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- [Alana] Hello, and welcome back.

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Our development team is
getting to the end of a sprint.

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Some exciting new features
are coming to the application.

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Now, we have to start thinking
about how we are going

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to deploy the application

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to get those features in
front of our customers.

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We've spoken about different
deployment strategies

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for the application, and the
team has decided they want

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to use the service, AWS CodeDeploy,

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to take our build artifact,
getting built by CodeBuild,

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and deploy this to our
application instances.

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CodeDeploy supports
deploys to EC2 instances,

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on-premises physical servers,

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AWS Lambda, and Amazon ECS.

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Our application is
hosted on EC2 instances.

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To get started with CodeDeploy,

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we will need to create an application,

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and one or more deployment groups.

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Let's go through what each of these means.

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An application defines
the compute platform

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we are deploying to.

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This is a choice of the
supported platforms:

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EC2/on-premises, Lambda, and ECS.

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I'm deploying to EC2 instances,

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so I would use the
EC2/On-premises compute platform.

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An application can have
multiple deployment groups.

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For an EC2 server deployments,

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the deployment group
needs to know information

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about several things, like:

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The IAM role that CodeDeploy will use

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to authenticate to other services.

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The deployment style, whether
it's in-place or blue/green.

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In-place will replace the
application on our instances,

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and blue/green will
create new green instances

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to deploy the application.

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Then, we have to specify the
deployment configuration.

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For an EC2 deploy,

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this controls the number or percentage

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of healthy hosts we want
available during a deployment.

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We also have to specify
how to find our instances

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by tags, Auto Scaling group,

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or even on-premises tagged instances.

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For a blue/green deploy,

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we can configure an Auto Scaling group

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that CodeDeploy will copy to
provision the green instances.

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Specifically for a blue/green deploy,

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you have control over
when to route the traffic

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to the green instances.

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It can be automatic or the
deploy can wait for you

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to continue the deployments
when you're happy to go ahead.

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You also control how long the original,

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or blue, instances are kept
after successful deploy.

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Optionally, you can also
select a load balancer,

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so CodeDeploy knows where to register

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and deregister instances
during the deployment.

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We can also associate CloudWatch alarms.

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A deployment can be halted

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if any of the configured
CloudWatch alarms go

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into an alarm state.

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And finally, auto rollback.

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If we want to automatically rollback

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on a deployment failure,

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a rollback is just going

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to redeploy the last
successful deployment for you.

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With an application and
deployment group in place,

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I'm ready to create a deployment.

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A deployment for EC2 just
needs to know my application,

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the deployment group, and the
revision of my application.

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The revision is the
artifact we want to deploy.

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This will contain all the
files and instructions run

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on each host during the deployments.

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These instructions are
configured in an AppSpec file.

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We will go into a lot more
detail on the AppSpec file,

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and the hooks you have
to run your commands

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during a deployment, later.

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How exactly are these commands
run on my instances, though?

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Well, this is the job
of the CodeDeploy agent.

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We need to have the agent installed

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and running on all of the instances

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where we plan to deploy the application.

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The link on your screen
goes to more details

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on how to install the CodeDeploy agent.

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I'll also include this link
in the course readings.

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An EC2 deployments from CodeDeploy
can pick up this artifact

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from S3 or from a GitHub commit.

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When CodeDeploy is added as part

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of an AWS CodePipeline action,

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the revision can be
picked up from the output

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of another CodePipeline action,

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for example, the artifacts created

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from a pipeline build phase.

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Here's Russ to show you more
about this in the console.

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- [Russ] Let's jump into the console,

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and see how all of this works
with a simple deployment.

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From inside the console,

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I can create a CodeDeploy application.

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This is just the application name,

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and the compute platform we are
deploying to, EC2 instances.

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Now, I create the deployment group.

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We give it a name.

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I choose the service role.

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This is the role it
will use to authenticate

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to other AWS services.

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Our deployment type,

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let's start simple with
an in-place deployment.

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CodeDeploy needs to know which instances

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that we want to deploy to,

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so I'm going to give it
an EC2 instance name tag.

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We are given an option to
install the CodeDeploy agent

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on our instances.

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I don't need to do this because
I already have this set up.

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For deployment settings,
let's do all at once.

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This will mean an outage
for our application,

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but I'm deploying to a dev environment

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and I want to deploy as fast as I can.

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I have a load balancer set up,

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so I can tell CodeDeploy

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about my load balancer target group, here.

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I now have an application and
a deployment group set up.

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I have everything I need
to create a deployment.

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This will send an application revision

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to the deployment group we just created.

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Let me show you what a
simple revision looks like.

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I have a revision open in an editor here.

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The revision contains
a simple AppSpec file,

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the scripts I have specified
to run with each of the hooks,

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and a single source file I
want to deploy on my instances.

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Back in the CodeBuild console,

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from my deployment group, I
can choose Create deployment.

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All I need to supply here is
the location of my revision.

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I have zipped up the
contents of my revision

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and copied this to an S3 bucket.

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I can enter the S3
location of my revision.

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I can override some deployment
group settings, here.

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I'll just keep this set to all at once,

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and then choose Create deployment.

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My deploy completed in
about a minute and a half.

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If I choose View events here
for one of my instances,

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I see the sequence of events
that happen during the deploy.

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BlockTraffic is the event
that deregistered the instance

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from the load balancer.

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AllowTraffic is the event
that registered it back.

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ApplicationStop and
BeforeInstall are the two steps

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where my revision scripts ran.

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These events all ran
simultaneously on my instances,

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where you're using

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the all-at-a-time
deployment configuration,

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for this deployment.

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If we were to use one at a time

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for the deployment configuration,

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one instance would be selected,

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all of the events we
see here would complete.

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Only then would CodeDeploy
move to the next instance.

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That was a pretty quick
introduction to CodeDeploy.

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We have spoken about
CodeDeploy's application,

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deployment group,
deployments, and revisions.

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We saw the deployment run
against my five instances,

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where the CodeDeploy agent
followed the instructions

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in my AppSpec file to get
my applications installed.