In this article we are going to cover why Python Learning is must for Cloud Engineers, DevOps Engineers, Platform Engineers and SRE (Site Reliability Engineer).
Mastering/Learning Python as a Cloud Engineer, DevOps Engineer, Platform Engineer and SRE is essential for advancing in your career, as it empowers you to streamline and automate various tasks and tools integral to the DevOps/automation workflow.
According to a recent survey of Python developers by JetBrains 34% of Python is used for DevOps/System Administration/writing Automation Scripts
Table of Contents
Python for Cloud Engineers
Python is a popular and powerful programming language that’s widely used in cloud computing.
Cloud engineers can leverage Python for a variety of tasks, making it a valuable skill to have in this field.
Infrastructure as Code (IaC):Python with tools like Terraform lets you automate cloud infrastructure provisioning and management on platforms like AWS, Azure, and GCP. No more manual configuration.
Infrastructure as Code (IaC):Learn about tools like Ansible (which uses YAML but can be extended with Python) and Terraform.
Cloud APIs:Cloud Providers’ SDKs: AWS Boto3, Google Cloud’s Python Client, Azure SDK for Python can be used to manage and automate cloud resources.
Cloud APIs:Interact with cloud provider APIs using Python libraries like Boto3 (AWS) or Azure SDK to automate tasks like scaling resources or managing deployments.
Real time tasks using Python for Cloud Engineers
- We can automate repetitive tasks in cloud environments, such as deploying applications, scaling resources, and managing configurations.
- Write Python scripts to process and analyze cloud logs generated by resources and applications,
- Write Python scripts to define custom metrics and alerts based on cloud resource data,
Python for DevOps Engineers
DevOps Engineers:Automation Extravaganza: Automate all the things! Python excels at scripting repetitive tasks like server provisioning, configuration management, and application deployments using tools like Ansible.
CI/CD Pipelines:Integrate Python scripts into your CI/CD (Continuous Integration/Continuous Delivery) pipelines for seamless and automated testing and deployment processes.
Real time tasks using Python for Cloud Engineers
- Python is commonly used for monitoring and logging in DevOps. psutil, interfaces and CPU info are other prominent monitoring libraries.
- A DevOps engineer can use Python scripts to automate the deployment of applications, configure infrastructure, and perform repetitive tasks such as backups or log analysis. Python is a popular choice for automation tasks because it has a rich set of libraries and is easy to learn and use.
- Python to automate the CI/CD pipeline, which involves building, testing, and deploying software applications. Popular CI/CD tools like Jenkins, GitHub Actions, GitLab allow developers to write custom scripts in Python to customize the pipeline.
- Python to analyze logs and metrics collected from various sources, such as application servers, databases, or network devices. Python libraries like Pandas or NumPy are popular for data analysis and can be used to extract insights and trends from large volumes of data.
Python for Platform Engineers
Platform Engineers:Building Self-Service Platforms: Develop internal developer portals or self-service platforms with Python frameworks like Flask or Django. This allows developers to easily provision resources and deploy applications themselves.
Platform Management:Automate platform health checks, resource monitoring, and access control using Python scripts.
Python for SRE(Site Reliability Engineer)
Monitoring and Alerting:Python is fantastic for writing scripts to monitor system health, analyze logs, and trigger alerts for potential issues before they snowball.
Scalability and Performance:Write Python scripts to automatically scale cloud resources based on traffic or performance metrics, ensuring smooth operation under load.
Python for Version Control and CI/CD
Git Automation:Use libraries like GitPython to automate Git operations.
CI/CD Integration: Familiarize yourself with Python clients for Jenkins, CircleCI, or TravisCI.
Python for Containerization & Orchestration
Docker SDK for Python:Python helps in automating Docker operations like install docker, deploy docker image and clean unused docker images periodically.
Kubernetes Python Client:For automating tasks in Kubernetes clusters.
Write Python scripts to interact with the Kubernetes API using libraries like kubernetes to deploy,scale,update, and delete various Kubernetes resources like deployments, pods, services, and ingresses.
Perform CRUD (Create,Read, Update, Delete) operations on Kubernetes resources programmatically, allowing for automated provisioning and management.
Develop Python scripts to monitor the health of pods and deployments,triggering horizontal pod autoscaling (HPA) based on defined metrics.
Python for Networking
Socket:Understand the basics of network programming in Python.
Automate network tasks:especially if you work with tools like Cisco’s network automation tools or use Netmiko for SSH connections to routers and switches.
Python for Databases
Learn to interact with databases using Python, whether it’s SQL databases (using libraries like SQLAlchemy) or NoSQL databases.
Python scripts can automate repetitive database tasks,
Many web frameworks use Python and databases together.
Python for Automation
Scripting: Write scripts to automate regular tasks. Learn about command-line arguments, working with external processes, and automation tools.
Python Libraries for DevOps: – os and sys: Basic operating system interactions.
Subprocess: To spawn new processes, connect to their input/output/error pipes, and obtain their return codes. – Paramiko: For SSH-based interactions and HTTP requests.
Why Learning Python is important for Cloud, DevOps, Platform and SRE
As we have checked on Job Portal Python is must skill for Cloud Engineers, DevOps Engineers, Platform Engineers and SRE (Site Reliability Engineer).


Python Modules for Cloud, DevOps, Platform and SRE
- Boto3
- Google Cloud Client Libraries for Python
- Azure SDK for Python
- Django
- Flask
- FastAPI
- os and sys
- requests
- Fabrics
- PyYAML
- JSON
- psutil
- Jinja2
Real time Python tasks for Cloud, DevOps, Platform and SRE
- Python AWS Lambda to start and stop aws resources in non business hour
- Writing custom scripts or modules to automate infrastructure provisioning and configuration tasks using libraries like Boto3 for AWS or Azure SDK for Python.
- Python with AWS -Create S3 bucket, upload and Download File using Boto 3
- GitHub and JIRA integration with Python
- Find error logs and http response code using Python
- Database backup and restore using Python
- Write Python Scripts to interact with Kubernetes API using token, certificates, etc.
- Developing automation scripts or integrating with CI/CD platforms (e.g., Jenkins, GitHub Actions, GitLab CI/CD) to automate build, test, and deployment processes.
- Writing custom Python custom monitoring scripts or agents to collect metrics and logs from various sources.
- Integrating with security tools like Nessus, Qualys, or AWS Security Hub to automate security assessments and compliance checks.
- Many more…
Where is Python used in Real world?
YouTube: A Python application plays a critical role in delivering YouTube content.
Quora:Python is the foundation of Quora’s technology.
Snapchat:Python powers the vast majority of Snapchat’s backend.
Instagram:Instagram leverages Python extensively for its functionalities.
Facebook:Python supports various backend applications at Facebook.
Linux Servers:The ubiquitous presence of Python scripts is evident in Linux startup and management tools, which are the backbone of the World Wide Web.
Machine Learning Research:Python is a popular choice for machine learning research projects worldwide
How should I start learning Python?/ Python Learning Roadmap
Learning Python is easy but same time there is chance of missing the proper learning track. So, to learn Python programming or Programming with Python, you must follow a proper tutorial.You can learn Python using below syllabus/Python Course Content.
1.Python Fundamentals:
- Introduction to Python:Cover the basics of Python syntax, data types (strings, integers, lists, dictionaries), variables, operators, and control flow statements (if/else, for loops, while loops).
- Functions and Modules: Explain how to define and use functions for code reusability, explore built-in modules (like os, sys, json) and introduce package management with pip.
- Command Line Interface (CLI) Scripting:write Python scripts that interact with the operating system using the os module, automate tasks like file manipulation, process execution, and environment variable management.
- Version Control with Git: Integrate Git version control basics into the course, demonstrating how to manage Python scripts and DevOps configurations using Git commands.
- Configuration Management with Python: Introduce tools like Ansible or SaltStack that leverage Python for infrastructure and application configuration management.
2.Python for DevOps:
Command Line Interface (CLI) Scripting:write Python scripts that interact with the operating system using the os module, automate tasks like file manipulation, process execution, and environment variable management.
Version Control with Git: Integrate Git version control basics into the course, demonstrating how to manage Python scripts and DevOps configurations using Git commands.
Configuration Management with Python: Introduce tools like Ansible or SaltStack that leverage Python for infrastructure and application configuration management.
3.Python for Cloud Automation:
Cloud APIs and SDKs: Focus on using Python libraries like Boto3 (AWS), Google Cloud Python Client Library, or Azure Python SDK to interact with cloud provider APIs for provisioning resources, monitoring services, and automating cloud deployments.
Infrastructure as Code (IaC): Explore tools like Terraform or Pulumi that use Python to define and manage cloud infrastructure through code. Teach students to write IaC scripts for creating and managing virtual machines, storage, networking, and security configurations.
4.DevOps Automation with Python:
Continuous Integration/Continuous Delivery (CI/CD): Demonstrate how to integrate Python scripts into CI/CD pipelines using tools like Jenkins or GitLab CI/CD. Students can write scripts for building, testing, and deploying applications.
Monitoring and Alerting: Show how to use Python libraries to process and analyze logs generated by cloud resources and applications, enabling the creation of custom monitoring dashboards and automated alerts for potential issues.
Testing and Debugging: Introduce Python testing frameworks like unittest or pytest for writing unit tests to ensure the functionality of DevOps scripts. Cover basic debugging techniques for troubleshooting Python code.
5.Advanced Topics (Optional) on Python:
Web Scraping with Python: For tasks that require data extraction from websites, introduce libraries like BeautifulSoup or Scrapy to write Python scripts for web scraping.
Data Processing with Python: Briefly cover libraries like Pandas and NumPy for data manipulation and analysis, which can be helpful for processing cloud-based data.
Security Automation with Python: For security-focused DevOps engineers, introduce Python libraries and tools for automating security tasks like vulnerability scanning and access control management.
6.Additional Tasks on Python:
Hands-on Labs: The course should incorporate plenty of hands-on labs where students can practice writing Python scripts for real-world DevOps scenarios.
Project-based Learning:Build a complete DevOps automation solution using Python scripts and integrate it with their existing infrastructure or cloud platform.
Version Control Integration: Throughout the course, emphasize the importance of using Git for version control of Python scripts and DevOps configurations.
If you want to take any paid courses to Learn Python for Cloud, DevOps, Platform and SRE Tasks, we recommend below courses
100 Days of Code: The Complete Python Pro Bootcamp
Conclusion:
We have covered why Python Learning is must for Cloud Engineers, DevOps Engineers, Platform Engineers and SRE (Site Reliability Engineer).
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