Aakib Khan

List of Important components of Dockerfile for DevOps Engineer 😎 !! A Dockerfile is a script with instructions to build a Docker image. Here are the main components explained in simple terms: FROM: This specifies the base image from which your Docker image will be built. Think of it as the starting point. For example, if you're working with Node.js, you might start with a Node base image. Example: FROM node:14 WORKDIR: This sets the working directory inside the container. It’s like creating a folder in which all your work (files, commands, etc.) will happen. Example: WORKDIR /app COPY: This command copies files or folders from your computer (the host) into the Docker image. It’s like dragging files into a folder inside the container. Example: COPY . /app (copies everything from the current folder to /app in the container) RUN: This is used to execute commands inside the Docker image while it’s being built. For example, you can use RUN to install software or dependencies. Example: RUN npm install (installs Node.js packages) CMD: This defines the command that will run when a container is started from your image. You should use CMD to specify the main process (like starting a server). Example: CMD ["node", "app.js"] (runs the app when the container starts) EXPOSE: This tells Docker that your container will use a specific port. It’s like saying, “Hey, I’ll need to use port 3000 to serve my web app.” Example: EXPOSE 3000 ENV: This is used to set environment variables inside the container. These are like settings or configuration values your app might need. Example: ENV NODE_ENV production (sets the environment to "production") ENTRYPOINT: Similar to CMD, but it’s used to configure a container that will run as an executable. It defines the main process and allows you to pass arguments dynamically. Example: ENTRYPOINT ["npm", "start"] In short, the Dockerfile builds an image by following a set of instructions, like choosing a base, copying files, installing dependencies, and defining how the container should behave #Dockerfile #docker #kubernetes

End-to-End CI/CD DevOps with Jenkins, Terraform, Docker, Kubernetes, SonarQube, ArgoCD, AWS EC2, EKS, and GitHub Actions (Django Deployment) blog by Joel wembo Building an end-to-end CI/CD pipeline for Django applications using Jenkins, Docker, Kubernetes, EKS, ArgoCD, GitHub Actions, AWS EC2, and Terraform can be quite a robust setup. In this article, we will guide you through setting up a comprehensive CI/CD pipeline using AWS EC2, AWS EKS, Jenkins, Github actions, Docker, trivy scan, SonarQube, ArgoCD, Kubernetes cluster of your choice, and terraform Technical Guide: End-to-End CI/CD DevOps with Jenkins, Docker, Kubernetes, ArgoCD, Github Actions , AWS EC2 and Terraform by Joel .O Wembo Technical Guide: End-to-End CI/CD DevOps with Jenkins, Docker, Kubernetes, ArgoCD, GitHub Actions, AWS EC2 and Terraform Preface This guide is designed to walk you through the entire process of setting up an end-to-end CI/CD pipeline using a myriad of industry-leading technologies. The Technical Guide is practical, not a theoretical manual, from automating builds and tests to seamlessly deploying your application in a Kubernetes cluster, we cover it all. Whether you’re a seasoned DevOps engineer looking to refine your skills or a developer eager to embrace modern deployment practices, this guide caters to all skill levels. checkout!!! blog link--->https://lnkd.in/gAe-hpdB #devops #cicd #kubernetes

Project 3: Aws DevOps Deployment 😎 #day3 #15days15project challenge Completion Steps → 1. fetch a code from github by git clone https://lnkd.in/dtZ7xDVg 2. Setup AWS CodeCommit: Establish a demo repository and configure essential permissions. 3. push code to code commit using aws CLI 4. Setup AWS CodeBuild: Create a project to build code and seamlessly integrate with your repository 5. Setup S3 Bucket: Configure an S3 bucket for efficient code storage and synchronize with your CodeBuild project 6. Setup AWS CodeDeploy: Create a CodeDeploy application and deployment group for seamless deployment orchestration 7. Setup EC2 Instance: Launch an EC2 instance and install the CodeDeploy agent for smooth deployment operations 8. Setting Up AWS CodeDeploy Agent on Ubuntu EC2 9. Create Deployment: Initiate deployments effortlessly and monitor progress meticulously 10. Setup AWS CodePipeline: Automate the deployment process with a robust pipeline connecting source, build, and deploy stages seamlessly 11. Monitor and Maintain: Regularly assess the health and performance of your application to ensure optimal operation. Project blog link --->https://lnkd.in/dtJHNPAU #kubernetes #docker #devops #python #data #amazon #email #90daysofdevops #90daysofaws #aws #cloud #like #devops #kubernetes #docker #technology #security #help #business #scalability #tensorflow #machinelearning #neuralnetworks #testing #html #javascript #frontend #job #interview