This repository provides an 8-week learning roadmap for DevOps and Platform Engineers to master Python for automation, cloud operations, infrastructure as code, and Kubernetes. It offers hands-on projects using tools like Docker, Terraform, and AI-powered solutions, aiming to prepare users for Python-based DevOps roles and interviews.

How It Works

The roadmap is structured weekly, progressing from Python fundamentals to advanced topics like AI-driven DevOps. Each week focuses on specific DevOps domains, such as API interaction, cloud SDKs, containerization, IaC, Kubernetes automation, security, and Generative AI. The approach emphasizes practical application through hands-on projects that mirror real-world tasks, integrating popular libraries and tools relevant to modern DevOps workflows.

Quick Start & Requirements

• Installation: Primarily relies on standard Python package management (pip).
• Prerequisites: Python 3, venv, pip. Specific projects may require Docker, Terraform, Kubernetes access, cloud SDKs (AWS boto3, GCP google-cloud-sdk), and potentially API keys for AI services.
• Resources: Requires a development environment with Python installed, and potentially access to cloud platforms or Kubernetes clusters for certain projects.
• Links: Python for DevOps Guide

Highlighted Details

• Covers AI-driven DevOps with LlamaIndex, GenAI, LangChain, and OpenAI API.
• Includes projects for automating AWS/GCP operations and Kubernetes management.
• Features Infrastructure as Code automation using Terraform and Ansible with Python.
• Addresses security automation, log analysis, and RBAC checks in Kubernetes.

Maintenance & Community

• The repository is maintained by techiescamp.
• Further community engagement details (e.g., Discord, Slack) are not explicitly provided in the README.

Licensing & Compatibility

• The repository's license is not specified in the README.
• Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The roadmap assumes a foundational understanding of DevOps concepts. Specific project requirements, such as cloud provider access or Kubernetes cluster setup, may necessitate additional configuration and resources beyond basic Python installation. The AI-focused weeks may require access to paid APIs or significant computational resources.