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Welcome back to BackSpace Academy. In
this lab we're going to be creating a NodeJS

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application using the serverless
application model or SAM for short.

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Now the AWS documentation can be quite a
bit confusing on how to actually use SAM

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so what I'm going to do is show you a
process that I use and it's very simple

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all I do is I have a github repository
which has two files in it, one file will

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be your SAM template and that will
define where your code for your Lambda

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functions is and also will define
any other services that you require such

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as an s3 bucket and it will also have
the code which will be an index.js

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file which will have your nodejs code
for your Lambda application. So all

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we need to do is bring that into the ec2
environment within Cloud9 and we just

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need to create our package.JSON file
which will reference any additional

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packages that our application requires
and from there we can just use SAM build

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to prepare it for deployment and then
use SAM deploy to deploy our application.

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So let's get into it. Now all of the code
is located in this Github repository

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here so the the link for this is in the
lab notes of course so the first thing

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that you need to do is make sure that
you star this repository that way you

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can find it easy enough again if you
need to and also so that other people

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can find it as well so once we've done
that we can have a look at our code so

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we've got here our template.yml and that
is going to define our Sam template and

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so let's have a look at that so we've
got a transform function or a transform

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statement here and that is required so
that tells us that word tells

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cloudformation to use the service application
model. Next we're creating

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called create thumbnail and that is a
lambda function now the properties for

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this lambda function the code will be
located in a folder called code and the

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handler will be in an index.js
file within code and that will have an

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exports module called handler the
runtime will be Nodejs the timout will be

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60 seconds and the policy that we're
going to use is the AWS managed Lambda

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policy called AWS lambda execute
and we're going to associate this with

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an event so when something happens to an
s3 bucket this event will be created and

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that will invoke this Lambda function so
the type of event is an s3 event and the

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bucket is going to be referencing a
bucket called sauce bucket which is down

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here and the event is going to be s3
object created so whenever an object or

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an image or whatever is put into this
sauce bucket an event will be created

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which will invoke this lambda function
so let's have a look at this source

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bucket so it it simply has type source
or type AWS s3 bucket so what that will

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do is it will automatically create an s3
bucket and it will name it with a unique

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name so we also need to have a
destination bucket so what this

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application is going to be doing is that
we are going to be uploading a file to a

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source bucket and that will invoke this
lambda function to process that image in

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that source bucket and make a thumbnail
of that image and put it into a

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destination bucket so what we also need
is a destination bucket and we would

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like that destination bucket to have the
same name as our source bucket but going

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to have - resized on the end of it so
what we've got here is at our

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destination bucket it depends on our
sauce bucket so we can't create this

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destination bucket until this sauce
bucket

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exists and then we're going to give it a
bucket name and that is going to be

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joining the name of our source bucket
with - resized on the end so what we use

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is we use a cloudformation join
function and the way that works is that

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first off we define what is the
character that we're going to put in

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between these text strings so we're not
going to have anything between them

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we're just going to have the source
bucket and then -resized so what

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we're going to do there is just have two
inverted commas with a dash in there and

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we're going to define then what the two
text strings are and so it's going

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to be referencing our source bucket name
and then we're going to have - resized

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so the bucket name will be the join of a
resource bucket name with - resized on

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the end so we're going to have two
buckets and when we drop an image into

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this source bucket that will create an
event which will invoke our lambda

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function so let's go back to the cloud9
console and get this happening okay

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starting off here in the cloud9 IDE
we're going to be using the ec2

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environment of cloud 9 to build our
application so what the first thing we

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need to do is we need to clone our
repository so git clone and then the URL

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of our repository again this is all in
the lab notes make sure you download

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those so that's done that for us and if
we look at our directory tree we can see

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that we've got our template demo and
I've got a code in there so let's take a

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look at our template demo and what we
can see here is that it's referencing

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our runtime so we need to make sure that
the runtime that we're referencing here

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for Lambda to run is going to be the
same as a runtime that we're going to be

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using to build this so let's just check
what our node version is on our ec2

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environment here in cloud 9

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so there we can see we're running
version 10 in cloud 9

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whereas our template is referencing
version 12 of node and that's pretty

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common for some reason I don't know why
cloud 9 seem to be a bit slow with

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updating its version so we just go into
here and change that to version 10 so

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that wiill be nodejs10.x and we just
do ctrl s to make sure that we save that

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and we just get out of that now and just
close that might as well just leave that

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open for now and let's have a look at
our code here so we've got our index.js

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and we'll open that up and have
a look at that so we can see here it's

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going to require the AWS software
development kit that is not a problem

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for us land that includes it and you
tools is also included with the Lambda

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service when it is invoked but sharp is
not so we need to install sharp on this

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environment and that we need to do that
with a package.json that references that

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sharp that sharp package so what we're
going to do is is we're going to change

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into our code directory and again just
copying from the lab notes it says the

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easiest way to do it and what we need to
do now is that we need to create a

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package JSON file so NPM in it and we're
just going to call the code package code

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that's fine leave everything as it is
everything looks and our entry point is

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going to be indexed which is which we've
got there and ok yes ok so that has

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created a package JSON so we open it up
there it's pretty well got no

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dependencies there whatsoever so what we
need to do now is that we need to do or

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we need to install sharp and that will
put that reference that in our package

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JSON as well as installing sharp so we
do NPM installed and sharp

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so now if we open up our package.json

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and then we can see it's put the
dependency of Sharp in there so we

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don't need any of these new modules now
because Sam bill doesn't need that will

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create all those so we can keep this
quite small now so all I need to do is

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just delete that so it's going to select
it press Delete and that has gone so

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we've got everything we need now we've
got our template which is going to

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define our Sam and how Sam is going to
package and deploy our application we've

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got our index which index J s and we've
also got our package JSON which is going

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to list all of the packages that our
application requires so all with all

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that we need to do now is to go back up
to the main folder there which has got

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our template.yml file in there and
so now we can just do a Sam build and

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that will build this application for you
and it will prepare everything force and deploy

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so we do Sam build so that has
successfully built our application so

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with three files only which is our
template.YML our package JSON and our

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index.js is all that we needed to
build our application it's a very simple

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process to follow this so once we've
done that all we can do now all you need

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to do now is just SAM deploy. So Sam
deploy - - guided. Okay and that

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will guide us through the deployment
process so we'll give this would just

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leave it with the stack name of Sam app
but easy enough to remember and the

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region is us east one confirmed changes
to port before deploying yes we will and

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allows the CLI or the Sam CLI to
create a role yes and save arguments

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to Sam configure it's fine
so now it will be preparing that

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changeset for us and asking us whether
we want to deploy that ok so what it's

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doing here is it is going to be creating
some Lambda permissions and then it's

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going to use those permissions to create
an IAM role for lambda and then it's

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going to be creating that Lambda 
function it's also going to be creating

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a destination bucket and a source bucket

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ok so after a few minutes all of these
resources have been created for us quite

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successfully so what we can do now is
that we can go into the s3 management

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console and we should see those two
buckets that were created so if you look

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at our template ml and we can see that
we did create a source and destination

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buckets and the destination bucket will
be the same name as a source bucket but

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with -resized on the end of it so
let's have a look at that we'll just

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refresh

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so there we can see our Sam app source
bucket and a bit of a hash string there

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- resized and the or that's the source
bucket there and then - resized is our

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destination bucket so if we go into this
will open both of them up so we go into

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our source bucket and what I'm going to
do is just upload an image

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and just to get that through accept all
the defaults if that's fine okay so

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that's uploaded that that object that
JPEG file so what's going to happen now

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is that that world trigger and s3 event
that s3 event will invoke that Lambda

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function which will then grab this data
JPEG file it will create a thumbnail

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image of that and it will store it into
our destination source or a destination

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bucket so let's go to that destination
bucket now and we're just going to

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refresh that and there we can see so
resize data JPEGs so let's have a look

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at that original one
where's 150 K and the next one is 9.8 K

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so it's created a thumbnail of that not
a problem so that has worked what I want

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to do now is actually have a look at
this code and see how it everything

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actually worked so let's open up our
index page is and have a look at it so

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first of all we have our exports handler
so that is going to be our index.js

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well when we reference that in our
template.yml it's going to be our

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index.js and then what that module that
we're exporting and here are going to be

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calling it handler so the first thing
we're going to do is that we're going to

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get the source
bucket and that is going to become is

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going to come from the event that
triggered this s3 bucket name so how do

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we know that so why we do that as we go
to the two the s3 documentation so here

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we are in the s3 developer guide so we
just go down to notifications and then

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we can see event message structure so
let's just scroll down and see what it

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looks like so it's going to be an array
called records and having a few objects

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in there so what we've got here is s3
bucket and name so go back to our cloud

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9 we can see that we've got s3 bucket
and name and we also need to know what

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the source keys so what the actual name
of that image file

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all that we uploaded is and so again
we'll go back to the event structure and

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we can see here we've got s3 object and
key so if we go back to our code we can

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see there we've got its three object and
key so now we we know what the source

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bucket is we know what the file name is
and from there we can create our

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destination bucket which will be the
same as the source bucket or we can

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reference our destination bucket it's
already been created and that will have

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the name sort of their source bucket
with - resized on the end of it and our

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destination key and that's what we're
going to use there which is going to be

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based upon our source key as well so
then what we need to do is to infer our

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image type and make sure that is either
a JPEG or a PNG type file so once

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everything is fine we've got a jpg or
PNG file in there we can download that

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image so we need to get the parameters
which will be the bucket source bucket

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and the source key for that image and so
then we're going to download that using

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the get objects command from the AWS
software development kit and so once

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we've got that image we can then apply
sharp to that image so sharp will get

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the original image which which we've got
here and it's going to resize it to a

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width of 200 and it's going to put it
into a buffer so that you will have

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temporary storage of that file for us if
there's an error it will lock

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console.log out that error so once we've
got the original image and we've got it

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stored in a buffer we can now get it
back use it or we can now upload it to

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the destination file or the destination
folder with that thumbnail image so we

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have our destination parameters which
will be our destination bucket and our

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destination key and what is going to be
going in there will be in our buffer so

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the buffer will contain the thumbnail
image that we created using

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which will be 200 pixels wide and the
content type will be image so once we've

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created those parameters we can pass
those parameters to a put object command

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and once that's successfully done that
will be fine and our object our

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thumbnail image of our original image
will be uploaded to that bucket so quite

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straightforward we're simply just
getting that image from the event s3

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bucket name and the name of the image
from s3 object key and then we're using

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sharp to resize it to 200 and putting it
into a buffer and then we're just

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getting put objects to put it into our
destination bucket into that destination

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key from the buffer so let's now jump
into lambda and have a look at how it

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all worked so just going to the lambda
management console and this time we're

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going to look at the application we
actually created a application that

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consisted of multiple parts not just a
lambda function so there's our

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application Sam - app if we click on
that

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and we can see that it's created or it's
made up of a lambda function and - s3

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buckets and so there will be a link to
the s3 buckets and here is a link to our

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Lambda function so there's our lambda
function and what we can do is we can go

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to monitoring and view the logs in cloud
watch and see what was produced through

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the console dot log so scroll down
there's our log stream so let's have a

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look here so we've got the first one
here so it received again at that event

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record and within that event record we
had s3 bucket and bucket name and we

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also had the key which is data dot JPEG
so that file that I uploaded and then

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what happened next was it successfully
resized

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Sam app sauce bucket data JPEG and
uploaded it to Sam app source bucket

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resize JPEG so that's pretty cool
everything worked fine so I think I've

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shown you everything that you need to
really know about this same process and

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I hope you in I hope you got a lot out
of it and I I hope you enjoyed it and I

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look forward to seeing you in the next
one but before we do that we'll just

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clean this up so we need to first off
empty our buckets so we'll get this

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bucket and empty it

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we'll go to the next bucket or resize
bucket well empty that as well

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so now that our buckets are empty we can
just go into cloud formation and delete

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our Sam apps we're just going to refresh
this make sure it's all okay yep and

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delete our Sam app make sure you don't
delete these other two just delete the

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Sam app and delete that stack so after a
certain amount of time that will delete

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all of those Lambda resources those s3
resources and that that that app if you

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want we can go into here also in to
delete our code as well so just delete

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that and there we go that's done so I
look forward to seeing you in the next

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one