
One
of
them
is
connected
via
usb
to
my
alarm
panel
device.
So
I
can
arm
and
disarm
the
alarm
and
get
alerts
when
windows
or
doors
are
open
or
there's
motion,
or
things
like
that
and.
A
If
you
currently
don't
have
any
hardware
laying
around
we'd
recommend,
just
you
know,
grabbing
a
raspberry
pi
or
two,
you
really
don't
need
much
more
than
that
to
get
started.
You
can
obviously
start
with
one,
but
when
it
comes
to
kubernetes,
having
multiple
nodes
really
gives
you
a
much
better
experience
and.
B
If
you're
running
raspberry
pi's
the
processors
they
run,
aren't
typical
intel
processors
they're
based
on
arm,
which
is
gaining
a
lot
more
popularity
now,
and
so,
when
you're
going
to
run
like
arm
compute
modules
or
compute
devices
in
your
kubernetes
cluster,
it's
going
to
be
important
to
look
for
container
images
that
support
arm.
Typically,
things
that
have
like
multi-arch
support
are
going
to
are
going
to
fall
in
that
category.
A
Arms
really
come
a
long
way
hasn't
it.
You
know
from
back
in
the
day
when
we
were
running
docker
swarm
on
some
pies,
and
I
just
remember
trying
to
install
redis
for
the
first
time
and
there
was
no
arm
image
for
redis
yet
and
I
was
like
well,
I
guess
I'm
returning
all
this
stuff.
Next,
let's
talk
about
software,
we'll
start
with
k3s,
which
is
going
to
be
the
backbone
of
your
home
lab
kubernetes
cluster
k3s
is
a
cncf
project
originally
started
by
the
folks
over
at
rancher.
A
It
is
a
lightweight
kubernetes
distribution,
which
basically
means
they've,
stripped
out
a
bunch
of
cloud
provider,
specific
things
that
you're
really
not
going
to
need
it's
packaged
as
a
single
binary
that
holds
all
of
the
things,
including
your
docker
container,
runtime
ingress
controller.
Basically,
everything
you
need
to
get
started
is
right
in
the
single
binary.
A
It
runs
great
on
a
single
node
or
many.
It
has
a
really
awesome
and
easy,
install
and
upgrade
experience
basically
you're,
just
replacing
that
single
binary
the
control
plane
uses
either
sqlite
by
default
or
xcd.
If
you
want
to
switch
to
a
high
availability
as
far
as
installing
k3s,
we
recommend
checking
out
ketchup
by
alex
ellis
quick,
shout
out
to
alex
he's,
got
tons
of
content
out
there
about
kubernetes,
k3s
and
raspberry
pi,
so
be
sure
to
check
him
out.
But
ketchup
is
a
very
simple
installer
for
k3s.
B
Helm
is
quite
useful
because
it
provides
an
easy
way
to
install
a
workload
in
sets
and
values
that
are
that
are
pertinent
to
that
workload.
Without
dealing
with
a
ton
of
yaml.
It
allows
for
easy
upgrades
and
rollbacks
and
there's
a
huge
community,
and
I
guess,
ecosystem
of
helm,
charts
that
have
already
been
made
that
you
can
reference
pretty
much
anything
that
you
think
you
want
to
run
in
kubernetes
probably
have
already
been
packaged
up
as
a
home
chart
when
using
helm.
B
There's
lots
of
easy
ways
to
find
and
discover
helm
charts
that
you
want
to
install
you
can
do
a
google
search
for
the
thing
you're
interested
in
plus,
you
know
helm.
You
can
search
on
github,
there's
also
a
really
great
site
called
artifact
hub,
which
has
thousands
of
helm,
charts
referenced
there
and,
specifically
for
home
use.
There's
a
really
great
community
called
kates
at
home
that
have
over
100
helm,
charts
in
their
catalog.
B
B
So
I'm
basically
in
turning
on
ingress,
I'm
sending
a
hostname
for
it
and
I'm
setting
the
ingress
path
default
and
then
I'm
turning
on
persistence.
So
the
settings
that
I
make
will
will
live
beyond
like
restarts
of
the
pod
and
then
I'm
referencing,
the
chart
name
in
this
case.
It's
the
home
assistant
chart
at
the
case
at
home,
home
repository,
and
so
when
I
run
this,
it
installs
the
chart
it
installed
fairly
quickly.
You
can
see
now
the
pod
is
there
and
is
booting
up
in
just
a
few
seconds.
B
It
should
be
ready
to
go.
It's
play
it's
doing
whatever
like
startup
probes
or
readiness
probes
that
are
necessary
for
it
to
be
there,
and
now
it's
running
and
ready.
So
I'm
going
to
switch
to
a
browser
and
I'm
going
to
navigate
to
that
ingress,
url
that
I
just
set
and
I'm
at
the
basically
the
home
assistant
like
setup
page
and
I'm
ready
to
go.
A
A
Mqtt
is
just
the
message
broker
that
we
use
for
most
of
the
iot
things
and
so
z-wave
to
mqtt,
really
just
kind
of
keeps
track
of
all
of
my
z-wave
devices.
This
is
where
I
would
come
to
add
a
new
device
to
my
network.
It's
a
process
called
inclusion,
and
so
once
I
start
this
up,
it
would
pair
and
depend
on
that
usb
device
to
connect.
It
there's
also
the
same
thing
for
zigbee.
A
A
That's
running
inside
of
my
cluster,
it's
an
eclipse
project
by
the
name
of
mosquito,
and
you
can
see
here
a
bunch
of
different
topics
that
are
being
subscribed
and
published
to,
and
this
is
really
the
heart
of
how
that
smart
home
communication
goes
between
the
different
applications.
So
again,
your
cluster
is
continuously
passing
messages
amongst
itself.
A
B
Even
though
you
may
have
redundancy
with
your
compute
devices
and
your
storage
in
some
cases,
there's
still
times,
especially
for
home
automation,
where
you
are
tied
to
a
single
physical
device,
but
basically,
if
the
device
that
you
have
your
your
usb
device
connected
to
goes
down.
That's
a
problem,
and
so
one.
B
That
is,
I'm
making
use
of
a
kubernetes
sig
project
called
node
feature
discovery
as
well
as
the
scheduler,
and
so
what
that,
what
that
means
is,
I
have
no
teacher
discovery
configured
to
label
dynamically
label,
the
node
that
a
usb
device
is
connected
to
with
a
certain
label
saying
this
device
is
on
this
node
and
then
I
I
schedule
the
pods
or
the
workloads
that
require
those
devices.
So,
for
example,
z-wave
to
mqtt
needs
to
be
able
to
talk
to
the
z-wave
radio.
B
B
But
if
I,
if
I
unplug
it
and
I
plug
it
somewhere
else,
node
feature
discovery
will
remove
the
label
from
the
node
that
it's
no
longer
connected
to
and
it
will
apply
the
label
to
the
nude
node
that
it's
connected
to
and
then
the
scheduler
will
eject
the
pods
if
they're
currently
running
on
a
node
that
does
not
have
the
required
label
and
then
kubernetes
scheduler
will
of
course
schedule
them
back
on
the
proper
node.
So
this
gives
the
kubernetes,
like
native
scheduling,
way,
to
handle
movement
of
devices.
B
So
if
I,
if
I
have
a
problem,
say
like
with
this
laptop
or
or
any
device
that
I
have
any
node
that
I
have
a
physical
device
connected
to
that,
I
need
to
still
be
able
to
use.
I
simply
just
plug
it
into
a
new
device
or
new
node
and
kubernetes
will
handle
the
rest
for
me
automatically,
which
is
which
is
really
handy.
This
is
what
happens
behind
the
scenes
in
kubernetes
when
a
device
is
moved
from
one
node
to
the
other
in
this
particular
terminal
window.
B
B
B
The
node
called
that,
and
so
I
fully
expect
that
node
to
get
that
label
and
there
we
go.
It
just
showed
up
now
it's
on
k3se
and
when
the
descheduler
loop
runs,
it
detects
that
it
doesn't
doesn't
fit
on
that
node
anymore,
and
so
it
ejects
it
and
then
it's
going
to
basically
be
rescheduled
by
kubernetes
onto
the
appropriate
node.
That
has
a
label
which
in
this
case
case,
is
key
3se
in
the
bottom.
B
A
So
here
I
could
see
my
tv
usage.
That's
broken
out
by
different
tvs
in
my
house,
so
here
we
can
keep
track
of
how
much
time
we're
watching
tv
pretty
straightforward,
prometheus
query
if
you're
not
familiar
with
what
they
look
like
right,
same
thing,
with
our
lights,
we
can
map
how
long
we
leave
the
lights
on.
I
can
punch
this
out
to
look
the
past
24
hours.
B
B
So,
like
I
reference
the
image
which
also
gets
updated
when
there's
a
new
new
version,
I'm
sending
things
like
environment
variables,
ingress
settings,
service,
settings
storage,
for
like
persisting
the
configuration,
I'm
annotating,
the
pods
for
doing
backups
to
valero,
for
example,
and
then
I
also
have
this
add-on
called
code
server,
which
is
vs
code,
but
server
based.
It's
actually
a
sidecar
running
along
with
home
assistant.
So
I
can.
I
can
edit
the
home
assistant
configuration
files
directly
through
vs
code
and
persist
into
github.
B
When
I
make
changes
to
the
repo,
if
I
were,
for
example,
to
change
the
version
of
the
home
assistant
image,
that's
running
git
ops
will
pick
it
up.
Well,
flux
will
pick
it
up.
It'll
it'll,
detect
a
change
in
the
repo
it'll,
then
notice
a
change
to
the
the
helm
chart
like
values,
and
it
will
apply
that
and
then
the
workload
will
basically
get
restarted
with
the
new
value.
B
Do
a
lot
of
automation
of
systems
and
so
I'm
very
much
a
fan
of
automating
as
much
as
possible.
So
in
my
particular
case
in
my
home
lab
and
my
kubernetes
home
lab,
I'm
running
ubuntu
server
on
all
the
nodes
and
out
of
the
box.
Ubuntu
server
is
configured
to
automatically
download
and
install
security
updates
and
if
a
particular
update
or
cve
that
was
installed
requires
a
reboot.
Ubuntu
will
will
signal
that
by
creating
a
file
on
the
file
system,
and
so
I
run
a
kubernetes
workload
called
cured,
k-u-r-e-d
and.
B
B
Another
is
for
kubernetes
upgrades
themselves,
but
themselves
I
run
k3s
and
rancher
has
a
tool
called
system
upgrade
controller,
and
what
that
does?
Is
it
monitors
for
a
new
version
of
kubernetes
or,
more
specifically,
a
new
version
of
k3s
and
when
it
detects
there's
a
version
and
it
meets
the
criteria
to
be
installed,
it
will
train
the
nodes,
coordinate
them,
upgrade
the
version
of
kubernetes
on
that
node
and
then
uncord
them,
and
it
does
that
one
at
a
time
as
needed
for
both
the
cured
solution
and
the
system
upgrade
controller
solution.
B
I
think
I
have
them
configured
to
only
run
like
at
night,
like
between
1
am
and
5
am
so.
When
I
wake
up
the
next
morning,
I
might
see
like
in
my
like,
monitor
or
whatever
that
some
of
the
nose
rebooted
I'm
none
the
wiser,
because
everything
just
magically
works
and
I
never
have
to
worry
about
keeping
my
stuff
up
to
date.
Lastly,
for
helm,
charts
and
docker
image
versions,
if
they're
senver,
I
make
use
of
a
github
tool
called
renovate,
it's
super
super
awesome.
B
Basically,
all
of
my
helm
charts.
If
there's
a
new
version
of
the
chart
available,
it
will
open
a
pull
request
on
my
git
ops,
repo,
letting
me
know,
there's
a
new
version
of
the
helm
chart
and
then
I
can
merge
the
pull
request
to
automatically
install
the
new
home
chart
similar
for
new
versions
of
docker
containers
that
compose
the
workloads
that
I'm
running.
B
If
maybe
the
helm
chart
didn't,
you
know
have
that
update
or
whatever
and
there's
lots
of
configurations
you
can
do
and
rules
to
guard
how
renovate
works
like,
for
example,
I
think
I've
run
plex
and
I
have
it
set
up
where
during
the
evening,
if
there's
a
new
version
of
plex,
it's
automatically
going
to
install
it
because
they
barely
have
breaking
changes.
Okay,
so
for
lessons
learned,
some
things
that
we've
we've
discovered
as
we've
been
going
through
this
journey
is
a
few
different
things
here.
B
One
is
that
if
you're
going
to
run
helm,
charts
or
applications
that
have
custom
resource
definitions
or
crds,
it's
going
to
be
important
to
note
that,
while
helm
can
install
crds,
initially
there's
currently
an
issue
with
how
helm
deals
with
upgrades
to
home,
charts
and
changes,
the
crds,
it
basically
does
not
upgrade
the
crds
after
they're,
initially
installed,
and
so
you'll
most
likely
want
to
handle
your
crd
installation
out
of
band
of
your
helm.
Chart
that
way,
you'll
be
able
to
maintain
the
lifecycle
crds
much
easier
and
avoid
all
those
problems.
A
K3S
has
its
own
local
provisioner,
that's
built
in,
so
it
can
kind
of
like
provision
local,
you
know
disks
the
problem
with
that
is
it's
not
distributed
or
highly
available,
so
the
pod
actually
gets
locked
to
only
run
on
that
node,
because
that's
where
the
data
is,
if
you
want
to
persist
that
data,
so
we
recommend
using
something
like
rook
or
longhorn
the
process
to
migrate.
After
the
fact
is,
basically,
you
have
to
spin
up
a
you
know.
A
blank
copy
pod
attach
the
volume
do
like
a
cube
control.
A
B
And
kind
of
to
that
note
a
little
bit
is
you
will
most
likely
experience
some
sort
of
failure
or
setback,
which
is
perfectly
fine.
It's
your
opportunity
to
learn,
but
it's
good
to
have.
I
guess
a
plan
in
place
to
to
anticipate
that
failure
and
have
a
good
recovery
idea.
You
may
need
to
tear
down
your
cluster
and
recreate
it,
and
so
keep
that
in
mind
as
you
go
through
this
so.
A
B
Even
though
arm
support
is
getting
much
better,
there
still
are
a
number
of
workloads
that
don't
have
arm
support,
and
so,
if
you're,
if
you're
choosing
to
run
a
cluster,
that's
mixed
architecture.
So,
for
example,
a
mixture
of
intel
and
arm
based
hosts.
You
you
one
way
to
handle
that
that
mix
is
to
taint
your
arm
nodes
with
with
a
some
sort
of
label
to
say
this.
This
can't
schedule
things
and
then
add
tolerations
as
needed
for
the
workloads
that
you
know
can
support
mixed
arch.
That'll.