DevOps

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Deploying a Custom HTTPD Image with Your Own Web Content Using Jenkins Github Webhooks

In this article, we’ll guide you through deploying a custom HTTPD (Apache) Docker image containing your own web content using a Jenkins Freestyle project. This setup allows for easy automation and deployment every time you update your web content in a GitHub repository. Prerequisites Before we begin, ensure you have: - A GitHub account and a repository for your web content. - Jenkins installed and running. - Docker installed on your Jenkins server. - Basic knowledge of Docker and Jenkins. Step 1: Prepare Your Web Content 1. Create Your Web Content: - On your local machine, create a directory for your web content. - Inside this directory, create an `index.html` file or any additional files you want to serve. <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>My Custom Web Page</title&g

Setting Up a Custom HTTPD Server on Kubernetes with Minikube on Ubuntu

In this article, we’ll walk through the steps to set up a Kubernetes cluster on Ubuntu using Minikube and deploy a custom Apache HTTP server (`httpd`) with your own `index.html` file. Whether you’re a beginner or just looking to refresh your skills, this guide will help you get started with Kubernetes and Docker. What You’ll Need - An Ubuntu system - Basic knowledge of the command line - Installed tools: `curl`, `apt-transport-https`, `virtualbox` (or another virtualization tool) Step 1: Prepare Your Environment First, let’s ensure your system is up-to-date and has the necessary packages. sudo apt update sudo apt upgrade -y sudo apt install -y curl apt-transport-https virtualbox Step 2: Install Minikube Minikube is a tool that makes it easy to run Kubernetes locally. Here’s how to install it: 1. Download the Minikube binary: curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 2. Install Minikube: sudo install minikube-linux-amd64 /usr/local/bin/m

Docker Volumes

Docker Volumes are a key feature that allow you to persist data generated by and used by Docker containers. Volumes are stored on the host filesystem outside the container's filesystem, so they are not deleted when the container is removed, making them ideal for persisting data like database files, logs, and configuration files. Example: Using Docker Volumes 1. Creating a Simple Container with a Volume Let's create a simple Docker container using the official nginx image and attach a volume to persist data. docker run -d --name my-nginx -v /mydata:/usr/share/nginx/html:ro -p 8080:80 nginx Explanation: -d : Runs the container in detached mode (in the background). --name my-nginx : Names the container my-nginx . -v /mydata:/usr/share/nginx/html:ro : Creates a volume that maps the host directory /mydata to the container directory /usr/share/nginx/html . The :ro option makes this volume read-only inside the container. -p 8080:80 : Maps port 8080 on the host to port 80 in the con

Why DevOps: Addressing Shortfalls of Previous Methodologies

Why DevOps: Addressing Shortfalls of Previous Methodologies DevOps emerged as a response to the limitations of previous software development methodologies, aiming to improve collaboration, automate processes, and accelerate delivery. Here's an exploration of why DevOps became necessary, with explanations of the shortcomings of earlier methodologies using examples and analogies. Traditional Methodologies and Their Shortfalls Waterfall Model Description : A linear and sequential approach where each phase (Requirements, Design, Implementation, Verification, Maintenance) must be completed before the next one begins. Shortfalls : Rigidity : Changes are difficult and costly once a phase is completed. Late Testing : Testing only occurs after the implementation phase, leading to the discovery of major issues late in the process. Customer Feedback : Limited to the beginning (requirements) and end (deployment) phases, risking the final product not meeting user needs. Analogy : Building a h

History of Software Development Methodology

History of Software Development Methodology The history of software development methodology reflects the evolution of processes and practices that guide the creation of software systems. From the early days of ad hoc programming to the structured and iterative methods of today, software development methodologies have continually evolved to address the growing complexity and demands of software projects. Early Approaches (1950s - 1960s) Ad Hoc Development : Early software development in the 1950s and 1960s was often informal and lacked structured processes. Programs were typically written by a single developer or a small team, with little emphasis on planning, documentation, or formalised testing. Structured Programming : Introduced in the late 1960s, structured programming aimed to improve the clarity, quality, and development time of software. Promoted by Edsger Dijkstra, it emphasised the use of control structures like loops and conditionals, and the avoidance of "goto" s