README.md

🚀 Shell Scripting + Cloud Foundations: 5 Essential Skills for AWS Automation

This mini project lays the foundation for integrating Shell Scripting with Cloud Computing (AWS). The focus is on mastering 5 critical scripting skills in a real-world scenario: automating EC2 and S3 resource provisioning for a data-driven startup.

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🎯 Objective

Develop a modular shell script using:

• ✅ Functions
• ✅ Arrays
• ✅ Environment Variables
• ✅ Command-Line Arguments
• ✅ Error Handling

This script will prepare AWS resources (EC2 and S3) required by DataWise Solutions to deploy analytical environments for clients.

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📘 Use Case: DataWise Cloud Automation

A client of DataWise Solutions, an e-commerce startup, requires an automated solution to:

• Spin up EC2 instances for compute workloads
• Create S3 buckets to store customer interaction data

The script will automate both tasks while applying clean scripting patterns and safe error handling.

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🔧 Skill Breakdown

1. 🧩 Functions

Structure code into reusable blocks:

create_ec2_instance() {
  # logic to call AWS CLI to provision instance
}
create_s3_bucket() {
  # logic to create and configure S3 bucket
}

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2. 📦 Arrays

Track created resources dynamically:

declare -a created_instances
created_instances+=("instance-1-id")

Arrays help with logging, rollback, or monitoring status.

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3. 🔐 Environment Variables

Secure and configure deployment with:

export AWS_REGION="us-east-1"
export INSTANCE_TYPE="t2.micro"

Avoid hardcoding. Store credentials in .env or use aws configure.

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4. ⚙️ Command-Line Arguments

Make scripts flexible:

./deploy.sh my-bucket-name t2.micro

Access with $1, $2, etc. Validate inputs for robustness:

[ -z \"$1\" ] && echo \"Missing bucket name\" && exit 1

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5. 🛡️ Error Handling

Fail gracefully and inform the user:

aws ec2 run-instances ... || {
  echo \"EC2 instance creation failed\"
  exit 1
}

Use conditional checks, return codes ($?), and log errors for visibility.

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⚙️ Implementation: deploy.sh

#!/bin/bash
set -euo pipefail
source .env

declare -a created_resources

log() {
  echo "[$(date +'%F %T')] $1" | tee -a logs/deploy.log
}

create_s3_bucket() {
  bucket_name=$1
  if aws s3api head-bucket --bucket "$bucket_name" 2>/dev/null; then
    log "S3 bucket '$bucket_name' already exists."
  else
    aws s3api create-bucket --bucket "$bucket_name" --region "$AWS_REGION" --create-bucket-configuration LocationConstraint="$AWS_REGION"
    log "Created S3 bucket: $bucket_name"
    created_resources+=("s3:$bucket_name")
  fi
}

create_ec2_instance() {
  ami_id=$1
  instance_type=$2
  key_name=$3
  response=$(aws ec2 run-instances --image-id "$ami_id" --count 1 --instance-type "$instance_type" --key-name "$key_name" --region "$AWS_REGION" --query 'Instances[0].InstanceId' --output text)
  if [[ -n "$response" ]]; then
    log "Launched EC2 instance: $response"
    created_resources+=("ec2:$response")
  else
    log "EC2 instance launch failed"
    exit 1
  fi
}

# Usage check
if [[ $# -lt 3 ]]; then
  echo "Usage: $0 <bucket-name> <ami-id> <key-name>"
  exit 1
fi

bucket=$1
ami=$2
key=$3

log "Starting AWS resource provisioning..."
create_s3_bucket "$bucket"
create_ec2_instance "$ami" "$INSTANCE_TYPE" "$key"
log "Created resources: ${created_resources[*]}"

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🔐 .env File (Example)

export AWS_REGION="us-east-1"
export INSTANCE_TYPE="t2.micro"

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💡 Sample Execution

chmod +x deploy.sh
./deploy.sh my-bucket-name ami-0abcdef1234567890 my-keypair

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🐞 Debugging Tips

Use set -x at the top to trace execution when troubleshooting:

#!/bin/bash
set -x

Turn off tracing with set +x. Helpful when debugging AWS CLI commands.

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🧠 Concept Summary

Concept	Demo Section	Why It Matters
Functions	create_s3_bucket, create_ec2_instance	Organizes logic into modular units
Arrays	created_resources[]	Tracks provisioned AWS resources
Env Variables	.env + source	Secure, reusable configuration
Cmd Arguments	$1 $2 $3	Allows flexible execution
Error Handling	set -euo pipefail, exit codes	Prevents silent failures, logs errors

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📌 What's Next?

This mini project sets the stage for writing a production-grade shell script that provisions AWS resources on-demand. The full implementation will follow next.

⚠️ Troubleshooting

Issue	Cause	Solution
aws: command not found	AWS CLI not installed	sudo apt install awscli
AccessDenied	Missing IAM permissions	Attach proper policies to IAM user or role
InvalidParameter on EC2	Wrong AMI or config	Use correct ami-id, key-name, instance-type
S3 bucket exists but fails	Bucket already exists globally	Use a unique name with timestamp
script fails silently	No error handling	Use `set -euo pipefail` to catch failures

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📌 Conclusion

This project blends scripting skills with practical cloud automation. By mastering functions, arrays, env variables, arguments, and error handling, it’s possible to scale DevOps capabilities to manage real infrastructure tasks efficiently.

Next step: Expand the script to handle bulk operations, tagging, security groups, and dynamic scaling.