Shell Scripting and Python Interview Questions for DevOps Engineers

In the world of DevOps, automation is the heartbeat of efficiency. Whether it’s configuring servers, deploying code, or monitoring systems, automation reduces human error and saves time. Two of the most powerful tools for automation in a DevOps engineer’s toolkit are Shell scripting and Python.

If you’re preparing for a DevOps coding interview, understanding how to write effective shell scripts and Python scripts is crucial. In this blog, we’ll explore key shell scripting interview questions and Python for DevOps questions that will help you perform confidently in technical interviews.

What Makes Scripting Important in DevOps?

Automation scripting is the foundation of DevOps. It helps engineers perform repetitive tasks with precision. From CI/CD pipelines to system monitoring, scripting ensures seamless collaboration between development and operations.

Shell scripting is often used for system-level automation—like file handling, log management, and service monitoring—while Python is used for more complex automation, integrations, and orchestration tasks.

Together, these scripting languages empower DevOps teams to build robust, scalable, and efficient systems.

Shell Scripting Interview Questions

1. What is Shell Scripting, and why is it used in DevOps?

Shell scripting is a way to automate commands in Unix/Linux environments using interpreters like Bash or Zsh. In DevOps, it’s used for server provisioning, log analysis, deployment automation, and system maintenance.

2. How do you check if a file exists in Shell Script?

Example:

if [ -f /path/to/file.txt ]; then

  echo “File exists”

else

  echo “File not found”

fi

This command checks whether a file exists before performing an operation—common in deployment or configuration scripts.

3. How can you automate repetitive Linux tasks with Shell Script?

Tasks like log rotation, system updates, or clearing cache can be automated using cron jobs. For example:

0 3 * * * /scripts/cleanup.sh

This runs a cleanup script every day at 3 AM.

4. What are some commonly used Shell commands in DevOps?

Some frequently used commands include:

• grep – for searching patterns in logs.
• awk and sed – for text processing.
• df, du – for monitoring disk usage.
• systemctl, service – for managing services.
• curl, wget – for API testing or downloading files.

5. Explain the use of variables and arguments in Shell Scripts.

Variables store data temporarily in scripts, while arguments pass input dynamically. Example:

#!/bin/bash

echo “Hello, $1”

Running ./script.sh DevOps outputs: Hello, DevOps.

6. How do you handle errors in Shell Scripts?

Using exit codes and error redirection helps manage failures:

command || { echo “Command failed”; exit 1; }

This ensures that your script stops or alerts the user if something goes wrong.

7. How can you monitor system performance using Shell Script?

You can fetch CPU, memory, and disk usage with commands like:

top -b -n1 | grep “Cpu(s)”

free -m

df -h

These outputs can be parsed and logged for performance monitoring.

Python Interview Questions for DevOps Engineers

1. Why is Python preferred for DevOps automation?

Python is versatile, easy to learn, and integrates well with cloud APIs, monitoring tools, and CI/CD systems. It’s widely used for automation, data parsing, testing frameworks, and building infrastructure management tools.

2. How can you automate deployments with Python?

Python scripts can interact with cloud services like AWS, Azure, or GCP using SDKs such as boto3 or google-cloud. Example:

import boto3

s3 = boto3.client(‘s3’)

s3.upload_file(‘app.zip’, ‘mybucket’, ‘deployments/app.zip’)

This automates file uploads for deployment.

3. How do you handle errors and exceptions in Python scripts?

Using try-except blocks ensures stability:

try:

    result = 10 / 0

except ZeroDivisionError:

    print(“Cannot divide by zero”)

Error handling is critical in automation to avoid breaking pipelines.

4. How can Python integrate with CI/CD tools?

Python scripts can trigger Jenkins jobs, manage GitHub repositories, or validate configurations. With libraries like requests or subprocess, engineers can interact with APIs or system commands to automate build and deployment processes.

5. Explain how you would use Python for log analysis.

You can read and parse large log files to identify errors:

with open(‘server.log’) as file:

    for line in file:

        if ‘ERROR’ in line:

            print(line.strip())

This kind of automation scripting question is common in interviews, testing your ability to monitor and troubleshoot systems.

6. How do you schedule or run Python scripts automatically?

Python scripts can be scheduled using cron jobs, or by using task schedulers in CI/CD pipelines. For recurring automation, frameworks like Airflow or Celery are also used.

7. How do you use Python for Infrastructure as Code (IaC)?

Python integrates with tools like Terraform, Ansible, and Pulumi to manage infrastructure. You can also directly use boto3 or paramiko to provision servers, configure environments, and automate scaling.

Common DevOps Scripting Interview Tasks

During an interview, you may be asked to perform short automation tasks such as:

• Write a shell script to monitor disk space and send an alert if usage exceeds 80%.
• Create a Python script to check the availability of a list of URLs.
• Parse log files and count the number of failed login attempts.
• Automate deployment of a Docker container using a Python API.

These tasks evaluate your hands-on scripting skills and problem-solving mindset.

Scripting Best Practices for DevOps Engineers

• Keep scripts modular: Write functions and reusable components.
• Follow naming conventions: Use clear variable and function names.
• Add error handling: Always validate inputs and handle failures.
• Use version control: Store your scripts in Git for collaboration and rollback.
• Document and comment: Good documentation helps others understand your automation logic.
• Test before deployment: Validate scripts in staging environments before production use.

These practices show that you understand not just how to script, but how to maintain reliability and consistency in a DevOps ecosystem.

Conclusion

Mastering Shell scripting and Python for DevOps is essential for any engineer aiming to excel in automation and system reliability. From server management to CI/CD integration, scripting empowers engineers to build efficient, scalable solutions.

When preparing for your scripting interview tasks or DevOps coding interview, focus on practical problem-solving, understanding logic flow, and real-world application of automation. Remember, interviewers are not just testing syntax—they’re testing your ability to think, troubleshoot, and improve processes with scripting.