Muhammad Shuja Mustafa’s Post

Is your NestJS API slow under load? Here are the advanced optimizations most developers skip: 1- Caching with @nestjs/cache-manager Cache expensive DB queries or external API calls at the service level. Use Redis as the store for distributed. 2- Database Query Optimization Stop using .find() with no filters in production. Use query builders, select only needed fields, and always paginate with cursor-based pagination for large datasets. 3- Compression Middleware Enable gzip compression with the `compression` package. A 5-line change that can cut response sizes by 70%. 4- Request Validation at the Edge Use class-validator + class-transformer with global ValidationPipe. Reject bad requests before they ever hit your service layer. 5- Lazy-Loaded Modules Don't load everything at startup. Use lazy module loading for rarely-used features — critical for serverless NestJS deployments. 6- Async Everything Never block the event loop. Offload heavy tasks to Bull queues (@nestjs/bull) and process them in background workers. #NestJS #NodeJS #TypeScript #BackendDevelopment #WebPerformance #SoftwareEngineering #APIs

Recently, I’ve been focused on leveling up my full-stack development skills, and I’m excited to share my latest project: a high-performance URL shortener with built-in analytics! 🚀 I wanted to build something that was not only fast and robust but also incredibly easy to deploy. Here is a look under the hood: 🔹 Backend: Powered by PostgreSQL for persistent storage and Redis for lightning-fast caching. 🔹 Frontend: Built a dynamic UI using Framer Motion, complete with a custom 3D splash screen built in Three.js. 🔹 Infrastructure: Fully containerized with Docker for a seamless, one-click setup. 🔹 Testing: Implemented comprehensive unit tests to ensure both the frontend and backend remain highly available, alongside k6 load testing to guarantee stable performance under pressure. If you are interested in the architecture or want to deploy it yourself, all the setup details and code are available on my GitHub. 🔗 Check it out here: https://lnkd.in/dDpGiijc #FullStackDevelopment #WebDevelopment #PostgreSQL #Redis #Docker #ThreeJS #FramerMotion #TypeScript #SoftwareEngineering #TechPortfolio

Most Mongoose developers are wasting performance… without realizing it. If you're building APIs and NOT using .lean(), you're returning heavy Mongoose documents every time. 👉 But in 90% of GET APIs, you don’t need them. Here’s the fix: const users = await User.find().lean(); 💡 What changes? • No Mongoose overhead • Faster query response • Lower memory usage • Cleaner API output ⚠️ Important: Don’t use .lean() when you need document methods like .save() or .populate(). 🧠 Rule: Use .lean() for read operations, skip it for write/update logic. Small optimization. Huge impact. Are you using .lean() in your APIs? #NodeJS #MongoDB #Mongoose #BackendDevelopment #WebPerformance #JavaScript #APIDesign #100DaysOfCode

𝗧𝗮𝘀𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 𝗥𝗘𝗦𝗧 𝗔𝗣𝗜 Building real projects is how I learn — so I built one worth sharing. This is a fully functional Task Manager REST API deployed on Vercel, built from scratch using Node.js, Express.js, and MongoDB. No tutorials followed end-to-end. Just a problem, a blank file, and a goal to ship something clean. 🧩 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝘁 ▸ 𝗖𝗥𝗨𝗗 𝗔𝗣𝗜 𝗘𝗻𝗱𝗽𝗼𝗶𝗻𝘁𝘀 — Create, Read, Update, and Delete tasks with a clean RESTful interface ▸ 𝗠𝗼𝗻𝗴𝗼𝗼𝘀𝗲 𝗦𝗰𝗵𝗲𝗺𝗮 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 — Enforces data integrity at the model level before anything touches the database ▸ 𝗚𝗹𝗼𝗯𝗮𝗹 𝗘𝗿𝗿𝗼𝗿 𝗛𝗮𝗻𝗱𝗹𝗶𝗻𝗴 — Custom middleware catches errors app-wide for graceful, predictable responses ▸ 𝟰𝟬𝟰 𝗠𝗶𝗱𝗱𝗹𝗲𝘄𝗮𝗿𝗲 — Unknown routes return meaningful errors instead of silent failures ▸ 𝗘𝗦𝟲 𝗠𝗼𝗱𝘂𝗹𝗲𝘀 — Modern import/export syntax for a clean, maintainable codebase ▸ 𝗖𝗹𝗼𝘂𝗱 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 — Live on Vercel using Serverless Functions with MongoDB Atlas as the backend 🛠 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 ▸ Node.js & Express.js ▸ MongoDB & Mongoose ▸ Vercel (Serverless) ▸ Vanilla JS & CSS (Frontend) 🔗 Code: https://lnkd.in/dDR865aQ Live Project Link: https://lnkd.in/dJb5AUQ3 If you're learning backend development — build something, ship it, then talk about what you learned. That's the post people actually stop to read. #NodeJS #ExpressJS #MongoDB #BackendDevelopment #REST #WebDevelopment #MERNStack

Day 67 of my #100DaysOfCodechallenge Today I focused on improving my Node.js REST API by implementing sorting and field limiting using Mongoose. These features allow API users to control how data is returned from the database. Key things I learned: • How to sort results dynamically using query parameters Example: GET /api/v1/movies?sort=price • How to return only specific fields from the database to reduce payload size Example: GET /api/v1/movies?fields=name,price,ratings • Using JavaScript string manipulation to transform query parameters into MongoDB-compatible queries. This makes the API more flexible, efficient, and closer to production-level design. Next, I plan to implement pagination so users can control how many results are returned per request. #100DaysOfCode #NodeJS #MongoDB #BackendDevelopment #WebDevelopment #LearningInPublic

Throughout my experience engineering backend systems, I’ve found that managing database latency is often the silent bottleneck that makes or breaks a real-time application. We often default to heavy ORMs like TypeORM or Prisma. But as applications scale, the serialization overhead and complex query chaining can introduce severe friction. Furthermore, setting up Change Data Capture (CDC) for real-time applications usually requires deploying Redis and writing a mountain of boilerplate. I wanted a leaner, faster alternative. So, I built one. Today, I'm open-sourcing Kinetic SQL - a lightweight, universal SQL engine for Node.js (supporting Postgres, MySQL, and SQLite). The Architectural Highlights: 🚀 Native Real-Time Subscriptions: Subscribe to database changes directly in your Node backend without WebSockets or Redis. 🤖 Automatic Type Generation: It reads your schema and auto-generates type safety. You never have to manually write a TypeScript interface again. 🛠️ Native RPC Wrapper: Call your stored procedures and database functions just like native JavaScript methods. 🔌Middleware API (Zero-Overhead): Easily build plugins (like custom loggers, APM tracers, or data maskers) that intercept queries without adding latency or bloating the core engine. 🤝 Query Builder Friendly: It includes a .native escape hatch, so you can easily pass the highly optimized connection pool directly into Drizzle ORM. 🌍 Universal Fit: Drops instantly into Express, Fastify, Vanilla JS or NestJS (via a dedicated DI module). 🚀 NestJS Native: Drop-in "KineticModule" for zero-config integration with NestJS Framework. The Stress Test: To prove the engine can handle high-frequency concurrent reads/writes without choking the Node event loop, I built a Live Stock Market Simulator. It consistently achieves <4ms query latency. I would really appreciate architectural feedback from the community. If you're dealing with ORM bloat, I'd love for you to test it out. Links to the NPM Package, GitHub repo and Live Demo are in the comments below 👇 #SoftwareEngineering #NodeJS #OpenSource #TypeScript #JavaScript #SystemArchitecture #NestJS #ORM #SQL

Are you frustrated to create same CRUD multiple times? Here is the solution - 🚀 NextMin 2.0: The New Architecture is Live! We've just pushed a massive update to NextMin, transforming it into a high-performance, event-driven powerhouse for your Node.js & React applications. 🛠️✨ Building admin panels and internal tools just became significantly faster and more flexible. Here’s what’s new: 🔥 Native Realtime Support: Say goodbye to manual WebSocket boilerplate. Realtime synchronization is now baked directly into the core router. ⚓ Event-Driven Lifecycle: Hook into every action with our new events system. Run custom logic before or after any CRUD operation seamlessly. ⚡ Performance 2.0: We've introduced an intelligent caching layer using keyv (Redis/In-memory) to drastically reduce database latency. ✍️ Rich Text with Tiptap: Complex content editing is now native. Just add "rich": true to your schema and enjoy a premium editor experience. 🧩 The Unified NMAdapter: One adapter to rule them all. Whether you’re on SQL or MongoDB, the experience is now consistent and more robust. We’ve also refreshed our docs with a full Migration Guide and a sleek new Give it a shot: 👉 https://lnkd.in/g5Dn_S7C #NextMin #NextJS #NodeJS #ReactJS #OpenSource #WebDev #Realtime #DeveloperExperience #AdminPanel #EventDriven #EasyNodeJS

Your Django monolith can scale to millions of users. You're just doing it wrong. The rush to microservices often happens because the core monolith isn't properly architected for scale. Before you break everything apart, check if you've exhausted the capabilities of a well-designed monolithic deployment. A production-ready Django setup doesn't just run on a single server. It offloads work aggressively. User requests hit a load balancer, then Nginx, which serves static files directly and reverse-proxies dynamic requests to Gunicorn workers. The application layer itself must be stateless. This means user uploads go to S3 or a similar object store, not the local filesystem. Sessions and expensive query results live in a dedicated Redis or Memcached layer, protecting the database. Speaking of the database, you need to separate concerns. Use PostgreSQL with a primary for writes and multiple read replicas for reads. Most web traffic is read-heavy, making this a huge performance win. Finally, any task that takes more than a few hundred milliseconds—sending emails, generating reports, processing images—should be pushed to a Celery queue backed by RabbitMQ or Redis. This keeps your web workers free to handle incoming requests. Only after these components are in place and becoming bottlenecks should you consider a service-oriented architecture. Often, this setup is more than enough. #Django #SystemDesign #Python #Scalability

If you want to improve your Node.js application, here are some things you can focus on:   Performance Optimization: Use clustering, worker threads, caching (Redis), and avoid blocking the event loop. Database Optimization: Add proper indexing, optimize queries, use connection pooling, and join query Security Enhancement: Implement authentication (JWT/OAuth), rate limiting, input validation, helmet, and proper error handling. Code Refactoring: Follow clean architecture, modular structure, SOLID principles, and remove technical debt regularly. Scalability: Use load balancing, horizontal scaling, microservices if necessary, and Docker container. Use Modern Technologies: Adopt TypeScript, Prisma/Sequelize, proper logging (Winston), monitoring, and CI/CD pipelines. #NodeJS #NodeJSApplication #ExpressJS #NodeJSDeveloper #NodeJSWebsite #NodeJSPerformanceOptimization #BackendDevelopment #FullStackDeveloper #JavaScript #WebDevelopment #SoftwareArchitecture #PerformanceOptimization