10 Essential cURL Commands for Backend Developers

𝗬𝗼𝘂𝗿 𝗔𝗣𝗜 𝗿𝗲𝘁𝘂𝗿𝗻𝗲𝗱 𝟮𝟬𝟬. 𝗕𝘂𝘁 𝘁𝗵𝗲 𝗿𝗲𝗾𝘂𝗲𝘀𝘁 𝗳𝗮𝗶𝗹𝗲𝗱. 𝗔𝗻𝗱 𝘆𝗼𝘂 𝗰𝗮𝗹𝗹𝗲𝗱 𝘁𝗵𝗮𝘁 𝗮 𝘀𝘂𝗰𝗰𝗲𝘀𝘀. This is one of the most common API mistakes I see. Returning 200 OK for everything then burying the real result in the response body. { "success": false, "message": "User not found" } The client got a 200. But the user wasn’t found. That’s not a success. That’s a lie. 𝗛𝗧𝗧𝗣 𝘀𝘁𝗮𝘁𝘂𝘀 𝗰𝗼𝗱𝗲𝘀 𝗲𝘅𝗶𝘀𝘁 𝗳𝗼𝗿 𝗮 𝗿𝗲𝗮𝘀𝗼𝗻. They’re not decoration. They’re a contract between your API and everyone who consumes it. 𝗧𝗵𝗲 𝗰𝗼𝗱𝗲𝘀 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗺𝗮𝘁𝘁𝗲𝗿: • 200 → Success, here’s your data • 201 → Created successfully • 400 → Bad request, fix your input • 401 → Not authenticated • 403 → Authenticated, but not allowed • 404 → Resource doesn’t exist • 409 → Conflict, something already exists • 422 → Validation failed • 500 → Server broke, not the client’s fault 𝗪𝗵𝗲𝗻 𝘆𝗼𝘂 𝗿𝗲𝘁𝘂𝗿𝗻 𝘁𝗵𝗲 𝘄𝗿𝗼𝗻𝗴 𝘀𝘁𝗮𝘁𝘂𝘀 𝗰𝗼𝗱𝗲: • Frontend devs write broken error handling • Mobile apps show wrong messages to users • Debugging takes twice as long • Your API becomes unpredictable 𝗔 𝗴𝗼𝗼𝗱 𝗔𝗣𝗜 𝘂𝘀𝗲𝘀 𝘀𝘁𝗮𝘁𝘂𝘀 𝗰𝗼𝗱𝗲𝘀 𝗮𝗻𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗯𝗼𝗱𝗶𝗲𝘀 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. The status code tells you what happened. The body tells you why. { "status": 404, "message": "User not found" } { "status": 422, "message": "Phone number is required" } Clear enough to debug. Careful enough not to expose sensitive internals. 𝗗𝗷𝗮𝗻𝗴𝗼 𝗥𝗘𝗦𝗧 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗺𝗮𝗸𝗲𝘀 𝘁𝗵𝗶𝘀 𝗲𝗮𝘀𝘆. No excuses. 𝗨𝘀𝗲 𝘀𝘁𝗮𝘁𝘂𝘀 𝗰𝗼𝗱𝗲𝘀 𝗹𝗶𝗸𝗲 𝘆𝗼𝘂 𝗺𝗲𝗮𝗻 𝘁𝗵𝗲𝗺. Your API is a conversation. Make sure it’s saying the right thing. #Django #Python #BackendDevelopment #APIDesign #WebDevelopment #SoftwareEngineering

🚀 Tired of writing try-catch in every controller? There’s a better way 👇 --- 👉 Problem: @RestController public class UserController { @GetMapping("/user/{id}") public User getUser(@PathVariable int id) { try { return userService.getUser(id); } catch (Exception e) { return null; // ❌ bad practice } } } ❌ Issues: - Repeated code - Messy controllers - Hard to maintain --- ✅ Solution → Global Exception Handling Use @ControllerAdvice + @ExceptionHandler --- 💡 Example: @ControllerAdvice public class GlobalExceptionHandler { @ExceptionHandler(Exception.class) public ResponseEntity<String> handleException(Exception ex) { return new ResponseEntity<>("Something went wrong", HttpStatus.INTERNAL_SERVER_ERROR); } } --- 👉 Now, any exception in your app: ✔ Automatically handled ✔ Clean response returned ✔ No try-catch in controllers --- 🔥 Handle specific exceptions: @ExceptionHandler(UserNotFoundException.class) public ResponseEntity<String> handleUserNotFound(UserNotFoundException ex) { return new ResponseEntity<>(ex.getMessage(), HttpStatus.NOT_FOUND); } --- ⚡ Real-world impact: Without this: ❌ Inconsistent error responses ❌ Debugging becomes hard With this: ✅ Clean API responses ✅ Centralized error handling ✅ Production-ready backend --- 📌 Key Takeaway: Don’t handle exceptions everywhere… Handle them in ONE place. --- Follow for more real backend learnings 🚀 #SpringBoot #Java #BackendDevelopment #CleanCode #SoftwareEngineer

async/await didn't make your code faster. It just made the slowness harder to see. ───────────────────────── Most devs write this and ship it with confidence: const user = await getUser(id) const posts = await getPosts(id) const comments = await getComments(id) Clean. Readable. And quietly costing you 3x the wait time. ───────────────────────── Here's what's actually happening under the hood 👇 async/await is syntax sugar over Promises. Your linear-looking code compiles into a Promise chain. await doesn't block the thread — it pauses that function and resumes it later. Which means: you can run things in parallel. You're just choosing not to. ───────────────────────── The sequential trap When you await three independent requests in a row, you're making them wait for each other — for no reason. Total time = request1 + request2 + request3 On a slow network, that gap is seconds, not milliseconds. ───────────────────────── The fix: Promise.all const [user, posts, comments] = await Promise.all([ getUser(id), getPosts(id), getComments(id) ]) Total time = slowest request only. ───────────────────────── When one failure shouldn't kill the rest: Promise.allSettled Promise.all fails fast — one rejection kills everything. Promise.allSettled lets every Promise finish and returns each result individually. Use it when partial failure is acceptable. ───────────────────────── The error handling gap nobody talks about A floating Promise that rejects has nowhere to go. No catch. No log. Silent failure in production. Rule: every Promise either gets awaited inside a try/catch, or gets a .catch() attached. No exceptions. ───────────────────────── One question that saves you every time: Before writing a second await — ask yourself: Does this actually need to wait for the previous one? If the answer is no, run them together. ───────────────────────── This post took me 5 seconds to write and 2 years of production bugs to learn. If it saves you the same bugs — repost it for your team ♻️ #JavaScript #WebPerformance #FrontendDevelopment #WebDev #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

🚀 Understanding HTTP Status Codes (Every Developer Should Know) When working with APIs, debugging issues, or testing endpoints in Postman, HTTP status codes are your first clue to what’s happening behind the scenes. Let’s break it down in a simple way 👇 🔹 1xx – Informational Request received, continuing process (rarely used in day-to-day development) 🔹 2xx – Success ✅ ✔️ 200 OK → Request successful ✔️ 201 Created → Resource created (POST API) ✔️ 204 No Content → Success but no response body 🔹 3xx – Redirection 🔁 ✔️ 301 → Permanently moved ✔️ 302 → Temporary redirect 🔹 4xx – Client Errors ⚠️ (Your request has an issue) ❌ 400 Bad Request → Invalid data sent ❌ 401 Unauthorized → Missing/invalid authentication ❌ 403 Forbidden → No permission ❌ 404 Not Found → API or resource doesn’t exist 🔹 5xx – Server Errors 💥 (Server-side problem) ❌ 500 Internal Server Error → Something broke in backend ❌ 503 Service Unavailable → Server overloaded/down 💡 Pro Tip: Good APIs don’t just return status codes — they return meaningful error messages. Example: { "success": false, "message": "Invalid user ID", "statusCode": 400 } 📌 Why this matters: Understanding these codes helps you debug faster, build better APIs, and communicate clearly between frontend & backend. #WebDevelopment #API #Backend #NodeJS #MERN #Postman #SoftwareDevelopment #Coding

𝗔𝘀 𝗯𝗮𝗰𝗸𝗲𝗻𝗱 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀, 𝘄𝗲’𝗿𝗲 𝘁𝗮𝘂𝗴𝗵𝘁 𝗲𝗮𝗿𝗹𝘆 𝗼𝗻 𝘁𝗼 𝗮𝘃𝗼𝗶𝗱 𝗡+𝟭 𝗾𝘂𝗲𝗿𝗶𝗲𝘀. And yet… most of us still ship them to production like it’s a feature. Not gonna lie - I’ve shipped it too without realizing. N+1 is simple: 1 query to fetch the list, N more queries for each item. Congrats, you just turned one request into a DB stress test. Everything works fine… until it doesn’t. Slow APIs, spiking DB load, and suddenly your “clean code” is the bottleneck. But sure, blame the ORM - it was just “magically fetching relations,” right? Reality check: the ORM didn’t write bad queries. You did. You don’t really notice it… until your DB starts feeling it. Pay attention to them. They matter more than you think. #BackendDevelopment #JavaDeveloper #SpringBoot #APIDesign #DatabasePerformance #NPlusOne #SoftwareEngineering #CleanCode #PerformanceMatters #DevelopersLife #ScalableSystems #ORM #DevCommunity

𝗛𝗼𝘄 𝗚𝗮𝗿𝗯𝗮𝗴𝗲 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 𝗪𝗼𝗿𝗸𝘀 𝗶𝗻 𝗡𝗼𝗱𝗲.𝗷𝘀 As developers, we often focus on writing efficient code—but what about memory management behind the scenes? In 𝗡𝗼𝗱𝗲.𝗷𝘀, garbage collection (GC) is handled automatically by the 𝗩𝟴 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 𝗲𝗻𝗴𝗶𝗻𝗲, so you don’t need to manually free memory like in languages such as C or C++. But understanding how it works can help you write more optimized and scalable applications. 𝗞𝗲𝘆 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀: 𝟭. 𝗠𝗲𝗺𝗼𝗿𝘆 𝗔𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 Whenever you create variables, objects, or functions, memory is allocated in two main areas: Stack→ Stores primitive values and references Heap→ Stores objects and complex data 𝟮. 𝗚𝗮𝗿𝗯𝗮𝗴𝗲 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 (𝗠𝗮𝗿𝗸-𝗮𝗻𝗱-𝗦𝘄𝗲𝗲𝗽) V8 uses a technique called Mark-and-Sweep: * It starts from “root” objects (global scope) * Marks all reachable objects * Unreachable objects are considered garbage * Then, it sweeps (removes) them from memory 𝟯. 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗚𝗮𝗿𝗯𝗮𝗴𝗲 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻 Not all objects live the same lifespan: Young Generation (New Space) → Short-lived objects Old Generation (Old Space) → Long-lived objects Objects that survive multiple GC cycles get promoted to the Old Generation. 𝟰. 𝗠𝗶𝗻𝗼𝗿 & 𝗠𝗮𝗷𝗼𝗿 𝗚𝗖 Minor GC (Scavenge)→ Fast cleanup of short-lived objects Major GC (Mark-Sweep / Mark-Compact) → Handles long-lived objects but is more expensive 𝟱. 𝗦𝘁𝗼𝗽-𝘁𝗵𝗲-𝗪𝗼𝗿𝗹𝗱 During GC, execution pauses briefly. Modern V8 minimizes this with optimizations like incremental and concurrent GC. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗠𝗲𝗺𝗼𝗿𝘆 𝗜𝘀𝘀𝘂𝗲𝘀: * Memory leaks due to unused references * Global variables holding data unnecessarily * Closures retaining large objects 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀: * Avoid global variables * Clean up event listeners and timers * Use streams for large data processing * Monitor memory using tools like Chrome DevTools or `--inspect` Understanding GC = Writing better, faster, and scalable applications #NodeJS #JavaScript #BackendDevelopment #V8 #Performance #WebDevelopment

Built a production-style video transcoding platform from scratch — and it turned out to be one of the more interesting system design exercises I've done. The core challenge: how do you handle large file uploads and heavy processing (FFmpeg-based transcoding) without your backend becoming a bottleneck? The approach I went with: → Multipart uploads with pre-signed S3 URLs — the client uploads directly to S3, the backend never touches the bytes → SQS-based job queue to decouple uploads from processing → Worker service that long-polls the queue, transcodes into 720p/480p, and writes back to S3 → JWT auth with short-lived access tokens + refresh tokens in HTTP-only cookies, with JTI tracked in Redis for session invalidation The stack: React + TypeScript frontend, Python/FastAPI backend, Dockerized multi-service setup. The part I found most valuable wasn't the code — it was thinking through where failures happen in a distributed pipeline and how to design around them. Architecture decisions you make early (sync vs async, where auth lives, how you structure worker retry logic) end up mattering a lot more than they seem when you're just starting out. Still iterating — especially around reliability, retries, and failure handling in distributed systems. Here is the link to the repo : https://lnkd.in/gbyxKY3j #BackendDevelopment #SystemDesign #DistributedSystems #SoftwareEngineering #FastAPI #Docker #AWS

🌐 REST API Design — Small Decisions, Big Impact Writing APIs that work is easy. Designing APIs well is engineering. Here are some REST API practices I focus on 👇 ✅ 1. Use Proper HTTP Methods GET → Fetch data POST → Create PUT/PATCH → Update DELETE → Remove ✅ 2. Use Resource-Based URLs Good: /api/users/101/orders Avoid: /getUserOrdersById ✅ 3. Return Proper Status Codes 200 → Success 201 → Created 400 → Bad Request 401 → Unauthorized 404 → Not Found 500 → Server Error ✅ 4. Use DTOs + Validation Validate requests early: @Valid @NotBlank @Email Clean input = safer APIs. ✅ 5. Keep Responses Consistent { "success": true, "message": "Order created", "data": {...} } Consistency improves frontend integration. 🚀 In my projects I also use: ✔ Pagination ✔ Versioning (/api/v1) ✔ Exception handling ✔ Meaningful endpoint naming 🧠 Key Insight: Good APIs reduce bugs before they happen. What API practice do you consider non-negotiable? #Java #SpringBoot #RESTAPI #BackendDevelopment #SoftwareEngineering #FullStackDeveloper

🚀 Day 118 — Strengthening Backend Security with Express Validator 🔐 Today’s focus was on implementing robust input validation using Express Validator — a critical step in building secure, production-ready APIs. 💡 Key Highlights: ✨ Why Validation Matters • Ensures only valid data enters the system • Prevents malicious or incorrect inputs • Improves overall API reliability ⚙️ Core Concepts Covered • Validating req.body, req.params, and req.query • Using validation chains like body(), check() • Extracting errors with validationResult() 🛡️ Practical Implementation • Applied rules like required fields, email format, min length • Structured error handling for clean API responses • Prevented invalid data from reaching backend logic 📈 Outcome Built a stronger foundation for secure, scalable backend systems by enforcing proper validation and error handling — a must-have skill for real-world development. ⸻ #backenddevelopment #nodejs #expressjs #apidevelopment #websecurity #fullstackdeveloper #softwareengineering #codingjourney #buildinpublic #learninpublic #developers #techskills