When you develop an application and are ready to show it to the world, you deploy it on the server. Deploying changes frequently may soon prove a tedious task. How about a facility through which you can configure once and it is deployed as soon as it is pushed to the repository say Github or bitbucket. It will make things a whole lot easier and saves more time and resources.
Thankfully, we have auto-deployment, which takes care of it. It is also called continuous deployment (CD). We will use some DevOps tools for the same for example BitBucket.
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What is DevOps?
DevOps is an organizational approach that allows faster application creation and simpler maintenance of existing implementations by combining development (Dev) and operations (Ops) teams. Now, why do we need DevOps?
DevOps encourages shorter, more controllable iterations by allowing companies to build stronger relationships between Dev, Ops, and other stakeholders in the business through the implementation of best practices, automation, and new tools.
DevOps automation is not a technology in and of itself, but it incorporates everything from society to processes to tooling. Continuous integration and continuous delivery (CI/CD), real-time tracking, incident management systems, and communication networks are common first steps.
Following are some DeOps automation tools(in no particular order):
- Docker
- Sentry
- Jenkins
- Slack
- Nagios
- Ansible
- GitHub
- Vagrant
- Phantom
- BitBucket
Now we'll see how to automate the deployment of a simple Node.js application on an AWS EC2 instance and have it delivered automatically whenever a git push is performed on your production repository. Without you having to do something, the code will be deployed and hosted on your server. We will make use of Bitbucket to see how to automate the deployment process.
The prototype application will be a basic “Hello World” Node.js application, but the getting started principles will be covered, and the application can then be scaled according to your needs.
This is the Node server's app.js file.
express = require("express");
app = express();
const port = process.env.port | 3000
app.get("/", function(req, res){
res.status(200).send("BITBUCKET-->CODEDEPLOY!");
});
app.listen(port,()=>{
console.log(`Node server started on port : ${port}`)
});
The following is the directory structure:
Let's get started, shall we?
Pipelines are provided by Bitbucket servers, which we can use to make deployments simpler. They integrate with many platforms, including Amazon Web Services, Google Cloud Platform, Microsoft Azure, and others.
We'll create an IAM user with programmatic access, which will be used by bitbucket-pipelines to push a copy of our app to an S3 bucket and then cause a deployment on AWS Codedeploy, which will deploy our app on our behalf on our EC2 instance according to our appspec.yml configuration.
This might seem to be a lot, but don't worry, we'll get through it all! Let's start by creating an IAM User.
Step 1: Creating an IAM Group, User, and Role
Create an IAM Group with the following permissions.
- AWSCodeDeployFullAccess
- AmazonS3FullAccess
Create a User and give it Programmatic Access to this group. We'll need the credentials (Access Key, Hidden Access Key) later.
Create an IAM Role and select EC2 Service since our EC2 instance can use that role to communicate with CodeDeploy later. Also, add policies for AmazonS3FullAccessand AWSCodeDeployRole.
After you've created the role, change the Trust Relationship to the following. Adjust the area to the one you're working on.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": [
"ec2.amazonaws.com",
"codedeploy.us-east-1.amazonaws.com"
]
},
"Action": "sts:AssumeRole"
}
]
}
Step 2: Creating an S3 Bucket and an EC2 Instance
Create an S3 bucket, call it whatever you want, and keep the bucket settings default, for now, to keep things simple.
Build an EC2 Instance after that. We'll be using Ubuntu 16.04, but you can use whatever OS you want. We need to add the IAM Role-AWSCodeDeployRole we previously created. Now, for AWS Code Deploy to recognize our instance, it will search for tags, so we'll tag it with Name = CodeDeploy. Finally, open up the proper ports you need for your application in security classes, such as port 3000 for our application.
Start the instance and then install the CodeDeploy Agent on your server; the installation process will differ depending on your operating system. Make sure your Code Deploy agent is up and running by following the instructions for your operating system.
Step 3: Creating a CodeDeploy Application
Create an application in the AWS CodeDeploy console.
After that, Create a deployment group with the settings below.
Name: CD1 (You can choose any)
Service Role: AWSCodeDeployRole
Deployment Type: In Place
Deployment Settings: CodeDeployDefault.OneAtATime
Disable Load Balancing
Also, in the Environment configuration:
When you see one matching instance, click Create Deployment Group.
So far, we've created an IAM user for the Bitbucket Pipeline, an S3 bucket to store our application zip file, an EC2 instance to deploy our application, and a code deploys agent to deploy our application according to the appspec.yml file.
The appspec.yml for our framework is as follows:
version: 0.0
os: linux
files:
- source: /
destination: /home/ubuntu/my-app1
hooks:
BeforeInstall:
- location: scripts/before_install.sh
timeout: 300
runas: ubuntu
AfterInstall:
- location: scripts/after_install.sh
timeout: 300
runas: ubuntu
ApplicationStart:
- location: scripts/application_start.sh
timeout: 300
runas: ubuntu
The following are the three basic bash scripts that were used above:
1. before_install.sh
#!/bin/bash
# Install node.js and Forever.js
sudo apt-get update
sudo apt-get install nodejs-legacy -y
sudo apt-get install npm -y
sudo npm install forever -g
2. after_install.sh
#!/bin/bash
mkdir /home/ubuntu/my-app1
cd /home/ubuntu/my-app1
sudo npm install
3. application_start.sh
#!/bin/bash
# Stop all servers and start the server
forever stopall
forever start /home/ubuntu/my-app1/app.js
Here is how the package-lock.json and package.json look like:
package-lock.json
{
"requires": true,
"lockfileVersion": 1,
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"integrity": "sha512-TkRKr9sUTxEH8MdfuCSP7VizJyzRNMjj2J2do2Jr3Kym598JVdEksuzPQCnlFPW4ky9Q+iA+ma9BGm06XQBy8g==",
"requires": {
"media-typer": "0.3.0",
"mime-types": "~2.1.24"
}
},
"unpipe": {
"version": "1.0.0",
"resolved": "https://registry.npmjs.org/unpipe/-/unpipe-1.0.0.tgz",
"integrity": "sha1-sr9O6FFKrmFltIF4KdIbLvSZBOw="
},
"utils-merge": {
"version": "1.0.1",
"resolved": "https://registry.npmjs.org/utils-merge/-/utils-merge-1.0.1.tgz",
"integrity": "sha1-n5VxD1CiZ5R7LMwSR0HBAoQn5xM="
},
"vary": {
"version": "1.1.2",
"resolved": "https://registry.npmjs.org/vary/-/vary-1.1.2.tgz",
"integrity": "sha1-IpnwLG3tMNSllhsLn3RSShj2NPw="
}
}
}
package.json:
{
"name": "beanstalk",
"version": "1.0.0",
"description": "",
"main": "app.js",
"dependencies": {
"express": "^4.17.1"
},
"devDependencies": {},
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1",
"start":"node app.js"
},
"author": "",
"license": "ISC"
}
Add the following files to your repository, then use Bitbucket to set repository variables and allow pipelining when prompted.
Now we will set up and push bitbucket-pipelines.yml to our repository, and everything should work.
image: node:14.16.0
pipelines:
default:
- step:
caches:
- node
script:
- apt-get update
- apt-get install -y zip
- zip -r application.zip .
- pipe: atlassian/aws-code-deploy:1.3.1
variables:
AWS_DEFAULT_REGION: $AWS_DEFAULT_REGION
AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY: $AWS_SECRET_ACCESS_KEY
APPLICATION_NAME: $APPLICATION_NAME
S3_BUCKET: $S3_BUCKET
COMMAND: 'upload'
ZIP_FILE: 'application.zip'
VERSION_LABEL: 'my-app-1.0.0'
- pipe: atlassian/aws-code-deploy:1.3.1
variables:
AWS_DEFAULT_REGION: $AWS_DEFAULT_REGION
AWS_ACCESS_KEY_ID: $AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY: $AWS_SECRET_ACCESS_KEY
APPLICATION_NAME: $APPLICATION_NAME
DEPLOYMENT_GROUP: $DEPLOYMENT_GROUP
S3_BUCKET: $S3_BUCKET
COMMAND: 'deploy'
WAIT: 'true'
VERSION_LABEL: 'my-app-1.0.0'
IGNORE_APPLICATION_STOP_FAILURES: 'true'
FILE_EXISTS_BEHAVIOR: 'OVERWRITE'
The pipe we see here is another Atlassian script; all you have to do is paste the pipe, including a few key pieces of text, and the rest will be taken care of for you.
This is how the final directory structure appears.
It's now time to make a commit and push to remote.
When you go to the pipeline section of your repository after moving changes to Bitbucket, you'll see a pipeline activated with #1 that looks like this.
You'll see a successful pipeline run and your application deployed on the server if you followed along carefully.
Now try changing the message in your local repository, pushing it to remote, and checking your URL in a few minutes to see if it can reduce your burden for future deployments!
We can see that how the configuration in auto-deployment can save us from writing deployment configurations every time. Automation with DevOps is a great time saver. Try auto-deploying your complex application and invest more time in thinking about features, not about your next deployment.
How about learning a new skill when you get some time off development? Get a chance to explore our micro learning platform- KoolStories and upskill yourself in 15 minutes!
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