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All Practice Series

Introduction This is a comprehensive page about the technologies I have shared in series format. You can view brief introductions and links to directly access each series you are interested in. In the field of software development, to deploy a product from the initial idea to its release, the standard process typically involves several stages as follows: Database : Designing and implementing the database according to business requirements, storing data during the system's operation. Backend : Handling the main logic of the system, communicating with the database and services. Frontend : Building the interface for users to interact with the system, which could be a desktop, mobile, or web application. This usually includes implementing UI/UX and integrating APIs from the backend. DevOps : Deploying the system for use, which can be done on a server or in the cloud. Testing : Applying testing methods to ensure the product meets the standards for release. Of course, these are just stan...

Kubernetes Deployment for Zero Downtime

Introduction In Kubernetes (K8s) , a Pod is the smallest resource unit used to run one or more containers during deployment. There are several ways to create a Pod : you can create it directly, use a ReplicationController , or a ReplicaSet . However, the most commonly used resource for managing Pods is the Deployment . When you use a Deployment , it actually creates a ReplicaSet to manage the Pods but comes with many additional benefits that support the deployment process. Some Advantages of Deployment : Ensures Pod Availability : It guarantees that the specified number of Pods are always running according to the configuration, automatically deploying additional Pods if any failures occur. Supports Restart and Undo Deployment : Allows you to easily restart or roll back to previous versions of your Deployment . Zero Downtime Deployment : When updating configurations or scaling Deployments , zero downtime is crucial. This means that new Pods are created while the old Pods are stil...

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 ...

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 Reconciliation. State management : redux, mobx, recoil, zustand, xstate, etc. Middleware libraries : redux-thunk, redux-saga, redux-observable, etc. Popular packages : tasnstack query, immer, styled-components, etc. Rendering te...

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...

Helm for beginer - Deploy nginx to Google Kubernetes Engine

Introduction Helm is a package manager for Kubernetes , which simplifies the process of deploying and managing applications on Kubernetes clusters. Helm uses a packaging format called charts , which are collections of files that describe a related set of Kubernetes resources. Key Components of Helm Charts : Helm packages are called charts. A chart is a collection of files that describe a related set of Kubernetes resources. A single chart might be used to deploy something simple, like a memcached pod, or something complex, like a full web app stack with HTTP servers , databases, caches, and so on. Values : Charts can be customized with values, which are configuration settings that specify how the chart should be installed on the cluster. These values can be set in a ` values.yaml ` file or passed on the command line. Releases : When you install a chart, a new release is created. This means that one chart can be installed multiple times into the same cluster, and each can be indep...

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...

DevOps Practice Series

Introduction DevOps is a combination of development (Dev) and operations (Ops), aimed at uniting people, processes, and technology to enhance the software development lifecycle. Here are some key aspects of DevOps: Collaboration and Communication: DevOps fosters a culture where development, IT operations, quality engineering, and security teams work together seamlessly. Continuous Integration and Continuous Delivery (CI/CD): These practices automate the integration and delivery of code changes, ensuring faster and more reliable software releases. Infrastructure as Code (IaC): This approach involves managing and provisioning computing infrastructure through machine-readable scripts, rather than physical hardware configuration. Monitoring and Logging: Continuous monitoring and logging help teams to detect issues early and maintain system reliability. Automation: Automating repetitive tasks reduces errors and increases efficiency, allowing teams to focus on more strategic work. By impleme...

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...

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Build Charts with NextJS and D3.js

Introduction D3.js (Data-Driven Documents) is a powerful JavaScript library for producing dynamic, interactive data visualizations from numerical data. Instead of providing pre-built charts, D3 offers low-level tools that allow you to manipulate DOM elements directly (typically SVGs, Canvas, or HTML). The advantages: Infinite Customization: You can create any type of chart you can imagine. High Performance: Smoothly handles large data sets and animated transitions. Strong Mathematical Ecosystem: Fully supports scale calculation functions, coordinate axis formatting, and complex geometric algorithms. Detail First, let's start with a simple example of drawing a line chart that describes monthly revenue during the year. Please create the file app/api/revenue/route.ts to simulate a 12-month revenue api with a random amount from 1000-6000 import {NextResponse} from 'next/server' export async function GET () { const data = Array. from ({ length: 12 }, ( _ , i ) => ...

CSRF Anti-Attack Guide

Introduction CSRF (Cross-Site Request Forgery) is a type of attack targeting user sessions. Attackers trick the victim's browser into sending requests (accompanied by identification cookies) to websites where they are logged in without permission. To prevent CSRF, we have 3 main strategies: Method 1 : Check Origin / Referer headers Check if the Origin or Referer header matches the server domain. If they differ, block them immediately at the NextJS Proxy layer before forwarding to the server. Method 2 : Configure SameSite for Cookies When setting cookies for the client, you must set the SameSite=Strict or SameSite=Lax attribute. In this case, if the request originates from a different website, the browser will refuse to attach the Cookie, NextJS receives an empty request and will return a 401 Unauthorized error. Method 3 : Use CSRF Token Require the client to send a Token (generated randomly for each user or using JWT) in the Header. Since a fake site cannot have this token, the out...

Guide to Setting Up CI/CD for NextJS with Jenkins, Gitlab and AWS ECS

Introduction In the previous article, I provided instructions on setting up CI/CD with Jenkins and Gitlab to deploy a NestJS project to AWS EKS. Now, I will provide similar guidance for deploying a project using the NextJS framework to AWS ECS, triggering an auto build on Jenkins when pushing code to Gitlab, and running tests for the project before deployment. A summary of the steps involved will be as follows: Build the Docker image for the NextJS project and push it to AWS ECR. Deploy that Docker image to AWS ECS. Set up Jenkins to connect with Gitlab. When code is pushed to Gitlab, Jenkins will trigger an auto build of the steps defined in the Jenkinsfile, including: Pulling the new code from Gitlab. Running tests for the project. If the test fails, stop the deployment process. If the test passes, proceed to the next step. Building the Docker image with the new code and pushing it to AWS ECR. Deploying to AWS ECS by restarting the service, which will use the latest Docker image to d...

Kubernetes Deployment for Zero Downtime

Introduction In Kubernetes (K8s) , a Pod is the smallest resource unit used to run one or more containers during deployment. There are several ways to create a Pod : you can create it directly, use a ReplicationController , or a ReplicaSet . However, the most commonly used resource for managing Pods is the Deployment . When you use a Deployment , it actually creates a ReplicaSet to manage the Pods but comes with many additional benefits that support the deployment process. Some Advantages of Deployment : Ensures Pod Availability : It guarantees that the specified number of Pods are always running according to the configuration, automatically deploying additional Pods if any failures occur. Supports Restart and Undo Deployment : Allows you to easily restart or roll back to previous versions of your Deployment . Zero Downtime Deployment : When updating configurations or scaling Deployments , zero downtime is crucial. This means that new Pods are created while the old Pods are stil...

Using PureComponent and React.memo to improve Performance in React

Introduction PureComponent in React is built on the concept of Pure Function. In this article, let's dive into PureComponent and the memo hook in React, as well as how to apply these tools to improve performance in React applications. What is a Pure Function? First off, it's important to understand the concept of a Pure Function, which will always return the same result with the same input parameters. To put it simply, the same input will always yield the same output. For example: // this is pure function function sum ( a : number , b : number ): number { return a + b ; } sum ( 1 , 2 ); // always return 3 const offset = 3 ; // this is not pure function function sumWithOffset ( a : number , b : number ): number { return a + b + offset ; } sum ( 1 , 2 ); // result depend on offset value What is a Pure Component? In React, a PureComponent is considered a component that only renders when there's a change in props or state, where the change in props or state is det...

Using D3 and Canvas to Visualize Data on NextJS

Introduction In the previous article, I introduced how to use D3 to visualize data as charts. For most chart visualization needs, using D3 to create individual HTML DOM elements is sufficient. However, if you need to build a web application with superior performance to handle complex cases with relatively large datasets, then applying Canvas is a good solution for you Canvas is an HTML5 element that allows for extremely high-performance 2D graphic drawing via JavaScript. Unlike SVG, which creates separate DOM elements for each object, Canvas operates as a "blank canvas" where pixels are drawn directly onto a single surface. For instance, in real-world products like Figma, Canva, and TradingView, they all utilize Canvas to handle complex graphical operations. Outstanding advantages of Canvas include: superior render speed when processing thousands of objects simultaneously, memory resource savings as it does not increase the size of the DOM tree, and flexible customization for...

Using mlx-lm to run local LLM

Introduction mlx-lm is a library designed by Apple to optimize running Large Language Models directly on Apple Silicon chips. Compared to Ollama, mlx-lm has superior performance advantages due to its ability to directly access Unified Memory and maximize the power of Apple GPUs, resulting in faster processing speeds and better energy efficiency for Mac users. Prerequisites Because mlx-lm was developed specifically for Apple Silicon chips, the following instructions are only applicable if you are using an Apple computer. Detail First, install mlx-lm pip install mlx-lm Then, visit this HuggingFace page of the mlx community . This is a reputable page sharing LLMs that have been converted from GGUF to MLX to be suitable for running on Macs with Apple Silicon chips. You can search for models that fit your usage needs and machine configuration. Here, I will use the model mlx-community/Qwen2.5-Coder-7B-Instruct-4bit. The model name mlx-community/Qwen2.5-Coder-7B-Instruct-4bit consists of th...

Deploying a Golang Application to Google Kubernetes Engine

Introduction In this article, I will guide you through deploying a Golang Application to Google Kubernetes Engine ( GKE ). Previously, I wrote an article about deploying a NodeJS Application to GKE , which you can refer to for some basic information before continuing. Steps to Follow The process is quite similar to deploying a NodeJS Application and includes the following steps: Create a Golang Application Build a Docker image Push the Docker image Deploy the Docker image to GKE You will notice that when working with Kubernetes , the main difference is in the step where you build the Docker image. Depending on the application you need to deploy, there are different ways to build the Docker image . However, the common point is that once you build the Docker image , you have completed almost half of the process. This is because the subsequent steps involving Kubernetes are entirely the same. Detailed Process 1. Create a Golang Application In this step, you can either use an existin...

Using Nginx on Docker

Introduction Nginx is a popular open-source web server known for its superior performance compared to the Apache web server. Nginx supports various functionalities, including deploying an API gateway (reverse proxy) , load balancer , and email proxy . It was initially developed to build a web server capable of efficiently handling 10,000 concurrent connections with low memory usage. Run Nginx with Docker To use Nginx with Docker , simply execute the following command: docker run -dp 8080:80 nginx:alpine By default, Nginx uses port 80 , but you can map it to a different port if needed. Custom Nginx Configuration To customize the Nginx configuration, first, create a ` docker-compose.yml ` file with the following content: services : serviceName : image : nginx:alpine ports : - 8080:80 volumes : - ./default.conf:/etc/nginx/conf.d/default.conf - ./index.html:/usr/share/nginx/html/index.html In the ` volumes ` field, note that I have mapped two file...

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