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Python for DevOps

DevOps

COURSE OVERVIEW


This 10-day intensive course, Python for DevOps, provides the essential programming and automation skills required to manage modern infrastructure and delivery pipelines.

Course Description

This course bridges the gap between software development and systems operations by leveraging the Python ecosystem for full-scale automation. Participants begin with Python fundamentals and quickly move into specialized DevOps applications, including Linux system automation, REST API integration, and Cloud SDKs (AWS Boto3 and Azure SDK). The curriculum emphasizes practical application, showing how to automate CI/CD pipelines in Jenkins and GitHub Actions, manage Docker and Kubernetes via code, and build reusable automation frameworks using Object-Oriented Programming (OOP). The training concludes with a series of Capstone Projects where students build real-world tools for infrastructure provisioning and log monitoring.

 

Learning Objectives

 

By the end of this course, participants will be able to:

  • Master Python Fundamentals: Write and debug scripts using core syntax, data structures (lists, dictionaries, sets), and modular programming techniques.
  • Automate Linux Systems: Use the subprocess and os modules to automate disk monitoring, service restarts, and user management.
  • Process DevOps Data: Parse and manipulate common DevOps configuration and data formats, specifically JSON and YAML.
  • Integrate with APIs: Use the Requests library to automate operations across cloud platforms and CI/CD tools.
  • Orchestrate Cloud Infrastructure: Provision and manage resources in AWS (using Boto3) and Azure through automated Python scripts.
  • Automate Container Orchestration: Control the lifecycle of Docker containers and Kubernetes pods using specialized Python clients.
  • Build CI/CD Automation: Develop scripts to trigger deployments and manage artifacts within GitHub Actions and Jenkins pipelines.
  • Implement Robust Automation: Build production-ready tools with professional error handling, unit testing (pytest), and OOP-based modularity.

 

Target Audience

This course is designed for:

  • Systems Administrators and Operations Engineers looking to transition from manual tasks to automated, code-driven environments.
  • DevOps Professionals who need to deepen their ability to customize pipelines and cloud resources beyond basic configuration files.
  • Software Developers moving into DevOps roles who need to apply their coding skills to infrastructure and reliability engineering.
  • Cloud Engineers aiming to automate multi-cloud environments using standard SDKs.

COURSE OUTLINE


1. Introduction to Python for DevOps

1.1 What is Python

  • Overview of Python
  • Why Python is widely used in DevOps
  • Python ecosystem

1.2 Python in DevOps

  • Infrastructure automation
  • CI/CD pipeline automation
  • Cloud automation
  • Monitoring automation
  • Configuration management

1.3 Installing Python

  • Installing Python on Linux
  • Installing Python on Windows

Tools:

  • pip
  • virtualenv

2. Python Basics

2.1 Python Syntax

  • Python interpreter
  • Python scripts
  • Running Python programs

2.2 Variables and Data Types

  • Integers
  • Floating numbers
  • Strings
  • Booleans

2.3 Operators

  • Arithmetic operators
  • Comparison operators
  • Logical operators

2.4 Input and Output

  • Input from user
  • Output using print()

3. Control Flow

3.1 Conditional Statements

  • if
  • elif
  • else

3.2 Loops

  • for loop
  • while loop
  • nested loops

3.3 Loop Control

  • break
  • continue
  • pass

4. Python Data Structures

4.1 Lists

  • Creating lists
  • List operations
  • List slicing

4.2 Tuples

  • Immutable collections
  • Tuple unpacking

4.3 Dictionaries

  • Key value pairs
  • Dictionary operations

4.4 Sets

  • Unique collections
  • Set operations

DevOps use cases:

  • Managing configuration data
  • Parsing API responses

5. Functions

5.1 Function Basics

  • Defining functions
  • Function parameters
  • Return values

5.2 Advanced Functions

  • Default parameters
  • Keyword arguments
  • Lambda functions

5.3 Modular Programming

  • Code reuse
  • Utility functions

6. Python Modules and Packages

6.1 Built-in Modules

  • os module
  • sys module
  • subprocess module

6.2 Creating Modules

  • Custom modules
  • Importing modules

6.3 Python Packages

  • Package structure
  • Installing packages

Using:

  • pip

7. Working with Files

7.1 File Operations

  • Reading files
  • Writing files
  • Appending files

7.2 Log File Processing

  • Parsing log files
  • Searching logs
  • Filtering logs

7.3 Configuration Files

  • Working with JSON
  • Working with YAML

DevOps tools often use:

  • YAML
  • JSON

8. Error Handling

8.1 Exceptions

  • try
  • except
  • finally

8.2 Custom Exceptions

  • Creating custom exceptions
  • Logging errors

8.3 Debugging Python Programs

9. Python Object Oriented Programming

9.1 Classes and Objects

  • Creating classes
  • Object instantiation

9.2 OOP Concepts

  • Encapsulation
  • Inheritance
  • Polymorphism

9.3 OOP for DevOps Automation

  • Automation frameworks
  • Reusable automation modules

10. Python for Linux Automation

10.1 Running Linux Commands

Using:

  • subprocess module

Example tasks:

  • Disk monitoring
  • Service restart
  • System health checks

10.2 System Automation

  • File system automation
  • User management automation

Works with systems like:

  • Ubuntu

11. Python for DevOps Automation

11.1 Infrastructure Automation

  • Automating server configuration
  • Automating deployments

11.2 Configuration Management

Automation integration with:

  • Ansible

11.3 DevOps Task Automation

Example tasks:

  • Backup automation
  • Server health monitoring
  • Log analysis automation

12. Python and APIs

12.1 REST API Basics

  • HTTP methods
  • API authentication
  • JSON responses

12.2 Python Requests Library

Using:

  • Requests

12.3 Automating API Operations

Examples:

  • Create cloud resources
  • Manage CI/CD pipelines
  • Trigger deployments

13. Python for Cloud Automation

13.1 Cloud SDKs

Automate cloud using Python SDKs.

13.2 AWS Automation

Using:

  • Boto3

Tasks:

  • Launch EC2 instances
  • Manage S3 buckets
  • Automate infrastructure

13.3 Azure Automation

Using:

  • Azure SDK for Python

14. Python for CI/CD Automation

14.1 Pipeline Automation

Automating pipelines in:

  • GitHub Action
  • Jenkins

14.2 Pipeline Scripts

Tasks automated:

  • build automation
  • deployment triggers
  • artifact uploads

15. Python for Container Automation

15.1 Docker Automation

Using Python to control:

  • Docker

Tasks:

  • Build images
  • Run containers
  • Manage container lifecycle

16. Python for Kubernetes Automation

16.1 Kubernetes Python Client

Using:

  • Kubernetes

Tasks:

  • Deploy pods
  • Scale applications
  • Manage services

17. Python for Monitoring Automation

17.1 Metrics Collection

  • System monitoring scripts
  • Application metrics

18. Python Testing

18.1 Unit Testing

Using:

  • pytest

18.2 Integration Testing

  • Testing automation scripts
  • Pipeline testing

19. Python Packaging and Distribution

19.1 Python Packaging

  • Packaging Python projects
  • Versioning

19.2 Publishing Packages

  • Creating reusable automation libraries

20. DevOps Automation Projects (Capstone)

Project 1

Server health monitoring tool

Project 2

CI/CD pipeline automation tool

Project 3

Cloud infrastructure provisioning tool

Project 4

Log monitoring and alerting system

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