But this wasn't about wheels. It was about foundations. This is a reflection on a 90-day journey of "persistence"—moving from a local scratchpad to having my architectural insights published on System Weakness and reaching over 2,500 developers globally.

The Problem: The "Running" Fallacy

Most boilerplates in the Node.js ecosystem share a common flaw: they prioritize "getting it running" over "keeping it secure."

I grew weary of seeing production-level projects built on structures that leaked infrastructure details into the business logic. In many popular starters, the Security Ownership was fragmented, and the Core Domain was tightly coupled to specific database ORMs or framework-specific quirks.

I didn't want another "quick start." I wanted an Enterprise-Ready start.

The Struggle: Auditing Every Line in Isolation

The early days were solitary and, quite frankly, tedious. I spent weeks auditing every single line of code in nodejs-quickstart-structure.

My goal was strict Decoupling. I wanted a system where the business logic lived in a pure Core Domain, shielded from the Infrastructure Layer (the databases, external APIs, and even the web framework itself).

Development wasn't without its environmental hurdles. Dealing with WSL 2 on Windows presented its own set of "quirks" that tested my resolve. But these technical frictions were necessary; they forced me to ensure the generator was resilient across different developer environments.

The Breakthrough: Rethinking Stateless Security

The turning point wasn't a code commit, but a realization. While implementing JWT-based authentication, I realized that the industry's obsession with "statelessness" often comes at the cost of security—specifically, the difficulty of token revocation at scale.

I decided to write down my findings in a deep-dive analysis: “The Illusion of Stateless Security: Rethinking JWT Revocation at Scale.”

This wasn't just a "how-to" guide. It was an architectural challenge to the status quo.

The Achievement: Beyond the 2.5K Mark

System Weakness is known for its rigorous editorial filter, often publishing only one or two deeply technical pieces a day. When my article was accepted and published, it felt like a validation of the "Clean Architecture" philosophy I had baked into the generator.

The numbers followed the quality:

• 2.5K+ Views on the technical analysis.

• 3.1K+ Clones of the repository on GitHub.

Seeing developers from across the globe clone the structure I had built in my local WSL 2 environment was the ultimate proof of concept.

The Lesson: "Good Wine Needs No Bush"

There is an old saying: Good wine needs no bush.

If you build a product that solves a real architectural pain point, and if you write about it with enough depth and technical honesty, the world will eventually pay attention. You don't need a massive marketing budget; you need Persistence and Technical Integrity.

What’s Next?

The journey doesn't end here. The next milestone for nodejs-quickstart-structure is the implementation of a robust OAuth2 flow, further standardizing how we handle identity in modern applications.

If you believe that security and architecture shouldn't be afterthoughts, I’d love for you to join the movement. Check out the project, break it, and help us build a better "Day 0" for Node.js.

Explore the project on GitHub: paudang/nodejs-quickstart-structure

Pau Dang is the creator of Node.js Quickstart Structure and is on a mission to bring Enterprise-grade architecture to every developer's terminal.

After hitting 4,000+ NPM downloads in 30 days, the community feedback was clear: the tool was powerful, but the "Question-Answer" CLI experience had limits.

For v2.0.0, I decided to build a Visual Web UI Configurator. But it wasn't just about making it pretty; it was a technical challenge of simulation parity.

🛠️ The Challenge: 1,680+ Possible Combinations

Our generator isn't a simple "Hello World" boilerplate. It supports:

• Architectures: MVC vs. Clean Architecture.

• Languages: JavaScript vs. TypeScript (ESM).

• Communication: REST, GraphQL (Apollo), Kafka.

• Databases: MySQL, PostgreSQL, MongoDB.

Mathematically, this results in over 1,680+ project permutations. The real challenge for v2.0.0 was: How do I show the user exactly what they are getting in a browser sidebar before they even run a command?

🧠 Synchronizing Logic: app-setup.js vs. SimulationTree.vue

To solve this, I had to ensure that the frontend simulation logic exactly matched the backend scaffolding logic.

Every folder in the UI is reactive. When a user toggles from "MVC" to "Clean Architecture," the entire hierarchy shifts. For instance, in our Clean Architecture scaffold, the webserver folder is exclusively for JavaScript, while TypeScript configurations are relocated to src/config.

Technical Glimpse: Tree Logic

Using Vue 3's reactive props, I built the SimulationTree component to handle conditional rendering based on the selected tech stack:

// A conceptual look at the Reactive Simulation Logic
const folders = computed(() => {
  return [
    {
      name: 'src',
      children: [
        { name: 'application', visible: props.architecture === 'Clean Architecture' },
        { name: 'infrastructure', visible: props.architecture === 'Clean Architecture' },
        { name: 'webserver', visible: props.architecture === 'Clean Architecture' && props.language === 'JavaScript' },
        // ... and 1,680+ more condition checks
      ]
    }
  ];
});

This parity ensures that there are zero "surprises" when the user finally clones the repository.

🏛️ Architecture: Empowering Choice

Standardization shouldn't mean restriction. v2.0.0 empowers engineers to choose:

• MVC: For velocity and rapid prototyping.

• Clean Architecture: For enterprise isolation and long-term maintainability.

By automating the "boring stuff" like flyway migrations, multi-stage Dockerfiles, and Snyk security hardening, I allow developers to focus on the Business Domain from the first minute.

🦾 AI-Native Experience: The .cursorrules Factor

As someone who uses Cursor and other AI coding assistants daily, I realized that modern structure isn't just for humans—it's for LLMs.

Every project scaffolded by v2.0.0 includes a production-ready .cursorrules file. This acts as a "DNA Map" for AI agents, telling them exactly where business logic (domain) ends and delivery layers (interfaces) begin. This eliminates the "hallucination phase" where AI tries to guess your project's architecture.

🗺️ What’s Next for the Movement?

Reaching 4,000 developers was a signal that Node.js was missing a "Community Standard." with v2.0.0, we are one step closer to that.

👉 Experience the Simulation: Nodejs Quickstart Generator

⭐ Explore the Source Code: GitHub Repository

In this article, I’ll show you how to build an Automated Armor for your Node.js microservices using SCA and SAST, and how you can setup a zero-vulnerability baseline in under 5 minutes using the Node.js Quickstart Structure.

🛑 The "Manual Review" Trap

Many developers think code reviews are enough. But can your team manually audit 1,000+ nested node_modules every day? Probably not.

This is where automated tools like Snyk and SonarQube step in.

🛡️ Snyk: Protecting your "Front Door" (SCA)

Snyk scans your dependencies for known vulnerabilities. If a library you use (like express or mongoose) has a security flaw, Snyk detects it and even suggests the exact version to upgrade to.

🔍 SonarQube/SonarCloud: The "Quality Gate" (SAST)

While Snyk looks at external libraries, SonarQube looks at your code. It finds "Code Smells," bugs, and security hotspots (like SQL Injection patterns or hardcoded secrets) before they reach production.

🚀 Step-by-Step Security Setup

Setting up these tools is often the hardest part, but I’ve built a generator that does 90% of the work for you. Here is how to get your environment ready:

🛡️ 1. Snyk Integration (The Token)

1. Create an Account: Sign up for free at Snyk.io.

2. Get your Auth Token:

   • Click your profile icon (bottom left) -> Account Settings.

   • Find Auth Token and click "Click to show".

3. GitHub Secret: Add this as SNYK_TOKEN in your GitHub Repository Settings -> Secrets.

🔍 2. SonarCloud Integration (Organization & Host)

SonarCloud is the SaaS version of SonarQube. It's free for public projects!

1. Login: Use your GitHub account at SonarCloud.io.

2. Import Project: Click the "+" icon (top right) -> Analyze new project. Import your repository.

3. Disable Automatic Analysis: Go to Administration -> Analysis Method and turn OFF Automatic Analysis. Select GitHub Actions instead.

4. Get your Details:

   • Project Key: Usually your-org_your-repo. Find it on the project dashboard.

   • Organization Key: Your username or organization name.

   • SONAR_HOST_URL: For the cloud version, this is always https://sonarcloud.io.

5. Token: Go to My Account -> Security -> Generate Token. Add it as SONAR_TOKEN in GitHub Secrets.

🏗️ Demo: Zero-Vulnerability Projects

If you want a project that comes with these tools pre-configured, you can use the nodejs-quickstart-structure:

npx nodejs-quickstart-structure@latest init

When prompted for Enterprise Security Hardening, select "Yes".

It will automatically generate:

• 🐳 Hardened Dockerfile: Using node:22.22.2-trixie-slim (The gold standard for security).

• 🔄 CI/CD Pipelines: Pre-built workflows for GitHub Actions, GitLab, and Jenkins.

• 🐕 Husky Hooks: Automated linting and formatting before every commit.

💡 The Takeaway: Security is a Feature, Not a Chore

Automating security audits isn't just about finding bugs; it's about Engineering Excellence. By shifting security "Left" into your dev environment, you catch issues early, save thousands in technical debt, and deploy with the confidence of an elite engineer.

Ready to upgrade your workflow?

1. Try the Generator: nodejs-quickstart-structure

2. Read the Full Guide: Enterprise Security Setup

3. Star the project on GitHub if this helps your team! ⭐️

Have you encountered a major security flaw in your dependencies recently? Let's discuss in the comments below!

As a backend engineer, I got tired of manually configuring docker-compose.yml, fighting with Jest timeouts, and debugging Kafka network issues. That’s why I decided to build-in-public and open-source my own ultimate generator: nodejs-quickstart-structure.

In this article, I want to take you behind the scenes of how I engineered the CLI to automatically generate 100% Deterministic E2E Testing Infrastructures out of the box.

1. The Goal: A "Zero-Config" Production Setup

My vision for the CLI was simple: When a developer runs npx nodejs-quickstart init and selects TypeScript, PostgreSQL, Kafka, and Redis, the generated repository shouldn't just contain empty controller files. It must include a fully automated testing pipeline that actually tests the integration of these services.

To achieve this, the CLI needed to solve three major challenges:

1. Isolating Unit Tests from E2E Tests.

2. Automating the Docker lifecycle during testing.

3. Solving the dreaded "Kafka Host vs Container" networking issue.

2. Challenge #1: Isolating the Test Environments

Most generic templates dump everything into one jest.config.js. This leads to the infamous "flaky tests" where developers accidentally use their local development database state for E2E tests, or where heavy integration tests slow down local unit test execution.

How the CLI solves this: During the scaffolding process, the CLI uses EJS templates to physically separate configurations. It generates two distinct files:

• jest.config.js: Strictly for Unit tests (milliseconds execution, everything mocked).

• jest.e2e.config.js: Designed for heavy lifting. It safely ignores node_modules, specifically targets the tests/e2e directory, and extends the testTimeout to 30,000ms to allow Docker dependencies to boot.

// Automatically generated jest.e2e.config.js
module.exports = {
  ...require('./jest.config'),
  testMatch: ['<rootDir>/tests/e2e/**/*.test.ts', '<rootDir>/tests/e2e/**/*.test.js'],
  testTimeout: 30000,
  clearMocks: true
};

3. Challenge #2: The Automated Docker Lifecycle

A true E2E test shouldn't require the developer to manually orchestrate infrastructure. I wanted the command npm run test:e2e to be a magic bullet.

To achieve this, the CLI injects a custom Node.js script (scripts/run-e2e.js) into the generated project. Here is the magic workflow it executes:

1. Assigns a Testing Port: It overrides process.env.PORT = '3001' so E2E tests never collide with the developer's running dev server on 3000.

2. Boots Infrastructure: Executes docker-compose up -d db redis kafka.

3. Health Checking: It uses the wait-on library to constantly poll http-get://127.0.0.1:3001/health until the Node.js application confirms all database migrations and Kafka broker connections are successful.

4. Executes Jest: Runs the rigorous E2E assertions.

5. Graceful Teardown: Executes docker-compose down to sweep away the testing infrastructure, leaving the developer's machine spotless.

4. Challenge #3: The Kafka Networking Nightmare

If you’ve ever tried to run a Node.js test runner on your local host while Kafka sits inside a Docker bridged network, you've likely seen this error: getaddrinfo ENOTFOUND kafka

This happens because the kafkajs client connects to the Docker mapped port, asks for the cluster metadata, and Kafka responds: "Hi, I am the leader, my address is kafka:9092!". The host machine has no idea what kafka is, so it crashes.

How the CLI fixes this for you: The CLI expertly scaffolds the docker-compose.yml to utilize KRAFT mode and explicitly maps a secondary PLAINTEXT_HOST listener strictly for your host tests.

# Generated by nodejs-quickstart
kafka:
  image: bitnamilegacy/kafka
  ports:
    - "9093:9093" # Exposed safely for Host testing
  environment:
    - KAFKA_CFG_ADVERTISED_LISTENERS=PLAINTEXT://kafka:9092,PLAINTEXT_HOST://localhost:9093
    - KAFKA_CFG_LISTENERS=PLAINTEXT://:9092,PLAINTEXT_HOST://:9093,CONTROLLER://:9094

It then automatically points your .env.test Kafka Broker string to localhost:9093. The result? Seamless local testing with zero networking headaches.

5. Try it out!

Building tools for other developers is arguably one of the most rewarding challenges in software engineering. By standardizing these elite testing configurations, we can eliminate flaky tests across hundreds of new projects.

If you are starting a new Node.js microservice, don't waste 3 days configuring Jest, Docker, and Kafka manually. Give the CLI a spin:

npx nodejs-quickstart-structure init

Check out the full open-source repository here:
👉 GitHub - nodejs-quickstart-structure

Have you ever struggled with Dockerizing your E2E tests? Let me know your biggest pain points in the comments! 👇

Why Caching?

When scaling applications, the database often becomes the bottleneck. Caching strategically places frequently accessed data in memory (like Redis) to bypass slow disk I/O. But not all caching is equal. To understand the nuances, I built a showcase service from scratch.

To skip the boilerplate and focus on the patterns, I used nodejs-quickstart-structure, a CLI tool designed for AI-ready, structured development.

5 Caching Patterns You Must Know

Here is a breakdown of the 5 patterns implemented in this demo:

1. Cache-Aside (Lazy Loading)

• Purpose: The application manages the cache. Data is only loaded into the cache when specifically requested.

• When to use: Best for systems with Read >> Write ratios (e.g., User Profiles).

• Pros: Memory efficiency; cache only contains data that is actually needed.

2. Read-Through

• Purpose: Offloads data-fetching logic to the Cache Provider. The app simply calls "Get" from the cache.

• When to use: To keep the business logic (Use Case) clean and decouple from the database.

• Pros: Extremely clean business code.

3. Write-Through

• Purpose: Data is written to both the Cache and the Database simultaneously.

• When to use: When Strong Consistency is required.

• Pros: Minimal data inconsistency risk.

4. Write-Around

• Purpose: Data is written directly to the DB, and the corresponding cache entry is invalidated (deleted).

• When to use: When the written data might not be read again immediately.

• Pros: Prevents "polluting" the cache with data that won't be reused soon.

5. Write-Back (Write-Behind)

• Purpose: Data is written to the Cache first; the DB update happens asynchronously in the background.

• When to use: For exceptionally high write performance (e.g., Logging, Real-time Metrics).

• Pros: Near-instant write response.

Technical Implementation (Step-by-Step)

Follow this roadmap to see how I build a production-ready demo using Clean Architecture:

1. Project Initialization

Bootstrap the project using the AI-Native CLI:

npx nodejs-quickstart-structure@latest init

Selection Guide:

• Project name: nodejs-service-caching-pattern

• Architecture: Clean Architecture

• Database: MySQL

• Caching: Redis

• Communication: REST APIs

2. Defining Domain Interfaces

Abstract the caching and repository logic to ensure true decoupling.

• ICacheService.ts

export interface ICacheService {
  get<T>(key: string): Promise<T | null>;
  set(key: string, value: unknown, ttl?: number): Promise<void>;
  del(key: string): Promise<void>;
  getOrSet<T>(key: string, fetcher: () => Promise<T>, ttl?: number): Promise<T>;
}

• IUserRepository.ts

3. Infrastructure Layer

Implementation for Redis and Sequelize (MySQL).

• redisClient.ts

• UserRepository.ts

4. Database Seeding: Generate 1,000 dummy users for demo purposes.

• V20260319__seed_1000_users.sql

5. Implementing the Use Cases

This is where the pattern logic lives.

• Read-Through Example: getUserInfoReadThrough.ts

// The cache provider handles DB fetching upon miss
return await this.cacheService.getOrSet<User | null>(cacheKey, async () => {
    return await this.userRepository.findById(id);
}, 3600);

• Write-Back Example: updateUserWriteBack.ts

// Update cache immediately, DB updates in background
await this.cacheService.set(cacheKey, updatedUser, 3600);
this.asyncDatabaseUpdate(updatedUser); 

You can check sample code at here:

• createUserWriteThrough.ts

• createUserWriteAround.ts

• updateUserWriteBack.ts

6. API & Documentation

• cacheDemoController.ts

• swagger.yml

How to Test & Verify

Once deployed, you can trigger these endpoints to verify the internal logic:

1. Test Cache-Aside / Read-Through (Read Path)

• First Call (Cold Cache): curl -X GET http://localhost:3000/api/demo/cache-aside/1

  • Internal: App checks Redis (Miss) -> Queries MySQL -> Updates Redis -> Returns.

• Subsequent Call (Warm Cache): Repeat the command.

  • Internal: App checks Redis (Hit) -> Returns immediately with zero DB overhead.

2. Test Write-Through (Sync Write)

• Trigger: curl -X POST http://localhost:3000/api/demo/write-through -H "Content-Type: application/json" -d '{"name": "Performance", "email": "perf@test.com"}'

  • Internal: Service writes to MySQL AND Redis simultaneously.

3. Test Write-Around (Clean Write)

• Trigger: curl -X POST http://localhost:3000/api/demo/write-around -H "Content-Type: application/json" -d '{"name": "Guest", "email": "guest@test.com"}'

  • Internal: Writes to MySQL, then calls DEL to invalidate the Redis key. The next read will be a Miss to load the fresh data.

4. Test Write-Back (Async Write)

• Trigger: curl -X PUT http://localhost:3000/api/demo/write-back/1 -H "Content-Type: application/json" -d '{"name": "Fast Update"}'

  • Internal: Updates Redis immediately (super fast response). The DB update happens after a short delay asynchronously.

Final Thoughts on AI-Native Tooling

What makes nodejs-quickstart-structure special is not just the speed of initialization, but its AI-Native nature. With .cursorrules and pre-built prompts, it ensures that your project maintains Clean Architecture and consistent coding standards automatically from development to production.

Full Source Code: GitHub Repository

I hope this guide helps you choose the right caching pattern for your next project

After years of building distributed systems, I decided to automate the "boring stuff." The result is nodejs-quickstart-structure, a CLI tool designed to take you from zero to a production-ready scaffold in under 60 seconds.

Why another boilerplate?

Most starters in the Node.js ecosystem fall into two categories:

1. The "Hello World" starters: Too simple. Great for learning, useless for production.

2. The "Everything-in-the-Box" monoliths: Too bloated. You spend more time deleting features you don't need than actually coding.

I wanted something different: A Clean Architecture scaffold that is modular, testable, and comes with a "Production-Grade" infrastructure out of the box.

The Technical Deep Dive

1. Clean Architecture: Separating Concerns

We don't just throw everything into a src folder. The CLI generates a structure based on Uncle Bob's principles:

• Domain Layer: Your business entities and logic (Zero dependencies).

• Use Cases: Orchestrating the flow of data.

• Infrastructure Layer: Where the "heavy lifting" happens (Sequelize, Kafka, Express).

This separation means you can swap your database or web framework without ever touching your core business rules.

2. Event-Driven by Default (Kafka Integration)

In a modern microservice world, services need to talk. We’ve built-in a robust Kafka integration.

• Pre-configured Producers/Consumers: No more struggling with kafkajs boilerplate.

• Reliability: It’s designed to handle connection retries and heartbeats properly.

3. Solving the "It Works on My Machine" Syndrome

One of the most annoying bugs I encountered was the Case-Sensitive naming mismatch between Windows (Case-Insensitive) and Linux (Case-Sensitive).

In nodejs-quickstart-structure, I’ve integrated:

• Strict ESLint Import Rules: Catches naming mismatches in your IDE.

• Full Docker Stack: A docker-compose.yml that stands up your App, MySQL, Kafka, and Redis in a unified Linux environment. If it runs on your local Docker, it will run on your Production Kubernetes.

The Power of One Command

You don't need to clone a repo. You don't need to manually edit config files. Just run:

npx nodejs-quickstart-structure init

What you get instantly:

✅ Clean Architecture folder structure.

✅ Sequelize ORM with MySQL & Flyway migrations.

✅ Redis integration for high-performance caching.

✅ Kafka setup for asynchronous event-driven messaging.

✅ Unit Testing environment with Jest.

✅ CI/CD workflows for GitHub Actions.

Final Thoughts & Open Source Building this CLI was about more than just automation—it was about creating a standard. Whether you are a solo developer or part of a large team, having a consistent scaffold means anyone can jump into the codebase and understand it immediately.

I’m looking for feedback! Try it out, break it, and let me know how we can make it even better.

👉 GitHub: [https://github.com/paudang/nodejs-quickstart-structure]

👉 NPM: [https://www.npmjs.com/package/nodejs-quickstart-structure\]

We’ve all been there. You prompt Cursor or Claude to "Set up a Node.js Clean Architecture," and it does a decent job—at first. But as soon as you need to integrate Redis for caching, Kafka for event-driven messaging, and Docker for deployment, the "AI-generated" structure starts to crumble. It lacks cohesion, ignores edge cases, and isn't "Production-Ready."

The Solution: A Framework-Agnostic "Golden Standard"

I spent hundreds of hours refining the nodejs-quickstart-structure. My goal wasn't just to create another boilerplate, but to build a Professional Toolkit—the kind of structure a Tech Lead takes from company to company to skip two weeks of setup and get straight to business logic.

Today, it has reached nearly 3,000 downloads and holds the #1 spot on NPM search for Node.js quickstart structures.

What’s Inside the "Growth" Phase?

The tool currently supports:

• Clean Architecture: Strict separation of concerns.

• Hybrid Communication: Support for REST and GraphQL.

• Performance: Built-in Redis caching logic.

• DevX: Optimized .cursorrules so your AI assistant actually understands your code patterns.

Sneak Peek: The v1.16.0 Kafka Update (Coming Next Week)

I’m currently finalizing a major update focused on Event-Driven Architecture:

• BaseConsumer Abstraction: Automated JSON parsing, schema validation (Zod), and robust error handling.

• The "Golden Flow" Demo: A real-world integration showing API Request -> DB Save -> Cache Invalidation -> Kafka Event.

• AI-Native Kafka: Updated AI rules to help you generate new consumers/producers that follow the established architectural pattern.

Join the Journey If you’re tired of "re-inventing the wheel" for every new microservice, give this structure a try.

👉 NPM: nodejs-quickstart-structure

👉 GitHub: paudang/nodejs-quickstart-structure: A CLI to scaffold Node.js microservices with MVC or Clean Architecture

I’m on a mission to hit 10k downloads by the end of the year. If this tool saves you even an hour of work, I’d be honored to have your 🌟 on GitHub!

As Node.js developers, we've all been there. You have a great idea for a new project, but before you can write a single line of business logic, you have to spend hours setting up the foundation.

You know the drill:

1. Copy-paste a folder structure from an old project.

2. Configure ESLint, Prettier, and TypeScript.

3. Set up Docker and docker-compose.

4. Wire up the database connection.

5. Build the base Controller/Service layers.

It’s not hard, but it’s tedious. It’s called "Boilerplate Fatigue," and it kills your momentum. What if there was a way to just skip straight to the fun part of coding?

To solve this, I built an interactive CLI tool called nodejs-quickstart-structure.

The goal is simple: Run one command, and get a professional, industry-standard Node.js project ready for production code. Best of all? You are in full control of the architecture you want.

Before we dive into the tool, let's talk about the biggest decision you have to make when structuring your new Node.js app: MVC vs Clean Architecture.

🏛️ The Great Debate: MVC vs Clean Architecture

Choosing the right folder structure is critical for your application's success.

📌 What is MVC? (Model–View–Controller)

MVC is the classic software architecture pattern that divides an application into three interconnected parts:

• Model: Manages data, database connections, and core business logic.

• View: Handles the user interface and presentation.

• Controller: Acts as the middleman, processing incoming requests, fetching data from the model, and pushing it to the view.

👉 Best For: MVC is simple, fast to implement, and intuitively organized. It's ideal for small to medium projects, quick prototypes, and REST APIs where getting to market quickly is the priority.

📌 What is Clean Architecture?

Clean Architecture (popularized by Robert C. Martin - Uncle Bob) emphasizes separating the business rules from the infrastructure. It is often represented as concentric circles with strict dependency rules pointing inward:

• Entities: Core business objects and properties.

• Use Cases: Application-specific business rules.

• Interface Adapters: Bridges between use cases and external systems (Controllers, Presenters).

• Frameworks & Drivers: Databases, Web Frameworks, UI, and external tools.

👉 Best For: Clean Architecture is designed for maximum scalability, high testability, and long-term maintainability. It’s perfect for large enterprise projects, microservices, or complex systems expected to evolve heavily over time.

🚀 Introducing nodejs-quickstart-structure

There are plenty of generators out there, but they are either too simple (just a basic Express app.js) or too opinionated (forcing a specific framework you don't like).

nodejs-quickstart-structure is designed to balance speed with professional standards, letting you pick exactly how you want your app scaffolded.

✨ Key Features:

• Architecture Agnostic: Choose between MVC for speed or Clean Architecture for strict separation of concerns.

• Language Support: First-class support for both JavaScript and TypeScript.

• Database Ready: Auto-configured connections for MongoDB, MySQL, or PostgreSQL using Mongoose/Sequelize.

• Microservices & Event-Driven: Optional Kafka integration for robust message brokering.

• Performance Caching: Built-in Redis or Memory cache support.

• DevOps Friendly:

  • Generates a complete docker-compose.yml instantly wiring up your DB, Redis, Kafka, and Zookeeper.

  • Optimized Multi-Stage Dockerfile for small, secure production images.

  • CI/CD templates automatically included for GitHub Actions, Jenkins, or GitLab.

• Code Quality: Pre-configured with ESLint (Flat config), Prettier, Husky, and Lint-staged.

• Logging: Professional Winston + Morgan setup out of the box.

• Deployment: Ship confidently with an integrated PM2 Ecosystem Configuration for zero-downtime reloads and robust process management.

💻 Installation & Usage

It's published on npm. Start by installing the CLI globally:

npm install -g nodejs-quickstart-structure

Let's Scaffold a Project!

Navigate to your empty workspace and simply run:

nodejs-quickstart init

Quick Start (Recommended)

You can run the generator directly without installing it globally:

npx nodejs-quickstart-structure init

The CLI will fire up and ask you a few interactive questions:

1. Project Name: my-awesome-app

2. Language: TypeScript / JavaScript

3. Architecture: Clean Architecture / MVC

4. Database: PostgreSQL / MySQL / MongoDB

5. Caching: Redis / Memory cache

6. Communication: REST APIs / Kafka

7. CI/CD: GitHub Actions / Jenkins / GitLab

And... BOOM! 💥

Within seconds, you have a fully scaffolded, Dockerized project structure ready to run:

my-awesome-app/
├── src/
│   ├── config/           # Environment variables, db config, swagger
│   ├── controllers/      # (MVC) or interfaces/controllers (Clean Arch)
│   ├── routes/           # (MVC) or interfaces/routes (Clean Arch)
│   ├── usecases/         # (Clean Arch) Application Business Rules
│   ├── domain/           # (Clean Arch) Enterprise Business Rules
│   ├── infrastructure/   # (Clean Arch) Database repositories, external services
│   └── index.ts          # Express Entry point
├── docker-compose.yml    # Fully configured services matrix
├── Dockerfile            # Multi-stage production image
├── .eslintrc.mjs         # Flat config
├── package.json
└── ...

🛠️ Massive Customizability

The tool supports over 160 different core configuration combinations, rigorously tested on Windows and Linux via automated E2E pipelines.

If you choose TypeScript + Clean Architecture + PostgreSQL + Kafka + Redis, the tool will:

1. Generate the standard inward-facing Clean Architecture folder structure.

2. Install the pg and sequelize drivers, creating dynamic DB configurations.

3. Set up the kafkajs client and broker configs.

4. Auto-wire the ioredis cache client.

5. Create fully dockerized containers for Postgres, Redis, Kafka, and Zookeeper so everything boots with docker-compose up.

6. Generate beautiful Swagger (OpenAPI) docs.

You get to skip days of painful environment debugging and jump straight to writing the code that actually matters to your product.

🚀 Roadmap & Upcoming Features

We are constantly working to improve nodejs-quickstart-structure and make it the most robust boilerplate generator for Node.js.

👉Documents: [Nodejs Quickstart Structure]

You can track our current progress, see what features are being worked on, and vote for your favorites on our public Trello board:

👉 View our Public Roadmap on Trello

🤝 Open Source Contribution

This project is entirely Open Source (ISC License). I’d love for you to try it out, break it, report bugs, or even contribute new features!

• ⭐️ Star the GitHub Repo: https://github.com/paudang/nodejs-quickstart-structure

• 📦 Check it out on NPM: https://www.npmjs.com/package/nodejs-quickstart-structure

If you find this tool helpful in saving your precious boilerplate time, giving it a star on GitHub goes a long way in supporting its development. Let me know what you think in the comments below