Umesh Dangar’s Post

Understanding Async vs Sync API Handling in Node.js (A Practical Perspective) When building scalable backend systems, one concept that truly changes how you think is synchronous vs asynchronous API handling. Let’s break it down in a simple, real-world way. Synchronous (Blocking) Execution In a synchronous flow, tasks are executed one after another. Example: - Request comes in - Server processes it - Only after completion → next request is handled Problem: If one operation takes time (like a database query or external API call), everything waits. This leads to: - Poor performance - Low scalability - Bad user experience under load Asynchronous (Non-Blocking) Execution Node.js shines because it handles operations asynchronously. Example: - Request comes in - Task is sent to the background (I/O operation) - Server immediately moves to handle the next request - Response is returned when the task completes Result: - High performance - Handles thousands of concurrent users - Efficient resource utilization How Node.js Makes This Possible: - Event Loop - Callbacks / Promises / Async-Await - Non-blocking I/O Instead of waiting, Node.js keeps moving. Real-World Insight: When working with APIs: - Use async/await for clean and readable code - Avoid blocking operations (like heavy computations on the main thread) - Handle errors properly in async flows Final Thought: The real power of Node.js is not just JavaScript on the server — it’s how efficiently it handles concurrency without threads. Mastering async patterns is what separates a beginner from a solid backend engineer. Curious to know: What challenges have you faced while handling async operations? #NodeJS #BackendDevelopment #JavaScript #AsyncProgramming #WebDevelopment

async/await doesn't make your code faster. It makes your code non-blocking. These are NOT the same thing. I see this misunderstood constantly — even in codebases with senior devs. Example: // This is still sequential. Both await one after the other. const user = await getUser(id); const orders = await getOrders(id); // Total time: time(getUser) + time(getOrders) // This runs BOTH at the same time. const [user, orders] = await Promise.all([getUser(id), getOrders(id)]); // Total time: max(time(getUser), time(getOrders)) If getUser takes 200ms and getOrders takes 300ms: → Sequential: 500ms → Parallel: 300ms That's a 40% reduction from changing 2 lines. When I applied this pattern to our fintech API (replacing sequential DB calls),  average response time dropped from 340ms to 180ms. The concept: async/await is about WAITING EFFICIENTLY. Not about doing things faster — about not blocking while you wait. Use Promise.all when: ✅ Calls are independent (don't need result A to start B) ✅ You want the fastest possible response ✅ Failure of one should cancel all (add Promise.allSettled for partial) Don't use Promise.all when: ❌ Call B depends on result from Call A ❌ You need strict ordering Save this. Share it with your team. #NodeJS #JavaScript #Backend #AsyncProgramming #WebDevelopment

🎬 𝐄𝐯𝐞𝐫𝐲 𝐛𝐥𝐨𝐜𝐤𝐛𝐮𝐬𝐭𝐞𝐫 𝐦𝐨𝐯𝐢𝐞 𝐡𝐚𝐬 𝐨𝐧𝐞 𝐫𝐮𝐥𝐞 𝐨𝐧 𝐬𝐞𝐭 — No one waits for anyone else to finish their scene. ━━━━━━━━━━━━━━━━━━━━━━━ 𝗧𝗵𝗮𝘁'𝘀 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝗵𝗼𝘄 𝗡𝗼𝗱𝗲.𝗷𝘀 𝗲𝘃𝗲𝗻𝘁 𝗱𝗿𝗶𝘃𝗲𝗻 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝘄𝗼𝗿𝗸𝘀. 🧵 Node.js Event Driven Architecture ━━━━━━━━━━━━━━━━━━━━━━━ 𝗧𝗵𝗲 𝗖𝗼𝗿𝗲 𝗣𝗵𝗶𝗹𝗼𝘀𝗼𝗽𝗵𝘆 𝗘𝘃𝗲𝗿𝘆 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗗𝗲𝘃 𝗦𝗵𝗼𝘂𝗹𝗱 𝗦𝘁𝗮𝗿𝘁 𝗪𝗶𝘁𝗵 Most traditional backends think like this — → Request comes in → Server processes it → Response goes out Linear. Blocking. Predictable — but not scalable. Node.js flips this entirely. ━━━━━━━━━━━━━━━ 𝗧𝗵𝗲 𝟯 𝗣𝗶𝗹𝗹𝗮𝗿𝘀 𝗼𝗳 𝗘𝘃𝗲𝗻𝘁 𝗗𝗿𝗶𝘃𝗲𝗻 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: ━━━━━━━━━━━━━━━ 1️⃣ 𝗘𝘃𝗲𝗻𝘁 𝗘𝗺𝗶𝘁𝘁𝗲𝗿 — fires the signal. Something happened. 2️⃣ 𝗘𝘃𝗲𝗻𝘁 𝗟𝗶𝘀𝘁𝗲𝗻𝗲𝗿 — watches and waits for that signal. 3️⃣ 𝗘𝘃𝗲𝗻𝘁 𝗖𝗮𝗹𝗹𝗯𝗮𝗰𝗸 — reacts the moment the signal arrives. This is called the 𝗢𝗯𝘀𝗲𝗿𝘃𝗲𝗿 𝗣𝗮𝘁𝘁𝗲𝗿𝗻 — and it's the backbone of how Node.js handles thousands of concurrent connections without breaking a sweat. ━━━━━━━━━━━━━━━ 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝗸𝗲𝘀 𝗡𝗼𝗱𝗲 𝘀𝗰𝗮𝗹𝗲: ━━━━━━━━━━━━━━━ → Components don't call each other directly → They emit events and let listeners react independently → That's 𝗹𝗼𝗼𝘀𝗲 𝗰𝗼𝘂𝗽𝗹𝗶𝗻𝗴 — the foundation of every scalable backend system One event. Multiple listeners reacting independently — logging, auth, analytics — all at once. No blocking. No waiting. Express, NestJS, Socket.io — all built on this exact idea. 🚀 Next post — this in real code. 👀 #NodeJS #BackendDevelopment #JavaScript #SystemDesign #EventDriven #Developer

🚀 Skill Boosters — Notes #6: Struggling to understand how Node.js handles multiple requests? Let’s simplify it 👇 Link: https://lnkd.in/ebN-Cdmy In Node.js, everything revolves around a few powerful concepts: 👉 Event Loop 👉 Single Thread 👉 Asynchronous Programming 👉 Event-Driven Architecture 💡 Here’s the magic: Node.js is single-threaded, yet it can handle thousands of users at the same time. How? Because it doesn’t wait. 🔄 Event Loop Think of it as a manager that keeps checking: “Is the main thread free?” “Yes? Let’s execute the next task.” ⚡ Async > Sync Instead of blocking: ✔ Sends heavy tasks (API, DB, file) to background ✔ Continues handling other requests ✔ Comes back when task is done 🧵 Single Thread ≠ Slow Node.js uses: 👉 Single thread for execution 👉 + Background threads (libuv) for heavy work 🎧 Event-Driven System Everything is based on events: Request comes → event triggered Task completes → callback executed 🔥 Real Power This combination makes Node.js: ✔ Fast ✔ Scalable ✔ Perfect for APIs & real-time apps 💭 One Line Takeaway: 👉 Node.js= Single Thread + Event Loop + Async = High Performance Backend If you're building backend systems, mastering this is a game changer. 💬 What confused you the most about Node.js earlier? Event loop or async? #NodeJS #BackendDevelopment #JavaScript #WebDevelopment #SystemDesign #Programming

⚠️ STOP using any in TypeScript. It’s not flexibility… it’s silent technical debt. You’ve written this 👇 let data: any; Looks harmless. Feels fast. But here’s what you actually did: 🧨 You lose type safety — TypeScript stops protecting you. 🧩 You lose IntelliSense — your IDE can’t autocomplete or infer. 🕳️ You lose refactor confidence — renames and changes won’t propagate. 🐛 You gain runtime bugs — errors sneak past compile‑time checks. Using any is like: 🚗 Driving without a seatbelt 🧪 Skipping tests “just for now” 🧱 Removing guardrails from your code It works… until it doesn’t. 🧠 Why We Still Use It Be honest 👇 • “I’ll fix types later” • “API response is messy” • “This is just a quick hack” 👉 That “temporary” any? It never gets removed. ✅ What Senior Devs Do Instead They don’t avoid flexibility. They use safe flexibility 👇 ✔️ unknown → forces validation ✔️ generics <T> → reusable + type-safe ✔️ interface / type → clear data contracts ✔️ Partial<T> → safe optional updates ✔️ Record<K, V> → structured dynamic objects ⚡ Angular Reality Check ❌ Bad: getTickets(): any { return this.http.get('/api/tickets'); } ✅ Good: getTickets(): Observable<Ticket[]> { return this.http.get<Ticket[]>('/api/tickets'); } Now your: ✨ IDE helps you ✨ Compiler protects you ✨ Bugs get caught early 🧩 Golden Rule 👉 If you use any, you’re telling TypeScript: “Don’t help me. I’ll debug in production.” Where have you seen any create real problems? (or are you still using it 👀) 👇 Drop your experience 🔖 Save this before your next refactor #Angular #TypeScript #Frontend #CleanCode #WebDevelopment #SoftwareEngineering #JavaScript #DevCommunity

📘 How Node.js Works While learning Node.js, I explored what happens behind the scenes 👇 ⚙️ Core Components: 🧵 Call Stack Executes JavaScript code (single-threaded) 📥 Event Queue Stores async callbacks (setTimeout, API responses) 🛠️ Thread Pool (libuv) Handles heavy tasks (File I/O, Crypto, DB) 🧑💻 Worker Threads Used for CPU-intensive operations 🔁 Event Loop Moves tasks from queue → call stack 🔄 Event Loop Phases (Execution Order): 1️⃣ Timers Phase → Executes setTimeout / setInterval callbacks 2️⃣ I/O Callbacks Phase → Handles completed I/O operations 3️⃣ Idle / Prepare → Internal phase (Node.js setup) 4️⃣ Poll Phase ⭐ (MOST IMPORTANT) → Executes I/O callbacks → Waits for new events 5️⃣ Check Phase → Executes setImmediate() 6️⃣ Close Callbacks → Handles closing events (e.g., socket.close) ⚡ Priority (VERY IMPORTANT): Microtasks Queue (Highest Priority) → Promise.then(), process.nextTick() Event Loop Phases (in order above) 👉 Microtasks always run BEFORE moving to next phase 💡 Why it matters: This is why Node.js is: ⚡ Non-blocking ⚡ Efficient ⚡ Scalable 🧠 My takeaway: Understanding event loop phases + priority helps avoid bugs and write high-performance backend code. #NodeJS #JavaScript #BackendDeveloper #SystemDesign #LearningInPublic

𝐃𝐚𝐲 1/30 – 𝐍𝐨𝐝𝐞.𝐣𝐬 𝐒𝐞𝐫𝐢𝐞𝐬: 𝐖𝐡𝐚𝐭 𝐍𝐨𝐝𝐞.𝐣𝐬 𝐫𝐞𝐚𝐥𝐥𝐲 𝐢𝐬 (𝐛𝐞𝐲𝐨𝐧𝐝 𝐭𝐡𝐞 𝐝𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧) Most people say: 👉 “Node.js is a JavaScript runtime built on Chrome’s V8 engine.” That’s correct… but honestly, it’s not useful in real-world discussions. Let’s understand it like an engineer 💡 𝐍𝐨𝐝𝐞.𝐣𝐬 𝐢𝐬 𝐍𝐎𝐓 𝐣𝐮𝐬𝐭 𝐚 𝐫𝐮𝐧𝐭𝐢𝐦𝐞 — 𝐢𝐭’𝐬 𝐚𝐧 𝐞𝐯𝐞𝐧𝐭-𝐝𝐫𝐢𝐯𝐞𝐧, 𝐧𝐨𝐧-𝐛𝐥𝐨𝐜𝐤𝐢𝐧𝐠 𝐬𝐲𝐬𝐭𝐞𝐦 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐟𝐨𝐫 𝐡𝐚𝐧𝐝𝐥𝐢𝐧𝐠 𝐜𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐭 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭𝐥𝐲. What does that mean? 1. It uses a 𝐬𝐢𝐧𝐠𝐥𝐞-𝐭𝐡𝐫𝐞𝐚𝐝𝐞𝐝 𝐞𝐯𝐞𝐧𝐭 𝐥𝐨𝐨𝐩 2. It delegates heavy tasks (I/O, network, file operations) to the system 3. It doesn’t wait… it keeps moving 🔁 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐞𝐱𝐚𝐦𝐩𝐥𝐞: Imagine your backend API is: 1. Reading files 2. Calling external APIs 3. Querying databases In traditional blocking systems: ➡ One request waits for another In Node.js: ➡ Multiple requests are handled 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐰𝐚𝐢𝐭𝐢𝐧𝐠 🧠 𝐒𝐢𝐦𝐩𝐥𝐞 𝐚𝐧𝐚𝐥𝐨𝐠𝐲: Node.js is like a smart manager: Assigns tasks to workers Doesn’t sit idle Keeps taking new tasks ⚠️ 𝐁𝐮𝐭 𝐡𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐭𝐫𝐮𝐭𝐡 𝐦𝐨𝐬𝐭 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬 𝐬𝐤𝐢𝐩: Node.js is NOT always the best choice. ❌ CPU-heavy tasks (like image processing, large calculations) can block the event loop ❌ Poor async handling can still cause performance issues 🔥 𝐅𝐫𝐨𝐦 𝐦𝐲 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: In one of my projects, instead of processing everything synchronously, we used 𝐪𝐮𝐞𝐮𝐞-𝐛𝐚𝐬𝐞𝐝 𝐚𝐬𝐲𝐧𝐜 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 (similar to Service Bus pattern). This helped us: ✔ Avoid API timeouts ✔ Handle large workloads ✔ Improve system scalability ✅ 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲: Node.js shines when: ✔ You have I/O-heavy applications ✔ You need high concurrency ✔ You design it with async patterns correctly 📌 Tomorrow (Day 2): 𝐃𝐞𝐞𝐩 𝐝𝐢𝐯𝐞 𝐢𝐧𝐭𝐨 𝐄𝐯𝐞𝐧𝐭 𝐋𝐨𝐨𝐩 (𝐭𝐡𝐞 𝐡𝐞𝐚𝐫𝐭 𝐨𝐟 𝐍𝐨𝐝𝐞.𝐣𝐬) #NodeJS #BackendDevelopment #JavaScript #FullStack #SoftwareEngineering #SystemDesign

🔴 Race Conditions in Backend Systems (Call Stack + Async Reality Explained) Most developers think race conditions happen because “multiple threads execute at the same time.” But in Node.js, it’s deeper than that—even a single-threaded system can produce race conditions. --- 🧠 The Problem We have a simple API: async function increment() { const value = await db.read(); // READ const newValue = value + 1; // MODIFY await db.write(newValue); // WRITE } Initial state: count = 10 Two requests hit at the same time: Request A → increment() Request B → increment() --- 🔥 What actually happens (Call Stack view) 🟢 Step 1: Request A starts CALL STACK: increment(A) A reaches await db.read() → function is removed from stack. CALL STACK: EMPTY --- 🟢 Step 2: Request B starts CALL STACK: increment(B) B also reaches await db.read() → removed from stack. CALL STACK: EMPTY --- ⚠️ The critical moment Both requests execute DB read in parallel: A reads → 10 B reads → 10 ❗ (stale value) --- 🔁 Resume phase 🟡 A resumes first 10 → 11 → WRITE 🟡 B resumes later 10 → 11 → WRITE ❌ (overwrites A) --- 💥 Final result Expected: 12 ❌ Actual: 11 ❌ (lost update) --- 🧠 Key Insight Race condition is NOT about multiple threads. It happens because: > READ → MODIFY → WRITE is NOT atomic, and async execution creates time gaps where other requests can intervene. --- 🔐 Real Fixes Row locking (SELECT ... FOR UPDATE) Atomic updates (count = count + 1) Optimistic locking (versioning) --- 🚀 Takeaway Even in a single-threaded Node.js system: > concurrency + async pauses = interleaving execution = race conditions --- If you understand this stack-level flow, you don’t just “use backend APIs”—you understand how backend systems actually break and how to design them correctly. --- #NodeJS #Backend #SystemDesign #Databases #Concurrency #JavaScript #SoftwareEngineering

A few days ago, I encountered a memory spike issue in one of my Node.js services. Everything seemed fine initially, but the application continued to consume more memory over time. During this process, a junior developer on my team asked, “How is memory actually managed in Node.js?” This question made me pause, as we use it daily but rarely break it down simply. I explained it like this: 💡 “Think of Node.js memory like a workspace managed by V8.” There are two main areas: 🔹 Stack → small, fast, handles function calls and primitive values 🔹 Heap → larger, stores objects and dynamic data As our application runs, the heap continues to grow with objects. He then asked, “Who frees the memory?” That’s where the Garbage Collector (GC) comes in. I explained: 👉 V8 automatically identifies objects that are no longer reachable 👉 It removes them using: - Mark-Sweep → marks used memory and deletes unused memory - Scavenge → quickly manages short-lived objects “No need to manually free memory… unless you mess up references.” To make it practical, we used process.memoryUsage(). We ran a small script, observed the memory increase, and then saw the memory drop after the GC ran. That’s when it clicked for him. ⚡ Then came the real-world twist: I mentioned, “Problems arise when the GC cannot function properly…” This can happen when: 👉 You maintain unnecessary references 👉 You store large objects in memory 👉 You forget to clean caches These situations lead to memory leaks, causing your application to gradually fail. 🧠 My takeaway from this experience: Teaching someone else often deepens your own understanding. In backend engineering, it’s not just about writing code; it’s about comprehending what happens after it runs. If you're working with Node.js and haven't delved into memory management yet, it's definitely worth exploring. #NodeJS #JavaScript #BackendDevelopment

𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 #𝗩𝗶𝘀𝘂𝗮𝗹𝗟𝗼𝗴𝗶𝗰𝗘𝗻𝗴𝗶𝗻𝗲: 𝗠𝗼𝘃𝗶𝗻𝗴 𝗕𝗲𝘆𝗼𝗻𝗱 𝗦𝘁𝗮𝘁𝗶𝗰 𝗨𝗜 I’ve always been fascinated by "low-code" tools like Zapier, Node-RED and Mostly N8N, so I decided to build my own version from scratch. I’m excited to share a project I’ve been working on: 𝗔 𝗡𝗼𝗱𝗲-𝗕𝗮𝘀𝗲𝗱 𝗩𝗶𝘀𝘂𝗮𝗹 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲. It’s not just a UI; it’s a fully functional execution environment where you can orchestrate live API workflows. 𝗧𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: How do you let a user write code in a node, execute it safely, and make it "wait" for an API response before moving to the next node? 𝗧𝗵𝗲 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻: I built a custom execution engine using the AsyncFunction constructor. This allows each node to handle asynchronous tasks like fetch while passing data down the chain in real-time. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: ✅ 𝗔𝘀𝘆𝗻𝗰 𝗡𝗼𝗱𝗲 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻: Full support for async/await inside every node. ✅ 𝗗𝗮𝘁𝗮 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Pass the output of a POST request directly into a DELETE node. ✅ 𝗟𝗶𝘃𝗲 𝗖𝗼𝗻𝘀𝗼𝗹𝗲 𝗜𝗻𝗷𝗲𝗰𝘁𝗶𝗼𝗻: I intercepted the global console.log to provide real-time feedback within the UI. ✅ 𝗗𝘆𝗻𝗮𝗺𝗶𝗰 𝗦𝘁𝗮𝘁𝘂𝘀 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴: Visual feedback (Pending/Success/Error) using React Flow's state management. In the demo below, you can see a full 𝗖𝗥𝗨𝗗 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 using the DummyJSON API. The engine fetches a list, creates a new entry, updates it, and finally deletes it—all while animating the data flow. Next up: Adding persistent storage so users can save and share their logic flows! Github : https://lnkd.in/eK7h9vFc #ReactJS #TypeScript #ReactFlow #WebDevelopment #SoftwareEngineering #JavaScript #Programming React, Reactflow and Google