The AWS Builder

  🚀 Introduction Welcome to Day 8 of the DevOps series! In this lesson, we’ll build something practical: a GitHub repository tracker using just shell scripting and curl . This project introduces you to API integration — one of the most important DevOps skills. By the end of this tutorial, you’ll know how to: Fetch live GitHub data using an API Parse results using a simple tool ( jq ) Automate your report using a cron job 💡 What Is an API? An API (Application Programming Interface) allows two systems to communicate. In our case, we’ll use GitHub’s REST API to ask questions like: “How many ⭐ stars does this repo have?” “How many open PRs or issues exist?” GitHub’s API responds in JSON format — a lightweight data structure we can read easily with jq . 🧰 Prerequisites Before we start: Install curl and jq sudo apt-get install curl jq -y # Ubuntu/Debian curl lets you talk to APIs, and jq helps read JSON data. Know your GitHub repo Example...

  🚀 Introduction Welcome to Day 7 of the DevOps series! In this project, you’ll build a simple AWS Resource Tracker using a few lines of shell scripting and the AWS CLI . This script helps you monitor your AWS account — checking how many EC2 instances , S3 buckets , Lambda functions , and IAM users/roles you currently have. You’ll also learn how to automate it with a cron job so it runs daily and stores a simple report.   🧰 Prerequisites Before starting, make sure you have: AWS CLI installed and configured → aws configure Basic Linux knowledge (creating files, running scripts) IAM permissions with read-only access for EC2, S3, Lambda, and IAM 💻 Step 1: Create the Script Create a new file named aws_resource_tracker.sh #!/usr/bin/env bash set -euo pipefail # Default region (update as needed) REGION= " ${AWS_DEFAULT_REGION:-ap-southeast-2} " DATE=$( date +%F) echo "=== AWS Resource Tracker ===" echo "Date: ${DATE} " echo ...

  🚀 Introduction Welcome to Day 6 of the DevOps series! Linux is the foundation of modern DevOps infrastructure — from cloud servers to CI/CD pipelines and containers, nearly every DevOps tool runs on Linux. As a DevOps engineer, mastering Linux and shell scripting helps you: Automate manual tasks Manage servers efficiently Understand logs, permissions, and system resources Integrate scripts into CI/CD pipelines Today, we’ll explore Linux fundamentals, essential shell commands, and scripting basics that every DevOps professional should know. 🧩 What is Linux? Linux is a free and open-source operating system based on UNIX. It is known for its stability, security, and flexibility . 💡 Why Linux in DevOps? Most cloud servers (AWS EC2, Azure VM, GCP Compute) use Linux distributions like Ubuntu , CentOS , or Amazon Linux . Tools like Docker, Kubernetes, Ansible, and Jenkins run best on Linux. You can easily automate infrastructure setup using shell sc...

  🚀 Introduction Welcome to Day 5 of our DevOps series! In Day 4 , we learned how to create virtual machines (EC2 instances) using different automation tools and APIs. Today, we’ll go hands-on with the AWS Command Line Interface (CLI) , explore how to connect to EC2 instances , and walk through AWS CloudFormation templates and drift detection — key skills for any DevOps engineer. 💻 1. AWS CLI Overview The AWS Command Line Interface (CLI) lets you control AWS services directly from your terminal. It’s powerful for automation and scripting. 🧩 Setup Install and configure AWS CLI: aws configure Enter: AWS Access Key ID AWS Secret Access Key Default region (e.g., ap-southeast-2) Output format (e.g., json) Verify: aws sts get-caller-identity 🖥️ 2. Launching an EC2 Instance via CLI Example command: aws ec2 run-instances \ --image-id ami-0abcdef1234567890 \ --count 1 \ --instance-type t2.micro \ --key-name my-keypair \ --security-group-ids sg-...

🚀 Introduction Welcome to Day 4 of our DevOps learning journey! In the previous posts, we explored DevOps fundamentals, the lifecycle stages, and the role of virtualization in improving efficiency. Today, we’ll take it one step further — learning how virtual machines (VMs) are created and managed in AWS and Azure , and how DevOps engineers use different automation tools and APIs to provision them efficiently. ☁️ Understanding the Cloud VM Concept A Virtual Machine (VM) is a software-based computer that runs on physical hardware using a hypervisor. Cloud providers like AWS and Microsoft Azure make it simple to launch and manage VMs (called EC2 instances in AWS and Virtual Machines in Azure) within minutes — without worrying about physical servers. In DevOps, creating VMs automatically through scripts, templates, or code is part of a broader concept called Infrastructure as Code (IaC) — a key principle that enables automation, repeatability, and scalability. 🧱 AWS Free...