Python for DevOps Training — Automation, Cloud SDKs, Scripting & DataOps

Why Python Matters in DevOps & Automation

Python has become the lingua franca of DevOps and cloud automation — and for good reason. It powers AWS (boto3), Azure SDK, GCP client libraries, Ansible (written in Python), and countless CLI tools. It's the primary language for infrastructure automation, CI/CD scripting, cloud operations, and DataOps/MLOps pipelines. If you do one thing to increase your DevOps automation capability, learning Python is it. This course teaches Python specifically through the lens of DevOps: automating cloud infrastructure, writing CI/CD scripts, building CLI tools, and integrating with the tools you use every day.

Who Should Attend

• DevOps engineers who want to level up their automation skills
• System administrators transitioning from Bash to Python for complex automation
• Cloud engineers using Python for AWS/Azure/GCP SDKs
• Data/ML engineers automating pipelines with Python
• Anyone in ops who writes scripts and wants to write better ones

Learning Outcomes

• Write idiomatic Python for automation — no prior Python experience required
• Automate AWS (boto3), Azure, and GCP operations with Python SDKs
• Build CLI tools and automation scripts with argparse, subprocess, and os modules
• Write CI/CD pipeline scripts in Python that integrate with Jenkins and GitHub Actions
• Interact with REST APIs for infrastructure and DevOps tooling
• Process JSON, YAML, and configuration files for Infrastructure as Code workflows
• Write tests for your automation code with pytest
• Containerize Python applications and run them in CI/CD

Course Modules

1. Python Fundamentals for DevOps — Syntax, data types, control flow, functions. Everything taught through ops examples.
2. File & System Operations — os, pathlib, shutil, subprocess. Automating system administration tasks.
3. Configuration & Data Formats — JSON, YAML, CSV, INI. Reading, writing, validating config. jinja2 templating.
4. CLI Tool Building — argparse, click, typer. Building professional CLI tools for your team.
5. Cloud SDKs — AWS (boto3) — EC2, S3, IAM, Lambda automation. Infrastructure scripting with boto3.
6. Cloud SDKs — Azure & GCP — Azure SDK, Google Cloud Python client. Multi-cloud automation patterns.
7. API Integration — requests library. REST APIs. Authenticating with DevOps tools (Jenkins, GitLab, Jira).
8. Testing Automation Code — pytest. Mocking external services. Testing CLI tools. CI/CD for Python projects.
9. Containerization & Deployment — Docker for Python apps. Multi-stage builds. Running Python in Kubernetes.
10. Capstone: Python Automation Project — Build a multi-cloud automation tool with CLI, API integration, and CI/CD.

Hands-on Labs (20 total)

Write Python scripts to provision EC2 instances with boto3. Build a CLI tool for managing cloud resources. Parse and validate Terraform state files. Automate Jira ticket creation through API. Write pytest tests for infrastructure code. Containerize a Python automation service.

Automation Use Cases

• CI/CD: Python scripts for build validation, deployment orchestration, release note generation
• Cloud Ops: boto3 scripts for AWS cost analysis, resource tagging, automated cleanup
• DataOps: Python for data pipeline validation, Airflow DAGs, data quality checks
• MLOps: Python for model deployment scripts, inference API testing, drift monitoring

Related Courses

See Bash Scripting, PowerShell Training, DevOps Engineering, and DataOps Training.