🗂️ Day 3: (Building in public: OpsFlow - Authorization - The Part Most Developers Get Wrong) Built the task management core today. Projects, tasks, members. Standard CRUD stuff. Except it's not. The Real Challenge: Not "can users create tasks?" but "can THIS user modify THIS specific task?" Here's where most apps fail: ❌ Authorization in middleware: `app.use('/tasks', verifyToken, taskRoutes)` Problem: Every task route needs different rules. Update = different from delete. ✅ Authorization in service layer: ```typescript async deleteTask(taskId: string, userId: string) { const task = await Task.findById(taskId); const project = await Project.findById(task.project); // Resource-level check, not route-level if (!project.hasAccess(userId)) { throw new AuthorizationError(); } // Action-level check if (task.createdBy !== userId && !project.isOwner(userId)) { throw new AuthorizationError("Only creator or owner can delete"); } } ``` Why this scales: 1. Business rules stay in one place 2. Can be tested independently 3. Flexible per-resource rules 4. Clear error messages The pattern I followed: • Project owners can do everything • Members can view + create tasks • Task creators can edit their tasks • Owners override all permissions Also added: • Pagination (page, limit, total) for list endpoints • Filtering (status, priority, assignee) • MongoDB indexes on query fields • Proper population of related data What I learned: Security isn't a feature you add. It's a constraint you design around from day one. Middleware is for "who are you?" Service layer is for "what can you do?" For juniors: Start with "deny by default" - explicitly allow what's needed, not the reverse. How do you handle resource-level authorization in your stack? #SoftwareArchitecture #Authorization #NodeJS #APIDesign #Security
Building OpsFlow: Authorization in Service Layer
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As a Java-based API developer, I often see teams struggling with one recurring question — should we build our next API with REST or GraphQL? Both sound promising, but the real answer depends on what you value more: simplicity or flexibility. Modern applications demand speed, scalability, and clean data handling. Yet, when APIs become complex, teams either over-fetch data or end up making endless endpoint calls that slow everything down. Option 1: REST API The traditional choice — simple, reliable, and well-documented. Perfect when your data requirements are predictable, and resources can be modeled clearly. It keeps things organised and is ideal for applications where stability and caching matter most. Option 2: GraphQL API A modern approach — flexible, efficient, and client-driven. It allows fetching exactly what’s needed, reducing payloads and network requests. It shines when front-end teams handle diverse data needs or when multiple clients consume the same backend differently. So, when should you choose what? Choose REST when you want consistency, simplicity, and faster onboarding for large teams. Choose GraphQL when you need agility, client-specific data responses, and minimal over-fetching. In short: REST gives you structure. GraphQL gives you control. The right choice isn’t about trends — it’s about aligning the API design with the problem you’re solving. Comment down your solution and why would you choose that, Let's make this a deep conversation. Got a scenario, where you are confused upon what to choose, Let me know in the comments.
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Add measurable performance goals to your development lifecycle. This article shows how to log execution time, memory consumption and database queries from Artisan. https://lnkd.in/eyU5bXG7 #laravel #metricstracking #developer #benchmarking #codewolfy
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HNG Tech 🚀 Just Built A RESTful API with External API Integration! I recently completed a backend challenge that pushed me to level up my Node.js skills. Here's what I built: ✨ The Project: A clean REST API endpoint that serves my profile information combined with real-time cat facts from an external API. Simple concept, but packed with learning! 🛠️ What I Built: - GET /me endpoint returning JSON data - Live integration with Cat Facts API - Dynamic timestamps (ISO 8601 format) - Graceful error handling with fallback strategies - Full CORS support and request logging 💡 Key Challenges & Solutions: 1️⃣ External API Reliability Problem: What if the cat facts API goes down? Solution: Implemented timeout handling (5s) and fallback messages. The app never breaks - it just returns a default fact. 2️⃣ Data Freshness Challenge: Ensure both timestamp and cat fact update on EVERY request Solution: No caching anywhere. Each request triggers a fresh API call and timestamp generation. 3️⃣ Code Organization Why it matters: Messy code = maintenance nightmare My approach: MVC architecture with separate layers for routes, controllers, and services. Each file has one job. 🏗️ Tech Stack: - Node.js & Express.js - Axios for HTTP requests - Deployed on Microsoft Azure App Service - GitHub for version control 📊 What This Taught Me: ✅ External API integration isn't just about making requests - it's about handling failures gracefully ✅ Error handling is as important as the happy path ✅ Modular code = easier testing & scaling ✅ Environment variables are your friend in production ✅ Deployment is a skill in itself (learned about Azure's App Service, environment configuration, and CI/CD) 🔗 Try it yourself: https://lnkd.in/dVtjREi4 💻 Source code: https://lnkd.in/dqU9xaEg The best part? This project forced me to think like a backend engineer - not just "does it work?" but "what happens when things go wrong?" What's your biggest lesson from a recent project? Drop it in the comments! 👇 #BackendDevelopment #NodeJS #API #JavaScript #WebDevelopment #SoftwareEngineering #Azure #TechLearning #CodingJourney #LearningInPublic
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𝐌𝐨𝐬𝐭 𝐀𝐏𝐈 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐚𝐫𝐞𝐧’𝐭 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐂# 𝐜𝐨𝐝𝐞... 𝐁𝐮𝐭 𝐭𝐡𝐞𝐲’𝐫𝐞 𝐡𝐢𝐝𝐢𝐧𝐠 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐪𝐮𝐞𝐫𝐢𝐞𝐬. After refactoring to explicit loading, batching reads with Include(), and caching static lookups in memory, the average request time dropped to 0.21 seconds. No hardware upgrade. Just clean code + awareness. The client’s reaction: “𝐈𝐭 𝐟𝐞𝐞𝐥𝐬 𝐥𝐢𝐤𝐞 𝐚 𝐧𝐞𝐰 𝐬𝐲𝐬𝐭𝐞𝐦.” That’s when I realized performance isn’t a tool; it’s a discipline. A few weeks ago, I worked on a .NET Core project where API response times averaged 1.2 seconds per call. The team wanted to scale the server but scaling slow code just gives you expensive slow code. I opened Application Insights and found the real culprit: 🔹 EF Core’s lazy loading 🔹 Repeated joins on large tables 🔹 Missing .AsNoTracking() for read-only data If you’re working with .NET APIs: ✅ Always profile before optimizing ✅ Use .AsNoTracking() where writes aren’t needed ✅ Cache where data doesn’t change frequently ✅ Remember: Fast code is elegant code I love fine-tuning .NET systems to perform like Ferraris, not forklifts. If you’re building or maintaining enterprise-grade apps and struggling with performance then let’s connect. #DotNet #CSharp #BackendDevelopment #PerformanceTuning #EntityFramework #SoftwareEngineering #API #DOTNETAPI #Optimization #SoftwareDeveloperExpert #SAASSoftwareDeveloper #DotNetCore #AngularDeveloper #AzureDeveloper #AutomationEngineer #AIChatbotDeveloper #MuhammadAtharSaleem #SpargusSolutions
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🚀 Project: Expense Tracker Application 💰 🔗 GitHub Repository: https://lnkd.in/d9aAzR74 I’m excited to share my latest project — a full-stack Expense Tracker Application that helps users manage and visualize their personal finances efficiently. 🧩 Tech Stack Highlights Back-end: ⚙️ Spring Boot – core framework for building a production-ready backend 💾 Spring Data JPA – for efficient CRUD operations 🔐 Spring Security + JWT – secure authentication using stateless JWTs stored in HttpOnly cookies 🗄️ Liquibase – database schema versioning and migration management Front-end: ⚛️ React – component-based UI for a smooth user experience 🎨 Material UI (MUI) – professional, responsive design 📊 Chart.js – interactive visualizations for expense insights Infrastructure & Deployment: 🐳 Dockerized both backend and frontend, with images pushed to Docker Hub ☁️ Deployed on AWS EKS (Elastic Kubernetes Service) for container orchestration 🧠 AWS RDS (PostgreSQL) as the managed database 🌟 Key Features Secure user authentication and authorization Full CRUD operations for managing expenses Advanced filtering & sorting using RSQL Interactive dashboard with line, pie, and bar charts summarizing expenses 🎥 I’ve also created a walk-through video explaining the project and included screenshots showcasing the UI. This project gave me end-to-end exposure — from back-end API design and secure authentication to front-end development and cloud deployment on AWS. 💬 I’d love to hear your thoughts or feedback! #SpringBoot #React #AWS #Kubernetes #Docker #FullStackDevelopment #DevOps #Java #PostgreSQL #SoftwareEngineering #CloudComputing #ProjectShowcase