Scripting is a core skill in DevOps. Whether you’re automating infrastructure tasks, setting up CI/CD pipelines, or managing configurations, writing clean and reusable scripts in Bash and Python can save time, reduce errors, and improve collaboration across teams.

In this blog, you’ll learn how to write automation scripts that are easy to maintain, reusable across different environments, and aligned with industry scripting best practices. This is especially useful if you’re preparing for DevOps interviews, where scripting skills are often tested.

Why Clean and Reusable Scripts Matter in DevOps

In DevOps, automation is not optional—it’s essential. As systems grow in complexity, the ability to automate repetitive tasks using scripts becomes a critical part of daily operations.

Here’s why clean and reusable scripting is so important:

  • Reduces manual errors
  • Saves engineering hours on repetitive tasks
  • Simplifies troubleshooting and debugging
  • Makes onboarding easier for new team members
  • Enables consistent execution across environments

Both Bash and Python are widely used for scripting in DevOps. Bash is great for quick system-level tasks, while Python is ideal for more complex logic and integrations.

When to Use Bash vs Python

Before you begin writing scripts, it helps to know when to use which language.

Bash is ideal for:

  • Quick system administration tasks
  • Writing cron jobs
  • File manipulation and process monitoring
  • Interacting with Unix commands and tools

Python is ideal for:

  • Working with APIs
  • Parsing JSON or XML
  • File I/O operations with error handling
  • Building more modular, scalable automation tools

A good DevOps engineer knows how to choose the right tool for the task.

Scripting Best Practices for Automation

To write scripts that are clean, reliable, and reusable, follow these proven scripting best practices:

1. Use Descriptive Naming

Give your scripts and variables clear, meaningful names.

Bad Example:

a=5

Good Example:

retry_count=5

This makes your script self-explanatory.

2. Make Scripts Modular

Avoid writing long monolithic scripts. Break them into smaller, reusable functions or modules. This helps in debugging and reuse.

In Bash:

backup_logs() {

    tar -czf /tmp/logs.tar.gz /var/log/myapp

}

In Python:

def backup_logs():

    shutil.make_archive(‘/tmp/logs’, ‘gztar’, ‘/var/log/myapp’)

3. Use Configuration Files

Avoid hardcoding values like file paths, credentials, or server names. Store them in separate config files or environment variables.

Benefits:

  • Makes scripts reusable across environments
  • Prevents exposure of sensitive data
  • Easier to update configurations without editing the script

4. Handle Errors Gracefully

Scripts should not just break on failure. They should log meaningful errors and fail safely.

In Bash:

set -e

trap ‘echo “Error occurred on line $LINENO”; exit 1’ ERR

In Python:

try:

    deploy_app()

except Exception as e:

    print(f”Deployment failed: {str(e)}”)

5. Add Logging and Comments

Log important steps and decisions. Comment your code so someone else (or future you) can understand it easily.

# Restart the web server after deployment

systemctl restart nginx

# Backup the database before schema migration

Real-World Use Cases for Automation Scripts

1. Daily Backup Scripts

Bash Example:

#!/bin/bash

backup_path=”/backups/$(date +%F)”

mkdir -p “$backup_path”

cp -r /var/www/html “$backup_path”

This script creates daily backups of a web directory with date-based folders.

2. Deployment Automation

Python Example:

import os

import subprocess

def deploy():

    subprocess.run([“git”, “pull”])

    subprocess.run([“docker-compose”, “up”, “-d”])

deploy()

This simple Python script automates pulling the latest code and restarting containers.

3. Log Monitoring

Bash Example:

#!/bin/bash

tail -f /var/log/syslog | grep “ERROR”

A quick way to watch for error messages in system logs.

Making Scripts Reusable Across Environments

Your scripts should work in dev, staging, and production with minimal changes. Here’s how:

Use Environment Variables

export ENV=production

Then access this in your script:

if [ “$ENV” = “production” ]; then

    echo “Deploying to production”

fi

Parameterize Your Scripts

Use arguments instead of hardcoded values:

Bash Example:

#!/bin/bash

# Usage: ./deploy.sh app_name

app=$1

echo “Deploying $app…”

Python Example:

import sys

app = sys.argv[1]

print(f”Deploying {app}…”)

This makes your scripts flexible and adaptable to different tasks.

Tips for DevOps Interview Preparation

When preparing for DevOps interviews, scripting is often part of both the resume screening and technical assessment process.

Here’s how to showcase your scripting skills:

  • Add GitHub links to your personal or professional scripts
  • Be ready to explain how your script works and why you wrote it that way
  • Practice writing scripts on the spot or debugging broken ones
  • Talk about how your scripts improved reliability or saved time
  • Understand common Bash and Python libraries for DevOps (e.g., os, subprocess, shutil, argparse)

If you’re given a live coding exercise, focus on writing readable code over perfect code.

Conclusion

Scripting is a foundational DevOps skill that directly impacts automation, scalability, and team efficiency. Writing clean, reusable scripts in Bash and Python not only improves your daily workflow but also showcases your maturity as a DevOps professional.

Whether you’re automating a deployment, backing up logs, or creating monitoring tools, remember to follow scripting best practices. Use clear naming, modular design, error handling, and version control. These habits will help you in both interviews and production environments.

Practicing these principles not only makes your scripts more professional but prepares you for real-world DevOps challenges.