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hello hello welcome to solving with AWS
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I'm Rob your host joined today with a
man elastic searching for the meaning of
life Tom media's cloud is the solution
of the day how to streamline automate
and set up service and to end ingest
workflows to manage large video content
migrate your assets and associated
metadata to the cloud nice ok let's get
into how media to cloud works so Tom
talked to me about media to cloud
certainly this is the landing page for
the solution like all our solutions we
have a detailed deployment guide
CloudFormation template so you can spin
it up in your account with a couple of
clicks and the source code is available
on github if you want to take it and run
with it and customize it yourself that's
awesome let's see the architecture
diagram certainly so a lot of moving
parts here but it really all starts with
that uploading your video content into
s3 so I've got my thousand videos up my
dog's I could push them into s3 and it
kicks this on it certainly does every
time a new video is pushed up uploaded
into s3 that's going to trigger our
workflow and there's a couple of things
that we do on the first step the first
thing is we have a ingest step function
that's a do a state machine with backed
by a dubious lambda and what we're going
to do there is we're going to create an
md5 checksum for the video file so you
have details on the exact size of it and
we're also going to run media info and
that's going to extract some meaningful
metadata about our file
are you actually running this on the
original file so this is all being run
on the original file for the rest of the
workflow what that's where media convert
is coming in and we're going to create a
proxy version of the video that we can
then use later on what do you mean by a
proxy version so let's imagine if you're
moving a big archive over your original
masters we're talking about videos big
size videos you know very large video
formats we don't want to be passing that
through all of the rest of the workflow
into the machine learning services
that's just going to create extra cost
so being cost efficient and processing
efficient on these eggs
so we're going to create a compressed
version an mp4 version of the content
still with all the same audio tracks
resolutions and information that we need
to work in the workflow but not that
huge original video file going through
so now we have this proxy video what
analytics are run on it the the next
step is our analytics state machine
what's really cool about this solution
is that is actually the media analysis
solution that has been plugged into
media to cloud so we're using our own
solution within a solution yeah it's a
meta solution there you go
got it that is a solution that will
ingest your video take that and pass it
to services like recognition and
transcribe and comprehend to get
meaningful information back about that
content so some AI + ml services that
were running we are but there is no
upfront need v no deep understanding and
machine learning to use this solution
it's all comes out of the box really do
that's great it's built-in built-in so
final step is that we have another
workflow that's going to do some
labeling and some indexing for us and
that's using sage maker ground truth so
that's where the customer can come in
and actually identify people within the
video content and then send that
information to ground truth so that we
can get some further indexing going on
alright so now we have all this great
analytics where is it stored and what do
I do with it
certainly so the information is stored
in a combination of dynamodb that's
where our metadata RMD check file and
just the general details about the
content is stored and then all of the
information from our machine learning
services is going to be stored in s3
alongside that proxy file ok is it
indexed somewhere Amazon elastic search
is what we're using to index that
information so that's then fronted by an
API gateway so we have an API that you
can query to get information about back
about all your content ok can you show
me UX that comes with us yeah we have a
demo console that is deployed as part of
the solution I've uploaded three videos
here so if we drill down and take a
closer look at one of these files we've
got Andy at reinvent hey Andy how's he
doing
we have the general information about
the file we have
technical metadata that we got for media
info and then we've got all of the
information that we've gathered from
recognition from comprehending
transcribe so these are those three
analytical buckets that we saw on the
architecture diagram itself that's right
and then the last piece is I was
mentioning with Amazon ground truth we
have the ability to create snapshots
where we can focus in on a particular
face to find who this person is and then
send that off to ground truth to get
some additional indexing that's pretty
awesome so really able to glean a lot of
valuable information around the media
you're getting from your different files
correct so it's not just lift and shift
we're actually getting all of that
information as we're uploading content
into the cloud that's awesome thanks for
talking about media to cloud Tom you're
welcome thanks for joining and thank you
Tom for that technical deep dive on
media to cloud the media to cloud AWS
solution really expedites customers
ability to manage their media content it
also adds analytics through AI nml go
check out media to cloud and other
solutions on our AWS solutions website
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