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Kubernetes Practice Series

Introduction Kubernetes (often abbreviated as K8s ) is an open-source system designed to automate the deployment, scaling, and management of containerized applications. This page serves as a collection of articles related to Kubernetes (K8s) , including theoretical concepts and practical guides on using Kubernetes to set up essential tools for the software development process. I will continue to update this series with new articles as ideas come to mind, to ensure the series becomes more comprehensive. The articles are arranged in increasing order of difficulty to make it easier for you to follow. If you have time, it's recommended that you start from the beginning of the series to acquire the necessary knowledge and information that will prepare you for the subsequent articles. Key Topics Covered in This Series Basic Knowledge : Fundamental concepts, common commands, etc. Resources : Pod, Deployment, Service, StatefulSet, Ingress, etc. Pod Autoscaler : Horizontal and Vertical sc

Docker Practice Series

Introduction Docker is an open platform for developing, shipping, and running applications. This page is dedicated to compiling articles related to Docker , covering both the theoretical aspects and practical applications of Docker in setting up popular tools essential for software development. I will be updating this series with more articles in the future as new ideas for topics arise. The articles are arranged in increasing order of difficulty, making it easier for you to follow along. If you have the time, I recommend starting from the beginning of the series to ensure that you grasp the necessary knowledge and information needed for the more advanced articles later on. Here are some key topics in the series that you need to explore to effectively use Docker : Basic knowledge Docker commands Docker Compose Building Docker images Performance improvement Integration with CI/CD Once you have a solid understanding of the foundational knowledge, the extended topics (including advanced

NodeJS Practice Series

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

React Practice Series

Introduction React is a JavaScript library created by Facebook , often referred to as the most popular frontend framework today. This page aims to gather articles related to ReactJS , covering topics such as theory, features, and commonly used packages in the process of building ReactJS applications. I will update this series with more articles in the future as new ideas for content come up. The articles are arranged in increasing order of difficulty, so if you have time, it's recommended to start from the beginning of the series. This will ensure you grasp the essential knowledge and information needed for the subsequent articles. Here are some key topics in the series that you need to explore to effectively use ReactJS : Fundamental : React Hook, React Context, Lazy load, etc. State management : redux, mobx, recoil, etc. Middleware libraries : redux-thunk, redux-saga, redux-observable, etc. Popular packages : react-query, immer, styled-components, etc. Rendering techniques : C

Setting up Kubernetes Dashboard with Kind

Introduction In a previous article, I guided you through using Helm to deploy on Google Kubernetes Engine . However, if you want to cut down costs by using Kubernetes in your local environment instead of relying on a cloud provider during development, then Kind is your go-to. There are several tools to help set up Kubernetes locally, such as MiniKube , Kind , K3S , KubeAdm , and more. Each tool has its own pros and cons. In this article, I'll walk you through using Kind to quickly set up a Kubernetes cluster on Docker . Kind stands out for its compactness, making Kubernetes start up quickly, being user-friendly, and supporting the latest Kubernetes versions. Working with Kind Firstly, follow the instructions here to install Kind according to your operating system. If you're using Ubuntu , execute the command: [ $( uname -m ) = x86_64 ] && curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.23.0/kind-linux-amd64 chmod +x ./kind sudo mv ./kind /usr/local/bin/ki

Deploying a NodeJS Server on Google Kubernetes Engine

Introduction to GKE Google Kubernetes Engine (GKE) is a managed Kubernetes service provided by Google Cloud Platform , facilitating simple and efficient deployment of Docker images. We only need to provide some configuration for the number of nodes, machine types, and replicas to use. Some Concepts Cluster A Cluster is a collection of Nodes where Kubernetes can deploy applications. A cluster includes at least one Master Node and multiple Worker Nodes . The Master Node is used to manage the Worker Nodes . Node A Node is a server in the Kubernetes Cluster. Nodes can be physical servers or virtual machines. Each Node runs Kubernetes , which is responsible for communication between the Master Node and Worker Node , as well as managing Pods and containers running on it. Pod A Pod is the smallest deployable unit in Kubernetes . Each Pod contains one or more containers, typically Docker containers. Containers in the same Pod share a network namespace, meaning they have the same

Create API Gateway with fast-gateway

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

Explaining Async/Await in JavaScript in 10 Minutes

Introduction For a long time, we've relied on callbacks to deal with asynchronous code in JavaScript. As a result, many of us have faced dreadful experiences dealing with deeply nested functions ( callback hell ). Callback hell Callbacks come with a lot of drawbacks. When we have multiple asynchronous operations, callbacks have to wait for each other to execute, prolonging the completion time. Additionally, writing nested callbacks makes our code messy and hard to maintain. In the ES6 (ECMAScript 2015) version, JavaScript introduced Promises. This was a fantastic replacement for callbacks and was quickly embraced by the community. Our new code looks similar to the old one, making it easier to follow and maintain. However, the issues with callbacks weren't completely resolved. Since the ES7 (ECMAScript 2016) version, Async/Await has been added to make asynchronous code in JavaScript look and feel easier to use. What is Async/Await? Async/Await is a feature of JavaScript that

A Handy Guide to Using Dynamic Import in JavaScript

Introduction In JavaScript, when we import a file, the process usually happens synchronously, known as static import. However, as our applications grow, this synchronous loading can lead to slower initial page loads due to larger JavaScript bundles. Moreover, there are times when imports are necessary only under specific circumstances, leading to unnecessary loading times for users who might not even utilize those features. Details Instead of burdening all users with unnecessary imports, dynamic imports come to the rescue. They allow us to load modules or files only when they are needed, thus improving performance and user experience. Dynamic imports are invoked using the import() function and return a promise. When using default exports, the exported data can be accessed through the default field, while other data can be accessed through fields with matching names. Here's how you can use dynamic imports: import ( "ramda" ). then ( module => { const moduleDefaul

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Automating Server Configuration with Ansible

Introduction Ansible is an open-source IT automation tool written in Python . It's widely used for configuration management, making complex tasks simpler by automating system setup, software deployment, and more. Ansible is agentless , meaning it doesn't require an agent to communicate with other machines. It supports a wide range of operating systems, platforms, and devices, from Ubuntu and VMware to CentOS , Windows , Azure , AWS , and network devices like Cisco and Juniper . This design increases Ansible's usability because you don't need to install and maintain agents on hosts. This is a significant advantage over similar tools like Chef , SaltStack , and Puppet . Why Choose Ansible? Here are some reasons to choose Ansible over other configuration management tools: Open Source : It's free to use. Uses SSH : Easily connects directly to servers. Lightweight : Easy to set up and doesn't consume many resources. Readable Syntax : Uses YAML for scripts, ma

Deploying a NodeJS Server on Google Kubernetes Engine

Introduction to GKE Google Kubernetes Engine (GKE) is a managed Kubernetes service provided by Google Cloud Platform , facilitating simple and efficient deployment of Docker images. We only need to provide some configuration for the number of nodes, machine types, and replicas to use. Some Concepts Cluster A Cluster is a collection of Nodes where Kubernetes can deploy applications. A cluster includes at least one Master Node and multiple Worker Nodes . The Master Node is used to manage the Worker Nodes . Node A Node is a server in the Kubernetes Cluster. Nodes can be physical servers or virtual machines. Each Node runs Kubernetes , which is responsible for communication between the Master Node and Worker Node , as well as managing Pods and containers running on it. Pod A Pod is the smallest deployable unit in Kubernetes . Each Pod contains one or more containers, typically Docker containers. Containers in the same Pod share a network namespace, meaning they have the same

Docker Practice Series

Introduction Docker is an open platform for developing, shipping, and running applications. This page is dedicated to compiling articles related to Docker , covering both the theoretical aspects and practical applications of Docker in setting up popular tools essential for software development. I will be updating this series with more articles in the future as new ideas for topics arise. The articles are arranged in increasing order of difficulty, making it easier for you to follow along. If you have the time, I recommend starting from the beginning of the series to ensure that you grasp the necessary knowledge and information needed for the more advanced articles later on. Here are some key topics in the series that you need to explore to effectively use Docker : Basic knowledge Docker commands Docker Compose Building Docker images Performance improvement Integration with CI/CD Once you have a solid understanding of the foundational knowledge, the extended topics (including advanced

Kubernetes Pod Cheatsheet

Introduction This article is here to guide you on using Pod in Kubernetes . I'll give you some concepts and commands that Kubernetes often uses to handle Pod . Pod Introduction A Pod is the smallest deployable unit in Kubernetes . Here are some key points about Pods: Multiple Containers : A Pod can contain more than one container, and there's no limit to how many containers you can run inside a Pod. These containers are relatively tightly coupled and share resources such as disk. Shared Resources : All the containers inside a Pod are connected via localhost and share the same memory space. They also share storage (volumes), IP address, and configuration information. Unique IP Address : Each Pod gets a unique IP address. Ephemeral Nature : Pods are ephemeral in nature; they can be created, deleted, and updated. Prerequisites Before we begin, make sure you have the following: For Kubernetes systems, you can use minikube or have permissions to provision resources on cloud pro

Monitoring with cAdvisor, Prometheus and Grafana on Docker

Introduction Monitoring a system is crucial after deploying a product to a production environment. Keeping an eye on system metrics like logs , CPU , RAM , disks , etc, helps identify the system's status, performance issues, and provides timely solutions to ensure stable operations. While cloud providers like Google , Amazon , or Azure offer built-in monitoring systems, if your company needs to manage multiple applications/systems/containers and desires a centralized monitoring system for easier management, using cAdvisor , Prometheus , and Grafana is a sensible choice. These three popular open-source tools are widely used by DevOps teams, especially for monitoring container applications. cAdvisor Developed by Google , cAdvisor is an open-source project used to analyze resource usage, performance, and other metrics from container applications, providing an overview of all running containers. Find more details here Prometheus Prometheus is a toolkit for system monitoring and a

Kubernetes Practice Series

Introduction Kubernetes (often abbreviated as K8s ) is an open-source system designed to automate the deployment, scaling, and management of containerized applications. This page serves as a collection of articles related to Kubernetes (K8s) , including theoretical concepts and practical guides on using Kubernetes to set up essential tools for the software development process. I will continue to update this series with new articles as ideas come to mind, to ensure the series becomes more comprehensive. The articles are arranged in increasing order of difficulty to make it easier for you to follow. If you have time, it's recommended that you start from the beginning of the series to acquire the necessary knowledge and information that will prepare you for the subsequent articles. Key Topics Covered in This Series Basic Knowledge : Fundamental concepts, common commands, etc. Resources : Pod, Deployment, Service, StatefulSet, Ingress, etc. Pod Autoscaler : Horizontal and Vertical sc

Using Google Cloud Run to Deploy Docker Image

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

Installing PostgreSQL with Docker

Introduction In this guide, I'm going to walk you through installing PostgreSQL database and pgAdmin using Docker . The big advantage here is it's quick and straightforward. You won't need to go through a long manual installation process (and potentially spend time fixing errors if they arise). Installing Docker If you don't already have Docker installed on your machine, you'll need to do that first. At this step, you'll need to search Google because the installation process depends on the operating system you're using. Typically, installing Docker on Windows is simpler compared to using Ubuntu . Installing PostgreSQL Once Docker is set up, the next step is to install the PostgreSQL image. Here, I'm using postgres:alpine , which is a minimal version of PostgreSQL (it's lightweight and includes all the essential components needed to use PostgreSQL). docker run -- name postgresql - e POSTGRES_USER ={ username } - e POSTGRES_PASSWORD ={ passw

Github CI/CD with Google Cloud Build

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

Setup Gitlab CI

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

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