🚀 Python for DevOps Week 2 & Week 3: Automating Daily Ops & Containerizing with Docker

In my Python-for-DevOps journey, Weeks 2 and 3 were all about turning theory into daily operational tools.
Here’s a recap concepts + projects so you can follow along if you’re learning too. for code checkout this repo https://github.com/Harivelu0/python-for-devops

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🛠 Week 2: Automating DevOps Tasks with Python

🎯 Goal: Learn to automate daily DevOps operations with Python CLI tools.

📚 Key Concepts Covered

• Working with APIs → Using requests to interact with REST APIs.
• Automating SSH Tasks → Using paramiko for remote command execution.

• Cloud SDKs for Automation →

  • boto3 for AWS
  • google-cloud-sdk for GCP

• Building CLI Tools → Using argparse for structured command-line arguments.

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🔨 Hands-on Projects

1. AWS EC2 Instance Manager (boto3 + argparse)

• Start, stop, and terminate EC2 instances via CLI.
• Learned how to integrate Python with AWS SDK.
• Added safety confirmation for termination.

1. Kubernetes Pod Status Checker (kubectl + subprocess)

• Runs kubectl get pods for a given namespace.
• Parses and formats pod data for better readability.

💡 Takeaway:
By the end of Week 2, I could write Python scripts that directly manage cloud resources and cluster workloads no manual clicking in the AWS Console or running repetitive kubectl commands.

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🐳 Week 3: Docker & Python for Containerized Applications

🎯 Goal: Learn to containerize Python applications for portability and automation.

📚 Key Concepts Covered

• Dockerizing Python Apps → Writing Dockerfile for Python scripts.
• Running Python in Containers → Understanding how to package and run apps in isolated environments.
• Docker Compose → Setting up multi-container environments.
• Python SDK for Docker (docker-py) → Managing containers programmatically.
• System Metrics in Containers → Using psutil inside containers to expose metrics.

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🔨 Hands-on Projects

1. Docker Manager CLI (subprocess)

• Start, stop, restart, or remove containers from Python CLI.

1. Dockerized Flask Metrics API (psutil)

• Returns CPU & memory usage in JSON format.
• Packaged into a Docker image for portability.

💡 Takeaway:
Week 3 connected my Python skills to Docker I can now both control Docker from Python and run Python inside Docker. This is a huge step toward production-ready automation tools.

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Comments

[Suvrajeet Banerjee]

Amazing! 🎉🏆😃