How To Dev

Introduction NodeJS is an open-source and cross-platform JavaScript runtime environment . Here are some key points about NodeJS : V8 Engine : NodeJS runs on the V8 JavaScript engine , which is also the core of Google Chrome . This allows NodeJS to be highly performant. Asynchronous and Non-Blocking : NodeJS  uses an event-driven, non-blocking I/O model. It’s lightweight and efficient, making it ideal for data-intensive real-time applications. Single-Threaded : NodeJS  runs in a single process, handling multiple requests without creating new threads. It eliminates waiting and continues with the next request. Common Language : Frontend developers who write JavaScript for browsers can use the same language for server-side code in NodeJS . You can even use the latest ECMAScript standards without waiting for browser updates. This page is designed to compile articles related to NodeJS , including how to integrate it with various libraries and relevant tech stacks. I will continue to u

Introduction Gitlab is a comprehensive platform designed for software development and version control using git. It provides a user-friendly web interface that enhances the speed of working with git, making it easier to manage Git repositories. Gitlab  offers a range of features including: Free public and private repositories: You can host your code securely and privately or share it with the world. Continuous Integration/Continuous Deployment (CI/CD) : Automate the testing and deployment of your code. Free private docker image storage on Container Registry In this article, I'll guide you on how to push a Docker image to the Gitlab Container Registry and set up CI to automatically build and push Docker images when you push code to a Gitlab repository. Pushing a Docker Image to the Gitlab Container Registry First, you'll need a Gitlab account and a repository (either public or private will work). Use the NodeJS Typescript Server project I introduced earlier , or any proj

Introduction Continuous Integration (CI) : This is the process of building, testing, and performing necessary actions to ensure code quality before it gets merged into the main branch for deployment. Continuous Delivery (CD) : This usually happens after CI and includes steps to deploy the source code to various environments like staging and production . This guide will show you how to set up CI/CD on Github using Google Cloud Build . While Github provides shared runners, if you or your organization have many jobs that need executing during development, setting up your own runner is a better choice. Before proceeding, you should understand some basics about Google Cloud Run to build and deploy Docker images. You can refer to this article for more details: Build Docker image for NodeJS Typescript Server . Setting Up GitHub CI/CD First, create a Github repository. You can choose either a public or private repository. You can use a NodeJS TypeScript application, following my guide o

Introduction Google Cloud Run (GCR) makes deploying a Docker image as easy as running it locally. GCR also includes customizable configuration options for managing services, simplifying the deployment process significantly. Build Docker Image The key step in deploying with a Docker image is successfully building that image. In this guide, we’ll use a NodeJS server Docker image created in this article . Follow the steps to build your Docker image (or use an existing one), and push it to Google Artifact Registry before proceeding. Deploy Docker Image To deploy a Docker image using Google Cloud Run , simply use the following command: gcloud run deploy express-ts --image {docker image} --port {port container} --region {region id} --max-instances {number of instance} --allow-unauthenticated --image : is the link to the Docker image on Google Artifact Registry or Docker Hub --port : is the container port you are exposing --max-instances : is the number of instances

Introduction In this guide, I will walk you through deploying a NodeJS Typescript application to Google App Engine (GAE) . GAE offers a straightforward and quick deployment process for various programming languages. If you're developing your NodeJS app using JavaScript , deploying it is pretty straightforward. However, if you're using Typescript , there's an extra step you'll need to take, which I'll explain here. Prerequisites Before we proceed, ensure you have the following: A Google Cloud account with Google App Engine enabled. The gcloud CLI installed. Creating a NodeJS Typescript Project First, create a file named ` src/main.ts ` with the following content: import express from 'express' const app = express () const port = 8080 app . get ( '/' , ( req , res ) => { res . send ( 'This is NodeJS Typescript Application! Current time is ' + Date . now ()) }) app . listen ( port , () => { console . log ( `Server is runn

Introduction In this article, I will guide you on how to use fast-gateway to deploy a simple API Gateway on NodeJS along with express . The advantage of an API Gateway is that it acts as an intermediary layer to hide the rest of the system, including services, commonly used in Microservices architecture. Example Usage This is the Microservices model after deployment: First, install the package yarn add fast-gateway Next, define the ports that will be used. import * as express from 'express' import * as gateway from 'fast-gateway' const portGateway = 5000 const portService1 = 5001 const portService2 = 5002 Define service 1 as follows: const startService1 = (): void => { const app = express () app . get ( '/list' , ( req , res ) => { const items = [ { id: 1 , name: 'service 1 value 1' , }, { id: 2 , name: 'service 1 value 2' , }, ] re

Introduction to Kafka Kafka is an open-source , distributed messaging system that functions on a publish/subscribe model. It is widely used by numerous large companies for high-performance , real-time data streaming. Developed by LinkedIn since 2011, Kafka has grown into the most popular distributed streaming platform. It can handle vast amounts of records with high efficiency. Advantages of Kafka Open-source : Freely available and continuously improved by a large community. High-throughput, high-frequency : Capable of processing large volumes of data across topics continuously. Automatic message storage : Allows for easy message retrieval and verification. Large user community : Offers extensive support and shared resources. Basic Concepts If you're new to Kafka and Message Queues, here are some key concepts to understand: Producer : Creates and sends data to the Kafka server, where data is sent as messages in byte array format. Consumer : One or more consumers subscribe to