Wednesday, June 24, 2026

AWS Main Concepts (Easy & Beginner Friendly)

1. IAM (Identity and Access Management) 

What it is:
IAM controls who can access AWS and what they can do.

Example:

  • Create users for employees.
  • Give Admin access to managers.
  • Give Read-Only access to interns.

Use Case:
A company allows developers to manage EC2 servers but prevents them from deleting S3 files.



2. EC2 (Elastic Compute Cloud) 

What it is:
EC2 provides virtual servers in the cloud to run applications.

Example:

  • Host a website.
  • Run a web application.
  • Create a Linux server for DevOps practice.

Use Case:
You launch an Ubuntu EC2 instance and deploy your portfolio website.

3. S3 (Simple Storage Service) 

What it is:
S3 stores files, images, videos, backups, and documents securely.

Example:

  • Store website images.
  • Save database backups.
  • Host a static website.

Use Case:
Upload your portfolio website files to an S3 bucket and make it publicly accessible.

4. VPC (Virtual Private Cloud) 

What it is:
VPC creates your own private network inside AWS.

Example:

  • Public subnet for web servers.
  • Private subnet for databases.

Use Case:
Users can access your website, but the database remains hidden from the internet.

5. Security Groups 

What it is:
Security Groups act like a firewall for AWS resources.

Example Rules:

  • Allow HTTP (80)
  • Allow HTTPS (443)
  • Allow SSH (22)

Use Case:
Allow website visitors on port 80 and 443 while only administrators can access port 22.

6. Load Balancer 

What it is:
Distributes incoming traffic across multiple servers.

Benefits:

  • High availability
  • Better performance
  • No single point of failure

Use Case:
10,000 users visit your website. The Load Balancer shares traffic between multiple EC2 servers.

7. Auto Scaling 

What it is:
Automatically adds or removes EC2 servers based on demand.

Example:

  • High traffic → Add servers
  • Low traffic → Remove servers

Use Case:
During a festival sale, Auto Scaling launches extra servers automatically.

8. RDS (Relational Database Service)

What it is:
Managed database service for MySQL, PostgreSQL, MariaDB, etc.

Benefits:

  • Automatic backups
  • Easy maintenance
  • High availability

Use Case:
Store customer information for an e-commerce website without managing database servers manually.

9. Lambda 

What it is:
Runs code without managing servers.

How it works:
Event → Lambda Function → Output

Use Case:
When a user uploads an image to S3, Lambda automatically resizes it.

10. CloudWatch 

What it is:
Monitors AWS resources and applications.

Monitors:

  • CPU usage
  • Memory usage
  • Logs
  • Alarms

Use Case:
Send an alert when EC2 CPU usage exceeds 80%.

11. Route 53 

What it is:
AWS DNS service that connects domain names to AWS resources.

Example:

  • google.com → IP Address
  • mywebsite.com → EC2 Server

Use Case:
Connect your purchased domain name to your website hosted on AWS.

12. CloudFront 

What it is:
Content Delivery Network (CDN) that delivers content faster worldwide.

Benefits:

  • Faster website loading
  • Lower latency
  • Global caching

Use Case:
Visitors from India, USA, and Europe receive website content from the nearest AWS edge location.


Remember:
IAM → VPC → Security Groups → EC2 → Load Balancer → Auto Scaling → RDS → S3 → Lambda → CloudWatch → Route 53 → CloudFront
These are the most important AWS services every AWS Cloud/DevOps beginner should understand first.

User
  ↓
Route 53 (DNS)
  ↓
CloudFront (CDN)
  ↓
Load Balancer
  ↓
Auto Scaling Group
  ↓
EC2 Instances
  ↓
RDS Database

Files & Images → S3
Monitoring → CloudWatch
Permissions → IAM
Network Security → VPC + Security Groups
Automation → Lambda

Python Roadmap For DevOps Engineer

 Simple guide E-Book for Python using in DevOps

Day-01 : Overview of Python in DevOps
Day-02 : Data Types
Day-03 : Keywords and Variables
Day-04 : Functions, Modules and Packages
Day-05 : CLI Arguments & Env Variables
Day-06 : Operators in Python
Day-07 : Condition Handlings
Day-08 : List & Tuples
Day-09 : Loops
Day-10 : Working with Lists
Day-11 : Dictionaries & Sets
Day-12 : File Operations
Day-13 : Boto3 Overview
Day-14 : JIRA Integration
Day-15 : JIRA & GitHub Integration
Day-16 : Basic Interview Questions

— Day 1 —

Overview of Python in DevOps

Overview of DevOps

DevOps is a modern software development culture that focuses on improving collaboration between development and operations teams. Its main goals are automation, continuous integration, continuous delivery (CI/CD), faster releases, and reliable systems. DevOps helps organizations deliver high-quality software quickly and efficiently.

Python in DevOps

Python has become one of the most popular scripting languages for DevOps engineers. Its simplicity, flexibility, and large ecosystem of libraries make it ideal for automation, configuration management, cloud integration, and system monitoring tasks.

Four Pillars of Any Programming Language

  • Keywords — Reserved words that define the structure and logic of the language
  • Data Types — Define the type of data a program can store and process
  • Operators — Used to perform operations on variables and values
  • Logical Reasoning Skills — Ability to think logically and solve problems using code

Key Advantages of Python in DevOps

Ease of Use

  • Python’s simple and readable syntax makes it easy to learn and use for both beginners and experienced DevOps engineers.

Cross-Platform Compatibility

  • Python scripts can run on multiple operating systems such as Linux, Windows, and macOS, ensuring consistency across environments.

Rich Library Ecosystem

  • Python offers extensive libraries for API interaction, infrastructure automation, cloud management, and data handling, making it suitable for many DevOps use cases.

Community and Support

  • Python has a strong global community, providing quick problem-solving, documentation, and access to a wide range of tools and learning resources.

Core Use Cases of Python in DevOps

1. Automation of CI/CD Pipelines

Python is widely used to automate build, test, and deployment stages in CI/CD pipelines.

How it’s used:

  • Trigger builds
  • Run automated tests
  • Manage deployment scripts
  • Interact with CI/CD tools

Tools: Jenkins, GitLab CI, CircleCI

Real DevOps Example:

  • A Python script triggers Jenkins jobs, checks build status, and sends Slack notifications when a deployment fails or succeeds.

2. Infrastructure as Code (IaC)

Python helps in provisioning and managing infrastructure in a repeatable and automated way.

How it’s used:

  • Create EC2 instances
  • Manage VPCs, Load Balancers
  • Automate cloud resource provisioning

Tools: Terraform, AWS Boto3 SDK

Real DevOps Example:

  • A Python script using Boto3 automatically creates EC2 instances and attaches EBS volumes based on demand.

3. Configuration Management

Python ensures consistent configuration across multiple environments (Dev, QA, Prod).

How it’s used:

  • Maintain server configurations
  • Apply configuration changes automatically
  • Reduce configuration drift

Real DevOps Example:

  • Python scripts ensure all Linux servers have the same packages, users, and environment variables.

4. System Monitoring & Alerts

Python scripts monitor system health and send alerts when thresholds are breached.

How it’s used:

  • CPU, memory, disk monitoring
  • Log monitoring
  • Alert generation

Tools: Nagios, Prometheus, Grafana

Real DevOps Example:

  • A Python script checks disk usage every 5 minutes and emails admins if usage exceeds 80%.

5. Log Management and Analysis

Python parses and analyzes logs for errors and performance issues.

How it’s used:

  • Log parsing
  • Error detection
  • Real-time analysis

Real DevOps Example:

  • Python scans application logs and identifies repeated 500 errors, then raises alerts.

6. API Integration

Python interacts with external services through REST APIs.

How it’s used:

  • Cloud service integration
  • Monitoring tools integration
  • Automation via APIs

Services: AWS, Azure, DataDog, Splunk

Real DevOps Example:

  • Python pulls metrics from DataDog API and generates custom performance reports.

7. Cloud Automation

Python automates cloud operations across multiple cloud providers.

How it’s used:

  • Auto-scaling
  • Resource cleanup
  • Deployment automation

Clouds: AWS, Google Cloud, Azure

Real DevOps Example:

  • Python automatically stops unused EC2 instances at night to reduce cloud costs.

8. Container Management and Orchestration

Python helps manage containers and Kubernetes clusters.

How it’s used:

  • Manage Docker containers
  • Interact with Kubernetes APIs
  • Automate deployments

Tools: Docker, Kubernetes

Real DevOps Example:

  • Python script scales Kubernetes pods based on CPU usage.

Tools and Libraries for Python in DevOps

Boto3

  • AWS SDK for Python
  • Automates EC2, S3, RDS, IAM

Example:
Creating EC2 instances automatically.

Ansible

  • Python-based configuration management tool
  • Used for deployment and orchestration

Example:
Deploy applications to multiple servers using Ansible playbooks.

Requests

  • Simplifies API interactions

Example:
Calling cloud APIs to fetch server health status.

Kubernetes Python Client

  • Manages Kubernetes clusters via API

Example:
Scaling pods or restarting failed containers automatically.

Best Practices for Using Python in DevOps

Modularity

  • Write reusable and maintainable scripts.

Error Handling

  • Use try-except blocks for graceful failure handling.

Version Control

  • Use Git to track changes in automation scripts.

Logging and Monitoring

  • Implement logging for debugging and performance tracking.

Security Considerations

  • Never hardcode passwords or API keys.
  • Use environment variables or secret managers.

Steps for Website migration Local to AWS Server using FileZilla

What you need first

From your AWS EC2 instance:

  • Public IP / Public DNS on AWS
  • Key Pair (.pem file or .ppk file)
  • Ubuntu username (usually ubuntu)

STEP 1: Convert .pem to .ppk (for FileZilla) if you have .pem file

FileZilla uses .ppk format, not .pem.

  1. Open PuTTYgen
  2. Click Load → Select your .pem file
  3. Click Save private key
  4. Save it as: my-key.ppk

STEP 2: Open FileZilla & Go to Site Manager

  1. Open FileZilla
  2. Click:
    File → Site Manager → New Site


STEP 3: Configure Your AWS Connection on FileZilla

Enter following details:

Protocol: SFTP — SSH File Transfer Protocol
Host: Your AWS Public IP
Port: 22
Logon Type: Key file
User: ubuntu
Key File: (browse and select .ppk file)


STEP 4: Connected View

After successful connection:

  • Left side → Your local PC
  • Right side → Your AWS Ubuntu server

FileZilla Connected View


STEP 5: Upload Your Website

Two common locations to upload:

Option A: Apache (default)

Upload files to: /var/www/html

Option B: Nginx

Upload files to: /usr/share/nginx/html


Method:

Drag your website folder from left side to right side.

Drag → my-website-folder
To → /var/www/html


STEP 6: Fix Folder Permissions

If you get permission errors, run this on your linux server:

sudo chown -R ubuntu:www-data /var/www/html
sudo chmod -R 755 /var/www/html


STEP 7: Open Your Website

In browser:

http://YOUR_PUBLIC_IP




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