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Description
Don’t miss out! Join us at our upcoming event: KubeCon + CloudNativeCon Europe 2023 in Amsterdam, The Netherlands from April 17-21. 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.
Edge Meets Kubernetes: Project Flotta - Jakub Dżon & Gloria Ciavarrini , Red Hat
Do you have a Raspberry Pi and want to learn about a cool way to use your devices and a Kubernetes cluster? During this talk Jakub and Gloria will introduce you to Project Flotta. They will demonstrate how to register your devices within a Kubernetes cluster and how to deploy containerized workloads. You can’t imagine how easy it is to access cameras or other sensors available on your device fleet, collect data from them and then transfer it from an edge device to a cluster using the Flotta Project (https://project-flotta.io/)! At the end of the presentation, you will be able to make your distributed collected data sets available in one central location. You will also learn how to monitor your devices using Flotta's built-in metrics and logs collection mechanisms, that will allow you to have good insight into how your workloads perform.
A
This
is
Project
Porta.
During
this
presentation,
we'll
show
you.
The
main
picture
of
the
project
quota
will
show
you
how
to
configure
your
hedge
devices
how
to
deploy
container
edit
workwood
on
the
edge
device
without
relying
on
the
kubernetes
scheduler
project
Plata.
Let
us
to
monitor
our
heads
of
devices
and
let
Holter
has
to
get
data
from
them.
We
can
also
ask
us
the
hardware
to
the
hardware
that
are
available
on
each
Edge
device,
I'd
like
to
give
you
a
quick
overview
of
the
project
water.
A
On
the
kubernetes
side,
the
Plata
project
is
composed
by
a
quarter
operator
and
the
flutter
hedge
API
The
Collector
operator,
is
a
kubernetes
kubernetes
operator
used
to
manage
the
workload
of
the
hedged
devices
via
kubernetes
API.
The
plot
operator
is
also
responsible
to
deploy
all
the
plotter
project.
Custom
resource
definition
such
as
Edge
device
or
hedgeboard
Clips
here
deep,
like
a
head
gpis,
is
an
HTTP
entry
point
that
handles
all
the
communication
between
the
devices
and
the
cluster
by
default.
A
B
B
Our
flat
operator
project
that
generates
in
a
script
that
contains
all
the
necessary
information
to
make
your
device
be
visible
for
our
cluster
component.
So
let's
have
a
look.
How
it
looks
in
practice
here,
on
the
left
hand,
side
you
can
see
my
repository
checked
out
with
the
flot
operator
and
the
make
file
I
mentioned
on
the
right
hand,
side
I'll
be
monitoring
all
the
edge
device
CRS
registered
with
our
cluster,
which
correspond
to
devices
registered
with
the
cluster
at
the
bottom.
B
There
is
the
command
prompt
on
the
edge
device
where
I'll
execute
the
installation
script
that's
generated
with
make
agent
install
scripts
Target
that
will
generate
installation
dnf
sh
after
the
file
is
transferred
to
the
device.
It
needs
to
be
executed
with
additional
arguments
like
IP
address,
of
your
HTTP
API
endpoint,
flutter,
API,
endpoint
and
Port.
It
listens
on
and
the
installation
will
take
quite
some
time
as
we
need
to
install
our
RPM
and
dependencies
like
node
exporter,
podman,
ansible
or
NF
tables.
B
When
the
installation
of
those
components
is
complete,
the
device
will
automatically
restart
and
after
successful
boot,
it
will
register
with
the
control
plane.
Here
you
can
see
in
the
CR
listed
and
let's
have
a
look
what's
inside,
that
CR
flutter
agent,
when
it's
registered.
It
sends
some
information
about
Hardware
configuration
of
the
device
like
in
this
case.
You
can
see
labels
describing
the
architecture
of
the
CPU
another
in
the
status
part
of
the
CR.
You
also
can
see
Hardware
information.
B
Whenever
a
configuration
is
specified
at
the
level
of
edge
device
set,
it
is
applied
to
all
devices
belonging
that
set
and
whatever
is
configured
at
the
level
of
that
device
is
overridden
with
configuration
coming
from
the
edge
device
set.
Conversely,
whenever
device
is
removed
from
a
device
set,
the
configuration
encountered
at
the
edge
device
CR
would
be
applied.
For
example,
we
have
Edge
device
set
named
demoset
which
defines
configuration
for
metrics.
In
this
case
we
said
system
metrics,
Gathering
interval
to
60
seconds
and
at
the
same
time
we
disable
it.
B
If
you
want
to
apply
that
configuration
to
a
nudge
device,
we
need
to
label
it
with
flota
member
of
label,
with
the
value
corresponding
to
the
name
of
the
edge
device
set.
We
want
the
device
to
belong
to
like
in
this
case
we
put
demo
Dash,
set
value
to
the
label
and
the
device
would
belong
to
the
mod
set
Edge
device
set.
B
B
I've
got
three
Edge
devices
connected
to
my
cluster
and
at
the
bottom
you
can
see
the
respective
configurations
on
the
devices
when
I
apply,
changes
and
configurations.
Those
listings
will
change.
I've
got
definition
of
a
device
set
called
demo
Dash
set.
The
name
is
important
because
we
need
to
make
a
association
between
device
and
device
set,
the
creation
of
the
device
that
doesn't
change
anything
because
there
is
no
connection
between
an
end
of
the
device
and
that
device
set
to
make
that
connection.
B
If
we
remove
the
label
from
one
of
the
devices
it
will
revert
its
configure
on
device
configuration
to
whatever
is
specified
at
the
level
of
edge
device
in
the
cluster.
If
you
remove
the
device
set,
the
configuration
will
be
reverted
on
all
of
the
devices
and
they
will
go
back
to
their
default
configuration
in
flutter
workload.
Software
you
want
to
run
on
your
Edge.
Devices
needs
to
be
wrapped
as
a
container
image,
and
we
use
podman
to
execute
your
images
on
your
devices.
B
So
you
can
provide
information
what
you
want
to
run,
how
it
should
be
configured
on
the
device
using
standard,
kubernetes
pod
specification
that
is
embedded
into
our
custom
resource,
describing
your
workload
and
because
our
workloads
are
described
with
yamo.
You
can
use
your
standard,
CI
CD
pipelines
that
you
use
to
deploy
your
workloads
in
cluster
to
deploy
that
on
the
edge.
B
A
B
After
applying
the
workload
we
would
expect.
The
work
was
to
be
shown
in
the
status
on
the
bottom
screen,
but
they
aren't
because
the
devices
are
not
labeled.
Yet
after
labeling
the
devices
the
status
of
the
workloads
are
shown
and
they
would
transition
from
deploying
to
created
to
running
in
some
time
now
all
the
workers
are
running
and
we
can
try
to
connect
to
nginx
server
on
one
of
them.
We
will
use
links
and
port
8080
and
we
expect
default
nginx
website
to
be
shown,
which
is
there
and
we.
B
B
A
Now
we
know
what
an
edge
device
here
is,
how
to
deploy
a
workloads,
but
would
it
be
useful
to
to
retrieve
with
some
information
probably
had
supplies
but
flutter
give
us
a
simple
and
effective
way
to
monitor
metrics
locally
in
this
device
and
to
export
them
periodically
to
your
monster.
The
metrics
collected
will
be
then
saved
on
a
Time
series
degree
like
Thomas.
A
A
A
It
is
also
possible
to
disable
completely
the
metrics
collection,
and
in
this
case,
all
the
infrastructure
relating
to
metrics
acquisition
will
be
turned
off
included.
Prometheus
Network
support.
So
let's
start
to
Computing
our
metrics
collection.
This
can
be
done,
including
included
subsection
in
the
edge
devices
you
are
so
in
the
green
box.
There
is
a
metric
section
and
we
Define
the
interval
of
oxygen
equals
to
30
seconds.
The
default
is
60..
A
We
can
also
configure
the
hello
list
so
if
we
want
to
monitor
just
a
subset
among
the
whole
available
metrics,
we
can
just
create
first
of
all,
a
config
map
and
name
only
the
metrics.
We
are
interested
in
and
then
refer
to
this
config
mark
inside
the
edge
device
CR,
including
allow
list
subsection
in
the
spec,
and
if
you
want,
we
want
to
restore
the
population
to
the
the
fault.
A
It's
super
easy.
We
just
need
to
remove
the
Netflix
subsection
in
the
edge
device
CR,
so
press
it
flat
down
assume
that
the
device
can
be
openly
tight
and
they
can
found
can
be
found
anywhere
on
the
earth.
So
that's
why
project
doesn't
assume
that
the
device
are
always
connected.
If
they
are
battery
powered,
the
battery
could
die
and
the
connection
quality
may
be
poor
or
maybe
there
is
no
connectivity
at
all.
A
So,
let's
see
what
happened
in
action
in
the
next
video
in
this
demo,
we
will
see
what
happens
when
devices
have
connection
problems.
We
observe
our
cluster
from
agrapana
dashboard.
We
can
monitor
the
number
of
other
objects
head
devices
in
Edge
procludes
and
the
devices
that
have
registered
at
this
time,
Hollywood
device
has
registered
I
have
to
warn
you
in
this
demonicle
acrylic
stitching
cluster.
In
fact,
two
more
devices
are
already
registered.
A
A
Another
picture
of
the
offer
by
project
worker
is
to
run
antibody
on
the
device.
First,
we
need
to
Define
an
edge
compute
CR
and
that
configure
allows
to
specify
some
configuration
so
potentially
not
only
multiple
playbooks
to
apply
to
the
device.
We
also
need
to
assign
a
label
to
the
edge
device.
Indeed,
as
you
are,
and
to
specify
on
which
device
we
want
to
run
the
article
code.
So
to
be
honest,
there
is
things
are
a
little
bit
like
more
complicated
than
under
the
hood.
A
So,
as
the
flat
operator
receivd
has
come
to
PCR,
so
in
this
case
h
copy
one
it
generates
for
each
device
with
a
corresponding
label
a
new
CR
called
it
Playbook
execution.
This
CR
allows
us
to
link
its
anti-book
Playbook
execution,
to
advise
and
to
monitor
its
speeds
and
this
example.
We
create
the
edge
config
naming
Edge
complete
one
and
we
assign
the
label
the
corresponding
label
to
device
one
and
device.
Three
plot
operators
then
create
two
Playbook
execution,
CR
one
for
the
device
one
and
one
for
data.
B
A
A
A
In
a
moments
the
status
of
the
Playbook
will
change
from
deploying
to
execute
it
in
the
meanwhile,
let's
see
that
the
Playbook
execution
has
been
created
to
link
the
edge
device,
one
to
the
edge
conflict
team,
one
the
status
has
changed
into
successfully
completed.
So
let's
check
the
file
this
here.
It
is
and
look
at
the
contacts.
B
A
A
A
B
Further
processing,
in
this
case
in
case
of
flota,
we
use
S3
API
as
the
target
endpoint
that
is
used
to
upload
the
files
it
doesn't
have
to
be
AWS
S3
bucket.
It
can
be
any
service
providing
S3
API
whenever
files
are
created
in
a
specified
directory
on
the
edge
device.
Flutter
agent
detects
that
and
uploads
them
into
the
remote
endpoint
to
configure
that
behavior,
a
user
needs
to
provide
data
section
of
this
Edge
workload.
Specification
like
in
this
case
we
have
Source
directory
listed,
which
corresponds
to
in
container
export
Source
directory.
B
B
To
instruct
floater
agent
how
to
access
the
remote
storage,
a
user
needs
to
provide
storage
section
of
the
edge
device
manifest
where
there
is
S3
dedicated
configuration
which
references
config
map
with
information
about
the
bucket
and
secret,
which
provides
credentials
to
access
setup
packet
like
here.
On
the
left
hand
side
you
can
see
config
Map
listing
different
parameters
of
the
bucket
or
the
endpoint,
where
we
want
to
upload
the
files
and,
on
the
right
hand,
side.
You
can
see
the
AWS
credentials
that
should
be
used
for
accessing
the
remote
storage.
B
B
In
this
case,
we
map
that
depth
video
Zero
path
to
exactly
the
same
path
inside
the
container
running
the
workload.
This
way
user
will
have
access
to
that
on-host
device
to,
for
example,
take
photos
or
record
videos
to
make
things
simpler.
We
instruct
flutter
to
run
the
the
container
in
privileged
mode
for
the
purpose
of
this
presentation.
I
have
prepared
python
HTTP
server
listening.
A
B
A
A
B
And
let
me
show
you
how
its
descriptor
look
like.
You
should
see
that
we
have
already
different
architecture:
Arc
64
report,
as
reported
by
the
agent
and
I
label,
the
device
for
scheduling
with
app
snapshots
label
I,
also
configured
S3
storage
by
referring
config
map
and
secret
with
bucket
information
credentials.
B
Let's
see
the
workload
that
we're
gonna
use,
there's
the
app
snapshots
label
for
scheduling
and
the
container
in
the
pot
uses
a
Dev
video
device
to
take
pictures
and
set.
The
video
file
is
mapped
from
the
host
device.
The
video
Zero
and
the
workload
exposes
8080
part
on
the
device
to
allow
users
to
trigger
snapshot
taken,
and
the
snapshots
will
be
uploaded
from
Target
directory
to
snapshots
subdirectory
on
the
S3
bucket.