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DevOps
DevOps combines development and operations to automate and streamline software delivery. Python is widely used in Infrastructure as Code (IaC), CI/CD, Configuration Management, Monitoring, Containerization, and Security Automation.
- Infrastructure as Code (IaC)
- CI/CD
- Configuration Management
- Monitoring & Logging
- Containerization & Orchestration
- Security Automation
- DevOps Tools Use Cases
IaC automates infrastructure provisioning (servers, databases, networks) using code. It replaces manual setup with declarative or imperative scripts.
Tool | Description |
---|---|
Terraform | Declarative tool for provisioning cloud resources (AWS, Azure, GCP). |
AWS CloudFormation | Automates AWS infrastructure deployment using YAML/JSON templates. |
Ansible | Automates server configurations, package installations, and cloud deployments. |
Use cases: Automating cloud infrastructure setup (e.g., AWS EC2, S3, databases).
from python_terraform import Terraform
tf = Terraform()
tf.init() # Initialize Terraform
tf.apply(skip_plan=True) # Apply Terraform configuration
- CI (Continuous Integration): Automates code testing and merging.
- CD (Continuous Deployment/Delivery): Automates deployment to staging or production.
Tool | Description |
---|---|
GitHub Actions | Automates testing and deployments directly from GitHub. |
Jenkins | Open-source CI/CD tool for automating builds and deployments. |
GitLab CI/CD | Built-in CI/CD system for GitLab repositories. |
Use cases: Automating code testing and deployment.
.github/workflows/ci.yml
:
name: Python CI/CD Pipeline
on: [push]
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Checkout Code
uses: actions/checkout@v2
- name: Set Up Python
uses: actions/setup-python@v4
with:
python-version: "3.10"
- name: Install Dependencies
run: pip install -r requirements.txt
- name: Run Tests
run: pytest
Manages software, settings, and dependencies across multiple servers. Ensures consistent and reproducible environments.
Tool | Description |
---|---|
Ansible | Automates package installation, server configurations, and deployments. |
Chef | Configuration management tool using "recipes". |
SaltStack | Used for remote execution and system state management. |
Use case: Automating server configurations and deployments.
Ansible Playbook deploy.yml
:
- hosts: web_servers
tasks:
- name: Install Python
apt:
name: python3
state: present
- name: Deploy Application
copy:
src: app.py
dest: /var/www/app.py
Monitoring tracks server health, resource usage, and application performance. Logging stores error messages, events, and audit logs.
Tool | Description |
---|---|
Prometheus | Open-source metrics monitoring for servers and applications. |
Grafana | Visualizes Prometheus metrics on dashboards. |
ELK Stack (Elasticsearch, Logstash, Kibana) | Centralized logging and analytics system. |
Use cases: Tracking errors and system activity.
import logging
logging.basicConfig(filename="app.log", level=logging.INFO)
logging.info("Application started")
Containers package applications and dependencies into lightweight, portable environments. Orchestration automates the deployment and scaling of multiple containers.
Tool | Description |
---|---|
Docker | Packages applications into containers for portability. |
Kubernetes | Manages and scales containers across multiple servers. |
Docker Compose | Simplifies multi-container applications using YAML. |
Use case: Packaging Python applications for deployment.
Dockerfile:
FROM python:3.10
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["python", "app.py"]
Automates security scans, vulnerability detection, and compliance checks. Prevents misconfigurations, weak credentials, and security threats.
Tool | Description |
---|---|
Bandit | Static code analysis for Python security issues. |
Trivy | Scans Docker images for vulnerabilities. |
Vault | Manages secrets and access credentials securely. |
Use case: Detecting security vulnerabilities in Python code.
pip install bandit
bandit -r my_project/
Category | Recommended Tools |
---|---|
Infrastructure as Code (IaC) | Terraform, Ansible |
CI/CD | GitHub Actions, Jenkins, GitLab CI/CD |
Configuration Management | Ansible, Chef, SaltStack |
Monitoring & Logging | Prometheus, Grafana, ELK Stack |
Containerization & Orchestration | Docker, Kubernetes, Docker Compose |
Security Automation | Bandit, Trivy, Vault |
Follow The PEP 8 code format guidelines.
- Environment Configuration
- Data Types & Variables
- Operators
- Control Flow
- Data Structures
- Functions
- Modules & Packages
- File Handling
- Exception Handling
- Object Oriented Programming (OOP)
- Advanced Data Structures
- Decorators
- Generators and Iterators
- Context Managers
- Metaprogramming
- Concurrency and Parallelism
- Networking
- Database Interaction
- Testing
- Web Development
- APIs
- Data Science and Machine Learning
- File and Data Serialization
- Regular Expressions
- ASCII
- DevOps
-
GUI Development
- Tkinter
- PyQt
- Kivy
- PyGame (for game GUIs)
- Best practices for GUI programming
-
Advanced Networking
- Three-way handshake (TCP connection setup)
- Advanced socket programming
- Network security best practices
- Load balancing and scalability
-
Data Structures: Structs
- Struct module in Python
- Defining and using C-style structs
- Memory efficiency and struct packing
-
Secure Python Programming
- Best practices for writing secure Python code
- Avoiding common security vulnerabilities (e.g., injection attacks, insecure imports)
- Secure handling of secrets and environment variables
- Static code analysis for security (e.g., Bandit)
- Secure authentication and authorization practices
- AI/ML
-
Deep Learning: Activation Functions
- ReLU and Leaky ReLU
- Sigmoid, Tanh, and Softmax
- Choosing the right activation function