
Python for DevOps Course
Master Python automation for real DevOps workflows — from provisioning cloud infrastructure to scripting CI/CD pipelines and security compliance checks. This course gives you the practical Python skills that DevOps engineers use every day on the job. Stop doing manually what Python can handle for you.
What you will learn:
You will learn to write Python scripts that automate file operations, API calls, and cloud resource management across AWS, Azure, and GCP. You will parse JSON, YAML, and XML configuration files used by Kubernetes, Ansible, and CI platforms. You will build reusable REST clients, automate Docker container lifecycles, and integrate security scanning into deployment pipelines. You will instrument scripts with Prometheus metrics and structured logging for full observability. By the end, you will have a production-ready Python automation toolkit covering infrastructure, pipelines, monitoring, and security.
How you study in practice Python for DevOps Course
How you practise Python for DevOps Course
For companies looking to train their teams
With Dedika for businesses, the course includes exercises and examples tailored to your company and its specific needs.
Course content
8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsPython Foundations for DevOps
Python Foundations for DevOps
Lesson 1 • Core Python Syntax and Data Types
Cover variables, operators, strings, numbers, booleans, and type conversion. Provides the vocabulary for every script written in later chapters.
Lesson 2 • Control Flow and Loops
Apply conditionals and iteration to automate repetitive decision-making. Directly enables writing logic-driven automation scripts in subsequent chapters.
Lesson 3 • Functions and Modules
Define reusable functions, handle arguments, and import standard library modules. Supports modular script design used in all DevOps automation patterns.
Lesson 4 • Setting Up the Python Environment
Install Python, configure virtual environments, and select an IDE suited for DevOps work. Establishes the baseline toolchain used throughout the course.
Lesson 5 • Error Handling and Debugging
Use try/except blocks and debugging tools to write resilient scripts. Prevents silent failures in unattended automation pipelines.
Chapter 2HideHide detailsSee detailsFile System and Process Automation
File System and Process Automation
Lesson 1 • Scheduling and Automating Tasks
Schedule Python scripts as cron jobs and use the schedule library for in-process timing. Connects file and process skills into end-to-end automation pipelines.
Lesson 2 • Environment Variables and Configuration
Read, set, and validate environment variables for runtime configuration. Supports twelve-factor app patterns used in containerised deployments.
Lesson 3 • Path and Directory Operations
Navigate and manipulate the file system using the pathlib and os modules. Enables portable, cross-platform automation scripts.
Lesson 4 • Reading and Writing Files
Open, read, write, and append text and binary files using built-in file I/O. Forms the foundation for config parsing and log processing tasks.
Lesson 5 • Running Shell Commands from Python
Execute system commands and capture output using the subprocess module. Bridges Python scripts with existing CLI tools in DevOps workflows.
Chapter 3HideHide detailsSee detailsWorking with Data Formats
Working with Data Formats
Lesson 1 • JSON Parsing and Generation
Serialise and deserialise JSON using the json module and handle edge cases. JSON is the primary data exchange format in APIs and CI/CD tooling.
Lesson 2 • XML Parsing and Transformation
Extract data from XML documents using ElementTree and lxml. Supports integration with legacy systems and Maven/Ant build outputs.
Lesson 3 • YAML Configuration Files
Load and dump YAML documents using PyYAML and ruamel.yaml. YAML is the dominant format for Kubernetes, Ansible, and CI pipeline configs.
Lesson 4 • TOML and INI Configuration Files
Parse TOML and INI files for tool configuration and project metadata. Covers formats used by pip, pytest, and modern Python packaging tools.
Lesson 5 • CSV and Tabular Data
Read and write CSV files using the csv module and pandas for larger datasets. Enables processing of inventory exports, audit logs, and metric reports.
Chapter 4HideHide detailsSee detailsNetworking and API Automation
Networking and API Automation
Lesson 1 • Pagination and Rate Limiting
Handle paginated API responses and respect rate limits with retry logic. Prevents script failures when consuming large datasets from external APIs.
Lesson 2 • HTTP Requests with the Requests Library
Send GET, POST, PUT, and DELETE requests and handle responses. Provides the core skill for all API-driven automation in later sections.
Lesson 3 • Authentication and Security
Implement API key, OAuth2, and token-based authentication in scripts. Ensures automation scripts meet security requirements of enterprise APIs.
Lesson 4 • Network Diagnostics and Socket Programming
Check host reachability, open ports, and DNS resolution using Python sockets. Enables automated health checks and network validation scripts.
Lesson 5 • Building a Lightweight REST Client
Encapsulate API calls into a reusable client class with session management. Promotes code reuse across multiple DevOps automation scripts.
Chapter 5HideHide detailsSee detailsInfrastructure Automation with Python
Infrastructure Automation with Python
Lesson 1 • Kubernetes Automation with Python
Deploy and manage Kubernetes workloads using the official Python client. Supports automated rollouts, scaling, and health verification.
Lesson 2 • Configuration Management Integration
Trigger Ansible playbooks and Salt states from Python scripts. Closes the loop between dynamic inventory generation and configuration enforcement.
Lesson 3 • Automating Infrastructure as Code Tools
Invoke Terraform and Pulumi programmatically from Python scripts. Integrates IaC execution into Python-driven orchestration pipelines.
Lesson 4 • Docker Automation with Python
Build images, manage containers, and inspect networks using the Docker SDK for Python. Enables programmatic container lifecycle management in pipelines.
Lesson 5 • Cloud Provider SDKs
Use Python SDKs to create, list, and delete cloud resources programmatically. Covers the SDK patterns common across major cloud providers.
Chapter 6HideHide detailsSee detailsCI/CD Pipeline Automation
CI/CD Pipeline Automation
Lesson 1 • Artifact Management Automation
Upload, download, and promote artifacts in registries using Python scripts. Supports versioned artifact workflows in multi-stage pipelines.
Lesson 2 • Automating Build and Test Steps
Invoke build tools, run test suites, and parse test results from Python. Enables dynamic test orchestration beyond static pipeline YAML.
Lesson 3 • CI/CD Concepts and Python Integration Points
Map CI/CD pipeline stages to Python automation opportunities. Establishes the mental model for where Python scripts plug into build systems.
Lesson 4 • Deployment Automation Scripts
Script blue-green, canary, and rolling deployments using platform APIs. Reduces human error in release execution by encoding deployment logic in Python.
Lesson 5 • Notifications and Release Reporting
Send pipeline status updates to chat platforms and generate release notes. Closes the feedback loop between deployments and engineering teams.
Chapter 7HideHide detailsSee detailsMonitoring, Logging, and Observability
Monitoring, Logging, and Observability
Lesson 1 • Alerting Automation
Query monitoring APIs and trigger alerts based on threshold logic in Python. Replaces manual dashboard watching with proactive automated alerting.
Lesson 2 • Metrics Collection and Exposition
Instrument Python scripts with Prometheus client metrics and expose them via HTTP. Feeds custom metrics into existing monitoring stacks.
Lesson 3 • Log Parsing and Analysis
Extract patterns, errors, and metrics from raw log files using regex and parsing libraries. Enables automated anomaly detection and report generation.
Lesson 4 • Structured Logging in Python
Emit structured JSON logs and configure log levels, handlers, and formatters. Structured logs are machine-parseable by log aggregation platforms.
Lesson 5 • Distributed Tracing Integration
Instrument Python scripts with OpenTelemetry to emit traces and spans. Provides end-to-end visibility into automation workflows across services.
Chapter 8HideHide detailsSee detailsSecurity Automation and Compliance
Security Automation and Compliance
Lesson 1 • Audit Logging and Compliance Reporting
Collect audit trails from cloud and platform APIs and generate compliance reports. Supports evidence collection for security audits and regulatory reviews.
Lesson 2 • Secret Detection and Management
Scan codebases for exposed secrets and integrate with vault solutions via Python. Prevents credential leakage in repositories and pipeline artifacts.
Lesson 3 • Automated Security Testing in Pipelines
Integrate static analysis and DAST tools into CI pipelines via Python scripts. Shifts security left by blocking insecure code before deployment.
Lesson 4 • Infrastructure Compliance Checks
Validate cloud resource configurations against security policies using Python. Enforces least-privilege and encryption standards across environments.
Lesson 5 • Vulnerability Scanning Automation
Invoke dependency and container scanners from Python and parse their output. Automates security gates that block vulnerable artifacts from promotion.
Your valid completion certificate
This course is for you:
Sysadmins: ready to move beyond shell scripts into structured automation code.
Cloud engineers: wanting to control infrastructure programmatically instead of through consoles.
Junior DevOps engineers: looking to add Python scripting to their professional toolkit.
Platform engineers: needing reusable tooling that integrates across multiple internal systems.
Career changers from IT support: building automation skills to transition into DevOps roles.
QA engineers: expanding into pipeline automation and infrastructure testing with Python.
What our students say
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