Master Continuous Delivery on AWS: A Practical Guide

2025-02-11

Deploying applications on AWS using CodeBuild, CodePipeline, and Elastic Beanstalk is a game-changer for automating deployments. This guide walks you through the process step-by-step, ensuring you can set up a robust CI/CD pipeline with ease.

Setting Up a Git Repository

Start by initializing a Git repository for your project:

git init
git add .
git commit -m "Initial commit"
git remote add origin <repository-url>
git push -u origin master

Deploying a Web App with AWS Elastic Beanstalk

Install the AWS CLI if you haven’t already:
```
sudo apt install awscli
```

2. Configure your AWS CLI:

aws configure

3. Create an Elastic Beanstalk application:

eb init -p <platform> <application-name>

4. Deploy your application:

eb create <environment-name>

Creating an AWS CodeBuild Project

Navigate to the AWS Management Console and open CodeBuild.

2. Create a new build project:

Source: Connect to your Git repository.
Environment: Choose a managed image (e.g., Ubuntu).
Buildspec: Use a `buildspec.yml` file to define build commands.

Example `buildspec.yml`:

version: 0.2
phases:
install:
commands:
- echo "Installing dependencies..."
build:
commands:
- echo "Building the application..."
post_build:
commands:
- echo "Build completed!"

Building a CI/CD Pipeline with AWS CodePipeline

1. Open CodePipeline in the AWS Management Console.

2. Create a new pipeline:

Source: Connect to your Git repository.
Build: Select the CodeBuild project you created.
Deploy: Choose Elastic Beanstalk as the deployment provider.

3. Save and deploy the pipeline.

Testing the Pipeline

Once the pipeline is set up, push a change to your Git repository to trigger the pipeline:

git add .
git commit -m "Triggering CI/CD pipeline"
git push origin master

What Undercode Say

Mastering Continuous Delivery on AWS is essential for modern DevOps practices. By leveraging tools like CodeBuild, CodePipeline, and Elastic Beanstalk, you can automate deployments, reduce errors, and improve efficiency. Here are some additional Linux and AWS commands to enhance your workflow:

Check AWS CLI Version:
```
aws --version
```

List Elastic Beanstalk Environments:

aws elasticbeanstalk describe-environments

View CodeBuild Logs:

aws codebuild batch-get-builds --ids <build-id>

Monitor CodePipeline Execution:

aws codepipeline get-pipeline-execution --pipeline-name <pipeline-name> --pipeline-execution-id <execution-id>

SSH into Elastic Beanstalk Instance:
```
eb ssh <environment-name>
```
List S3 Buckets:
```
aws s3 ls
```
Create an S3 Bucket:
```
aws s3 mb s3://<bucket-name>
```
Sync Files to S3:
```
aws s3 sync . s3://<bucket-name>
```
Delete an S3 Bucket:
```
aws s3 rb s3://<bucket-name> --force
```
List EC2 Instances:
```
aws ec2 describe-instances
```

Start an EC2 Instance:

aws ec2 start-instances --instance-ids <instance-id>

Stop an EC2 Instance:

aws ec2 stop-instances --instance-ids <instance-id>

Create an IAM User:

aws iam create-user --user-name <username>

Attach Policy to IAM User:

aws iam attach-user-policy --user-name <username> --policy-arn <policy-arn>

List IAM Users:
```
aws iam list-users
```

Create a CloudWatch Alarm:

aws cloudwatch put-metric-alarm --alarm-name <alarm-name> --metric-name <metric-name> --namespace <namespace> --statistic Average --period 300 --threshold <threshold> --comparison-operator GreaterThanOrEqualToThreshold --dimensions Name=InstanceId,Value=<instance-id> --evaluation-periods 2 --alarm-actions <action-arn>

List CloudWatch Alarms:
```
aws cloudwatch describe-alarms
```

Delete a CloudWatch Alarm:

aws cloudwatch delete-alarms --alarm-names <alarm-name>

Create an SNS Topic:

aws sns create-topic --name <topic-name>

Subscribe to an SNS Topic:

aws sns subscribe --topic-arn <topic-arn> --protocol <protocol> --notification-endpoint <endpoint>

Publish to an SNS Topic:

aws sns publish --topic-arn <topic-arn> --message <message>

List SNS Topics:
```
aws sns list-topics
```

Delete an SNS Topic:

aws sns delete-topic --topic-arn <topic-arn>

Create a DynamoDB Table:

aws dynamodb create-table --table-name <table-name> --attribute-definitions AttributeName=<attribute-name>,AttributeType=<attribute-type> --key-schema AttributeName=<attribute-name>,KeyType=HASH --provisioned-throughput ReadCapacityUnits=<read-capacity>,WriteCapacityUnits=<write-capacity>

List DynamoDB Tables:
```
aws dynamodb list-tables
```

Delete a DynamoDB Table:

aws dynamodb delete-table --table-name <table-name>

Create an RDS Instance:

aws rds create-db-instance --db-instance-identifier <instance-id> --db-instance-class <instance-class> --engine <engine> --master-username <username> --master-user-password <password> --allocated-storage <storage>

List RDS Instances:
```
aws rds describe-db-instances
```

Delete an RDS Instance:

aws rds delete-db-instance --db-instance-identifier <instance-id> --skip-final-snapshot

Create a Lambda Function:

aws lambda create-function --function-name <function-name> --runtime <runtime> --role <role-arn> --handler <handler> --zip-file fileb://<zip-file>

List Lambda Functions:
```
aws lambda list-functions
```

Invoke a Lambda Function:

aws lambda invoke --function-name <function-name> --payload <payload> output.txt

Delete a Lambda Function:

aws lambda delete-function --function-name <function-name>

Create an API Gateway:

aws apigateway create-rest-api --name <api-name>

List API Gateways:
```
aws apigateway get-rest-apis
```

Delete an API Gateway:

aws apigateway delete-rest-api --rest-api-id <api-id>

For further reading, check out the official AWS documentation:
– AWS CodeBuild
– AWS CodePipeline
– AWS Elastic Beanstalk

By integrating these tools and commands into your workflow, you can achieve seamless, automated deployments, making your DevOps journey smoother and more efficient.

References:

Hackers Feeds, Undercode AI