README.md

🧪 Error Handling in Shell Scripting

Error handling is critical for building reliable and maintainable Bash scripts. In this mini project, we focused on building a script to automate the creation of AWS S3 buckets for different departments, while accounting for potential errors like duplicate bucket names, invalid configurations, or AWS CLI failures.

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✅ Project Script: Create S3 Buckets with Error Handling

#!/bin/bash

create_s3_buckets() {
    company="datawise"
    user=$(whoami)  # get your system username
    timestamp=$(date +%s)
    departments=("Marketing" "Sales" "HR" "Operations" "Media")

    for department in "${departments[@]}"; do
        bucket_name="${company,,}-${department,,}-${user,,}-${timestamp}"
        #bucket_name="${company,,}-${department,,}-${user}"

        # Check if bucket already exists
        if aws s3api head-bucket --bucket "$bucket_name" 2>/dev/null; then
            echo "S3 bucket '$bucket_name' already exists."
        else
            aws s3api create-bucket --bucket "$bucket_name" --region us-east-1
            if [ $? -eq 0 ]; then
                echo "✅ S3 bucket '$bucket_name' created successfully."
            else
                echo "❌ Failed to create bucket '$bucket_name'. Please check your AWS CLI config or permissions."
            fi
        fi
    done
}

create_s3_buckets

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🎯 What This Script Demonstrates

• Control flow: for loop to iterate through department names
• Conditional logic: if-else to check for bucket existence
• Error handling: exit status $? used to verify if bucket creation succeeded
• Idempotency: prevents trying to recreate existing buckets
• Feedback: provides useful output messages for each condition

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💡 Example Output (Plaintext)

{
    "Location": "/datawise-marketing-daretechie-1751813785"
}
✅ S3 bucket 'datawise-marketing-daretechie-1751813785' created successfully.
{
    "Location": "/datawise-sales-daretechie-1751813785"
}
✅ S3 bucket 'datawise-sales-daretechie-1751813785' created successfully.
{
    "Location": "/datawise-hr-daretechie-1751813785"
}

---

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🧰 Troubleshooting Table

Issue	Cause	Solution
AccessDenied or AuthFailure	Missing or invalid AWS credentials	Run aws configure to set up your credentials
BucketAlreadyExists	Bucket name not globally unique	Use naming conventions that incorporate your company name
aws: command not found	AWS CLI not installed or not in $PATH	Install AWS CLI and ensure it's in your system's path
Script exits silently	Errors suppressed or not handled	Add set -x or echo outputs for debugging

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🏁 Summary

This project highlighted how to:

• Use control flow to automate bulk resource creation
• Implement graceful error handling using exit codes
• Validate AWS operations before executing commands
• Display informative messages to users

By anticipating and managing errors, the script avoids crashes and improves the user experience. These practices are essential for scripting in real-world production environments where reliability and clarity are critical.