Common API Design Mistakes to Avoid

🚀 Backend Learning | How I Design APIs in Real Projects After working on multiple backend systems, I realized that good API design is not just about endpoints — it’s about clarity, scalability, and usability. Here’s the approach I follow: 🔹 1. Understand the Business Requirement → What problem are we solving? 🔹 2. Define Clear Endpoints → Keep naming RESTful and meaningful 🔹 3. Design Request & Response Structure → Consistent format (status, message, data) 🔹 4. Handle Edge Cases & Errors → Proper status codes & error messages 🔹 5. Think About Scalability → Pagination, filtering, versioning 🔹 6. Add Logging & Monitoring → For debugging and production insights 🔹 7. Keep It Simple → Avoid over-engineering 🔹 Outcome: • Clean and maintainable APIs • Better frontend-backend communication • Easier debugging and scaling Good APIs are not just built — they are carefully designed. 🚀 #Java #SpringBoot #BackendDevelopment #APIDesign #SystemDesign #LearningInPublic

🔁 Revisiting Backend Fundamentals (Node.js) After ~2.5 years of working with backend systems, I revisited core Node.js concepts—and the perspective is completely different now. What once felt "basic" now directly impacts real-world system design. Here’s what I focused on: • Module system & code structuring   • Dependency management (NPM)   • Core modules (fs, path, http)   • Async patterns & event-driven architecture  One key realization: 👉 Writing async code is easy.   👉 Writing predictable, debuggable async code is the real skill. I’ve shared detailed insights and practical takeaways here:   🔗 https://lnkd.in/ggNQm7-7 Curious—how do you revisit fundamentals after gaining experience? #NodeJS #BackendEngineering #SoftwareDevelopment #CleanCode

3 years ago, I wrote my first API. It worked. Barely. No error handling. No input validation. Hardcoded values everywhere. I was just happy it returned a 200. Fast forward to today - I've shipped APIs in production that handled real client data, prevented revenue losses, and a API that directly convinced a client to onboard. Here's what I wish someone had told me at the start: 1. "It works on my machine" is not done. Done means it works under load, with bad inputs, with network failures, with edge cases you didn't think of. I learned this the hard way. 2. Naming things well is a superpower. The biggest time sink in early code isn't logic - it's trying to understand what past-you was thinking. Write for the next developer, not the compiler. 3. You will touch the database in production. And it will be terrifying the first time. Learn SQL properly. Understand indexes. Respect transactions. I've fixed bugs at the DB level that would have taken down a live client system. 4. Pick boring technology first. I chased new tools early. Then I spent a week building a document processing POC under a tight deadline - and the tools that saved me were the ones I already knew deeply: NestJS and solid API design. Familiarity under pressure is an unfair advantage. 5. Ship something real as fast as you can. Side projects are great. But nothing teaches you faster than code that actual users depend on. The feedback loop is brutal and honest. The gap between "it works" and "it's production-ready" is where most of the real learning happens. Still learning. Always will be. What's one thing you wish you knew when you wrote your first API? Drop it below 👇 #softwaredevelopment #webdevelopment #reactjs #nodejs #apidesign #fullstackdeveloper #devjourney #programming

🚀 Day 6/45 – Backend Engineering (REST API Design) Today I focused on common mistakes developers make while building APIs. 💡 What I learned: 🔹 Mistake 1: Using wrong HTTP methods GET for updates ❌ POST for everything ❌ 👉 Use proper semantics (GET, POST, PUT, DELETE) 🔹 Mistake 2: Poor endpoint design /getAllUsers ❌ /createUser ❌ 👉 Use clean, resource-based endpoints: /users /users/{id} 🔹 Mistake 3: Ignoring status codes Always returning 200 ❌ 👉 Use: 201 → created 400 → bad request 404 → not found 🔹 Mistake 4: No pagination 👉 Leads to performance issues with large data 🛠 Practical: Refactored APIs in my project to follow REST standards with proper endpoints, status codes, and pagination. 📌 Real-world impact: Well-designed APIs: Improve frontend integration Reduce bugs Scale better in production 🔥 Takeaway: Good APIs are not just functional — they are predictable, scalable, and easy to use. Currently building a production-ready backend system — sharing real learnings daily. https://lnkd.in/gJqEuQQs #Java #SpringBoot #BackendDevelopment #RESTAPI #SoftwareEngineering

Starting Something New… Most tutorials teach features. But real systems are different. So I decided to challenge myself I’m building a MakeMyTrip-like travel booking system from scratch. Not just coding — I’ll document everything: Backend with Spring Boot & Microservices Database design using MySQL Real system design decisions Features like booking, payments, and search I’ll share everything publicly — step by step. No shortcuts. No skipping complexity. Goal: Become industry-ready + help others learn along the way. If you're into backend development or system design, follow this journey Let’s build something real #buildinpublic #java #springboot #systemdesign #developers

🚀 Mastering #Pagination in #BackendDevelopment (Spring Boot) Handling large datasets efficiently is a crucial skill for every developer. One concept that plays a key role in optimizing performance is Pagination. 🔍 What is Pagination? Pagination is the process of dividing large datasets into smaller, manageable chunks (pages) instead of loading everything at once. 💡 Why it matters? ✔ Improves application performance ✔ Reduces memory usage ✔ Enhances user experience ✔ Faster API responses 📊 Types of Pagination: 🔹 Offset-Based → Simple but slower for large data 🔹 Cursor-Based → Efficient and scalable 🔹 Keyset Pagination → Optimized for sorted data 🔹 Page-Based → Common in UI (page=1, size=10) 🔹 Infinite Scroll → Used in modern apps like social media ⚙️ Implementation in Spring Boot: Using Pageable and PageRequest, we can easily implement pagination in REST APIs. Example: GET /users?page=0&size=5 📌 Best Practices: ✔ Use offset pagination for small datasets ✔ Prefer cursor pagination for large datasets ✔ Always add sorting ✔ Avoid large offsets (performance issues) ✔ Use indexing for better speed 💬 Key Takeaway: Pagination is not just a feature—it’s a necessity for building scalable and high-performance applications. #Java #SpringBoot #BackendDevelopment #SoftwareEngineering #API #Pagination #TechLearning #Developers #Coding

A harsh reality but bitter truth... Why are you integrating backend with the frontend through the apis... Most developers still treat APIs like this: 𝐁𝐮𝐢𝐥𝐝 𝐛𝐚𝐜𝐤𝐞𝐧𝐝 → 𝐞𝐱𝐩𝐨𝐬𝐞 𝐞𝐧𝐝𝐩𝐨𝐢𝐧𝐭𝐬 → 𝐰𝐫𝐢𝐭𝐞 𝐝𝐨𝐜𝐬 → 𝐦𝐚𝐧𝐮𝐚𝐥𝐥𝐲 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐟𝐫𝐨𝐧𝐭𝐞𝐧𝐝 → 𝐝𝐞𝐛𝐮𝐠 𝐢𝐧𝐜𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐜𝐢𝐞𝐬 𝐟𝐨𝐫 𝐰𝐞𝐞𝐤𝐬 Then there is a workflow that quietly removes most of that friction. #SDK generation from Postman. You define the API once, and it is no longer just a collection of endpoints. It becomes production ready SDKs in Python, C#, C++, TypeScript, JavaScript, and more. Typed clients. Prebuilt methods. Consistent contracts. No repetitive API wiring. 𝐍𝐨𝐰 𝐜𝐨𝐦𝐩𝐚𝐫𝐞 𝐭𝐡𝐞 𝐢𝐦𝐩𝐚𝐜𝐭: 𝙏𝙧𝙖𝙙𝙞𝙩𝙞𝙤𝙣𝙖𝙡 𝘼𝙋𝙄 𝙞𝙣𝙩𝙚𝙜𝙧𝙖𝙩𝙞𝙤𝙣 20 to 35 #days of development, testing, and alignment 𝙎𝘿𝙆 𝙗𝙖𝙨𝙚𝙙 𝙞𝙣𝙩𝙚𝙜𝙧𝙖𝙩𝙞𝙤𝙣 4 to 7 #days to connect backend with frontend systems with consistent behavior across platforms This is not a productivity improvement. This is a shift in how backend services are consumed. Less glue code. Fewer integration bugs. Faster delivery cycles. Cleaner architecture boundaries. The real question is not whether SDK generation is useful. The question is how many teams are still ignoring it while spending weeks on manual integration. 𝐓𝐡𝐢𝐬 𝐒𝐃𝐊 𝐜𝐚𝐧 𝐛𝐞 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐢𝐧 𝟐 𝐭𝐨 𝟒 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚𝐧𝐲 𝐀𝐈 𝐭𝐨𝐨𝐥𝐢𝐧𝐠: 𝐆𝐢𝐭𝐇𝐮𝐛 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲 https://lnkd.in/dQfJbMN8 Appreciation to Postman and its #team for enabling this level of #developer experience. 𝐇𝐚𝐯𝐞 𝐲𝐨𝐮 𝐮𝐬𝐞𝐝 𝐏𝐨𝐬𝐭𝐦𝐚𝐧 𝐒𝐃𝐊 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐚 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦? 𝐈𝐟 𝐲𝐞𝐬, 𝐢𝐭 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐜𝐡𝐚𝐧𝐠𝐞𝐬 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐝𝐞𝐬𝐢𝐠𝐧 𝐀𝐏𝐈𝐬 𝐩𝐞𝐫𝐦𝐚𝐧𝐞𝐧𝐭𝐥𝐲. #Postman #SDK #APIs #SoftwareEngineering #Backend #Frontend #SystemDesign #Microservices #DeveloperExperience #TypeScript #Python #CSharp

Days 55–75 of #100DaysOfCode 🚀 Stepping deeper into full-stack development and production-ready systems while refining both backend and integration skills. 🔹 Built more advanced REST APIs with improved architecture and performance 🔹 Strengthened authentication systems (JWT, role-based access control) 🔹 Improved database design, relationships, and optimization techniques 🔹 Integrated frontend and backend into complete working applications 🔹 Explored deployment workflows and hosting (getting projects online) 🔹 Practiced testing, debugging, and handling real-world edge cases 🔹 Started focusing on writing cleaner, scalable, maintainable code This phase is about moving from just building features → to building real-world systems that can scale and perform reliably. Still learning. Still building. Still consistent. #100DaysOfCode #FullStackDevelopment #BackendDevelopment #JavaScript #NodeJS #APIs #WebDevelopment #SoftwareEngineering #LearningInPublic

Folks, Building APIs is easy… But designing scalable & production-ready APIs is what really matters. 👉 This is where API Design Best Practices come in. 🔧 How it works in real systems: 🔹 Use clear & consistent endpoint naming 🔹 Follow proper HTTP methods (GET, POST, PUT, DELETE) 🔹 Maintain standard response structure 🔹 Version your APIs (/v1/api/...) 🔹 Implement pagination & filtering 🔹 Handle errors with proper status codes ⚙️ Example: ✔️ /users → GET (fetch users), POST (create user) ✔️ /v1/payments → Versioned APIs ✔️ ?page=1&size=10 → Pagination ✔️ 400 / 404 / 500 → Standard error handling 💡 Key Insight: A well-designed API is not just functional — it is easy to use, scalable, and maintainable. 🔐 Why it matters: ✔️ Better frontend-backend collaboration ✔️ Scalable microservices architecture ✔️ Clean & maintainable codebase — Asad | Java Backend Developer #Java #SpringBoot #API #SystemDesign #Microservices #BackendDevelopment #LearningSeries

🚀 Backend Learning | API Versioning for Scalable Systems While working on backend systems, I recently explored how to handle API changes without breaking existing clients. 🔹 The Problem: • Updating APIs can break existing consumers • Different clients may depend on different API versions • Difficult to maintain backward compatibility 🔹 What I Learned: • URI Versioning: /api/v1/orders → /api/v2/orders • Header Versioning: Using custom headers for version control • Query Params: version=1 (less preferred) 🔹 Key Insights: • Always maintain backward compatibility • Version only when breaking changes are introduced • Plan versioning strategy early in system design 🔹 Outcome: • Smooth API evolution without breaking clients • Better maintainability • Improved developer experience Good APIs are not just designed — they are evolved carefully over time. 🚀 #Java #SpringBoot #BackendDevelopment #APIDesign #SystemDesign #Microservices #LearningInPublic