Every week someone declares MERN dead. Meanwhile, I’m still shipping it at scale. 🚀 Clickbait loves to bury MongoDB and Express. But real engineers know: trends fade, fundamentals don't. Why MongoDB + Express remain relevant (and teach you a lot): - Schema flexibility – Forces you to think about data shape early. Great for learning how to refactor as requirements change. - Developer speed – One language (JavaScript/TypeScript) from database to UI. Fewer context switches when you're starting out or iterating fast. - Scaling lessons – Setting up sharding in MongoDB Atlas or clustering Express teaches you distributed systems thinking without needing a PhD. Where the learning curve gets steeper (and why that's good): I've also built with NestJS + PostgreSQL – stronger ACID transactions, stricter schemas, and a more opinionated architecture. That curve forced me to learn dependency injection, repositories, and migration workflows. Different tools teach different lessons. My take: stack matters less than your learning curve. A messy NestJS app is still messy. A clean Express API can be a joy to maintain. MERN isn't dying – it's just a starting point that leads you to deeper waters when you're ready. What stack are you enjoying most right now – and what did it teach you? Let's share learning curves below 👇 #MERNStack #WebDev #TechDebate

🚀 Built & Deployed a Full-Stack MERN Application Excited to share a project where I implemented a complete full-stack workflow — from backend APIs to database integration and live deployment. 🔗 Live Project: https://lnkd.in/gBUxUcma 💻 GitHub: https://lnkd.in/gwvkjTvM 💡 Project Overview: This is a full-stack application where I built a backend server, connected it with a MongoDB database, and deployed it to a live environment. ⚙️ Tech Stack: Node.js Express.js MongoDB (Database) Mongoose (ODM) REST APIs Render (Deployment) 🔥 Key Features: CRUD operations with MongoDB Structured API routes following REST principles Database schema design using Mongoose Full backend deployment on cloud Error handling and async operations 📚 What I Learned: How to connect and manage MongoDB in a real project Writing clean and scalable backend architecture Handling async operations and API responses Real-world deployment challenges (env variables, server configs, cold starts) ⚠️ Challenges Faced: Debugging deployment issues on Render Managing database connection in production Handling API errors properly 🎯 What’s Next: Add authentication (JWT) Build a proper frontend UI Convert this into a complete production-ready SaaS-style project This project helped me move from “just coding” → “building real-world deployable systems”. Thanks to Ankur Prajapati and Sheryians Coding School Would appreciate your feedback 🙌 #MERN #MongoDB #NodeJS #ExpressJS #FullStackDevelopment #WebDevelopment #LearningInPublic

🚀 Learning System Design by Building a URL Shortener Today I worked on building a full-stack URL Shortener to understand how real-world systems are designed and scaled. What the backend is doing: Accepts a long URL and generates a unique short code Stores the mapping in MongoDB Redirects users from short URL → original URL Tracks total clicks for each shortened link Exposes a simple analytics endpoint for URL stats Handles duplicate URLs and validates input properly Tech Stack: Frontend: Next.js, Tailwind CSS Backend: Node.js, Express.js Database: MongoDB Atlas Deployment: Vercel + Render This project helped me understand concepts like: API design Routing and controllers Database schema design URL mapping logic Analytics tracking Deployment and production debugging 🔗 Live Demo: https://lnkd.in/g_qd-WB7 💻 Source Code: https://lnkd.in/g7Kp865n Still learning and improving it step by step ⚡ Would love to hear what features you’d add next! #SystemDesign #FullStackDevelopment #WebDevelopment #Nodejs #Nextjs #MongoDB #SoftwareEngineer #BuildInPublic #BackendDevelopment #100DaysOfCode

Started this as a weekend thing. I wanted a rate limiter that actually fit how I build Node APIs: TypeScript, the frameworks I use day to day, and real stores once you're past localhost. Wasn't trying to publish anything. Just wanted to learn by building. What changed the shape of the project was how I used AI. Not as a code vending machine, but as someone to think out loud with. We'd sketch the API, I'd argue about edge cases, we'd rewrite the parts that felt off, add tests, kept going. The boring scaffolding got quick. The harder stuff got the attention it actually needed: distributed limits, what happens when Redis goes down, getting metrics out without baking in a specific vendor. That weekend thing is now ratelimit-flex. It plugs into Express, Fastify, NestJS, and Hono. Backed it with Redis, Postgres, Mongo, DynamoDB, or keep it in-memory for dev. Sliding window, token bucket, fixed window. Hooks for metrics and a few resilience patterns I kept reaching for at work. I don't think "AI wrote it" is the interesting part. The interesting part is that a clear idea, the patience to sit with the hard problems, and AI handling the grunt work can take a weekend curiosity and land it somewhere you'd actually trust next to production traffic. If you're writing APIs in TypeScript, I'd love eyes on it. And honestly, tell me what breaks: 🔗 https://lnkd.in/gFRjDUWq 🔗 https://lnkd.in/g4guDyEz #OpenSource #TypeScript #NodeJS #API #Ratelimiter

🚀 Full-Stack CRUD Application Built with MERN Fundamentals I recently built a complete CRUD (Create, Read, Update, Delete) application using Node.js, Express, and MongoDB Atlas — focusing on understanding real-world application flow rather than just writing code. 🔧 What I implemented: • RESTful API design (GET, POST, PUT, DELETE) • Backend with Express.js • Cloud database integration using MongoDB Atlas • Dynamic frontend using HTML, CSS, and JavaScript • End-to-end data flow from UI to database and back ⚙️ Key Features: • Create → Add new users via form • Read → Fetch and display users dynamically • Update → Edit user data with pre-filled forms • Delete → Remove users instantly from database 💡 What this project strengthened: • Clear understanding of client-server architecture • Working with APIs and asynchronous operations • Handling real debugging scenarios (routing, IDs, async issues) • Structuring scalable backend logic 🔁 Core Architecture: Frontend → API → Backend → Database → Response → UI This project helped me move beyond tutorials and actually understand how production-level applications function. 📌 Next Focus: GraphQL & WebSockets to explore real-time and flexible API systems. #FullStackDevelopment #MERN #NodeJS #MongoDB #ExpressJS #JavaScript #BackendDevelopment #WebDevelopment 

Hitesh Choudhary Just watched "Taking Backend to Next Level" by Hitesh Choudhary 🔥 This part of the Chai aur Code backend series is pure gold if you're serious about MongoDB + Mongoose. Key takeaways: • Moving from basic schemas to real-world data modelling • Understanding when to embed vs reference • Designing scalable and performant MongoDB schemas • Avoiding common mistakes that slow down your backend later If you're building full-stack apps (especially MERN), this video helps you think like a professional backend developer — not just someone who can do CRUD. Highly recommended for intermediate developers who want to level up their backend skills. Watch here: https://lnkd.in/ggBCgQ3s What’s one thing you changed in your data modelling after learning advanced Mongoose concepts? Share in comments 👇 #NodeJS #MongoDB #Mongoose #BackendDevelopment #MERN #FullStack #WebDevelopment

Tuesday Build Log: When “It Works” Isn’t the Same as “It’s Correct” Yesterday, I tried to share a huge milestone in my 20-week backend mastery journey, but the algorithm had other plans 😅. Let’s try this again! Over the weekend, I pushed my backend skills a bit further. I built a REST API that: → Takes a name input → Calls multiple external APIs (age, gender, nationality prediction) → Processes and classifies the data → Stores everything in PostgreSQL with proper structure → Exposes clean CRUD endpoints Stack: Node.js + TypeScript + Express + PostgreSQL It worked. I got the expected result. But the real story wasn’t the success, it was everything around it. Here’s what stood out: 🔹 Sometimes the bug isn’t your code I spent hours debugging what looked like a backend issue. Turns out it was just poor internet conditions slowing everything down. 🔹 “Fixing it” vs “Fixing it properly” I ran into database connection issues during deployment. I found a workaround that worked instantly… but I know it’s not the final solution. 🔹 Backend development is more than writing logic You’re dealing with infrastructure, environments, networking, and third-party systems all at once. And that’s where things get interesting. Right now, I’m learning that: → A working system doesn’t always mean a correct system → Debugging is as much about elimination as it is about knowledge → Real growth happens when things don’t behave the way you expect Still early in the journey, but things are starting to connect. If you’ve worked with backend systems in production: What’s one issue that looked like a code bug… but wasn’t? #BackendDevelopment #NodeJS #PostgreSQL #BuildInPublic #DevJourney PS: I hope this doesn’t get shadowbanned or something 😅

🚀 Backend Learning Log #13 — vidTube Today, I worked on building the “Get All Videos” API for my vidTube backend. 🛠️ What I implemented: • Pagination (page & limit) for efficient data loading • Search functionality using regex (title & description) • Filtering videos by user (owner-based filtering) • Sorting (by createdAt with asc/desc control) • Calculated total videos count for better frontend handling Adding pagination, filtering, and search makes the API production-ready and frontend-friendly. 🔗 GitHub Repository: https://lnkd.in/g79x35ZC Tech stack: Node.js • Express.js • MongoDB • Mongoose #BackendDevelopment #NodeJS #ExpressJS #MongoDB #API #WebDevelopment #BuildInPublic

🚀 Backend Development Progress Update – This Week This week, I focused on strengthening my backend development fundamentals and understanding how servers and databases work together. 🔹 What I Learned: ✅ Setting up a basic backend server using Node.js and Express.js ✅ Understanding how "express.json()" works for handling JSON requests ✅ Learning proper backend project structure and folder organization ✅ Connecting MongoDB Atlas with the backend using Mongoose ✅ Understanding MongoDB connection strings and environment variables ✅ Learning why keeping database credentials secure is important ✅ Understanding how the backend communicates with the database 🔹 Challenges Faced: While connecting MongoDB Atlas, I faced issues with the connection URL and DNS errors. Debugging those problems helped me understand the setup process much better and improved my confidence in handling backend errors. 🔹 Key Learning: Backend development is not only about writing APIs—it starts with strong fundamentals like server setup, database connections, debugging issues, and writing clean project structure. Small problems often teach the biggest lessons. 🔹 Next Focus: ➡️ Creating routes and controllers ➡️ Building REST APIs ➡️ Learning authentication using JWT Step by step, getting better every week 💻 #BackendDevelopment #NodeJS #ExpressJS #MongoDB #MongoDBAtlas #Mongoose #WebDevelopment #FullStackDeveloper #LearningInPublic #100DaysOfCode #DeveloperJourney

🚀 I stopped using "LIKE" for search… and everything changed. For a long time, my search looked like this: 👉 "WHERE name LIKE '%doctor%'" It works in the beginning. But once data grows or users make typos… it starts falling apart. So I decided to build a real search system using PostgreSQL’s "tsvector". --- Here’s what I ended up doing 👇 🔹 Full-text search with "tsvector" 🔹 Auto-updating search column using database triggers 🔹 Weighted ranking (name > description) 🔹 GIN indexes for fast queries 🔹 Typo handling using "pg_trgm" --- Now it behaves like an actual product: ✔ “doctor” → finds relevant contacts ✔ “docter” (typo) → still works ✔ “english school” → best matches come first --- 💡 Biggest realization: I used to think databases are just for storing data. They’re not. If you use them properly, they can handle: 👉 search 👉 ranking 👉 performance without adding extra services. --- ⚙️ Stack I used: • Node.js • TypeScript • Prisma • PostgreSQL (tsvector + pg_trgm) --- Still improving this: ➡ better ranking signals ➡ pagination ➡ smarter query parsing --- If you’re still using "LIKE" for search… you’re leaving a lot of performance and capability on the table. Curious — how are you handling search in your apps? --- #PostgreSQL #BackendDevelopment #FullTextSearch #SoftwareEngineering #WebDevelopment #NodeJS #Prisma #DatabaseDesign #BuildInPublic #LearningInPublic #Developers #Tech