Learning Backend Development Lessons from a REST API Build

🚀 𝐏𝐑𝐎𝐉𝐄𝐂𝐓 #𝟒: 𝐂𝐥𝐨𝐜𝐤𝐢𝐧𝐠 - 𝐓𝐢𝐦𝐞 𝐒𝐞𝐬𝐬𝐢𝐨𝐧 𝐋𝐨𝐠𝐠𝐢𝐧𝐠 (𝐏𝐄𝐑𝐍) For this project, I built Clocking. The inspiration came from a concept we’re all familiar with: The 10,000-Hour Rule. To truly master skills like coding, writing, or trading, we need to put in the hours. In the past, I used standard stopwatches to track my progress, but it was a mess—I had to take screenshots and manually organize them into folders just to know how much time I’d actually spent. I built Clocking to solve this: a dedicated tool to track deep work sessions and visualize progress without the manual clutter. On the backend, I built a robust API using Node.js and Express to persist session data into a PostgreSQL database, allowing users to keep a permanent, organized record of their journey toward mastery. 𝐓𝐡𝐞 𝐕𝐢𝐬𝐢𝐨𝐧 𝐟𝐨𝐫 𝐅𝐮𝐭𝐮𝐫𝐞 𝐈𝐭𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬: I see a lot of potential to take this further—specifically by integrating Computer Vision to verify that a session is actually being worked on. Imagine a dedicated verification system where users can "prove" their deep work through visual check-ins. It would function like Strava, but for skill-building; a platform where people can share their journey with genuine, verified proof of the work they’ve put in. 🛠️ Tech Stack (PERN): PostgreSQL, Express.js, React.js, Node.js, CSS (Modules), and Git for version control. ⚠️ Important Note: This app is currently hosted on Render’s free tier. If it hasn’t been accessed in a while, the server may take 1 to 5 minutes to "wake up" and load the data on your first visit. 🌐 Check out the Live Demo: https://lnkd.in/g5Sae2Cp 📄 GitHub Docs: https://lnkd.in/gykYsXv6 💻 GitHub Profile: https://github.com/Rahelxv #100FullStackProjectsChallenge #WebDevelopment #BuildInPublic #PERNStack #ReactJS #PostgreSQL #FullStackDeveloper #10000HoursRule #Productivity

Leveling up my Backend Engineering: Beyond Basic CRUD I’ve just wrapped up the first major project of my backend journey: a Personal Expense Tracker API built with Node.js, Express, and MongoDB. While many start with simple "Create/Read" operations, I wanted to push myself to build something "production-ready." Here’s what I implemented to bridge the gap from student to junior developer: ✅ Advanced Filtering: Built a dynamic query engine to filter expenses by category and specific date ranges. ✅ Pagination & Scaling: Implemented a skip and limit logic to ensure the API stays fast, even with thousands of records. ✅ The "Midnight Bug": Solved a real-world edge case where end-date filtering was missing records due to time-stamp boundaries. Normalizing user intent is key! ✅ Automated Testing: Used Bruno to build a full testing suite, including "Happy Path" and "Error Handling" collections to ensure 100% reliability. Backend development is more than just connecting a database; it’s about performance, handling messy user input, and rigorous testing. Next stop: Adding JWT Authentication and Role-Based Access Control! 🛠️ #NodeJS #ExpressJS #MongoDB #BackendDevelopment #WebDev #Bruno #CodingJourney #JuniorDeveloper

🚀 Day 53–71: The Phase Where Everything Started Making Sense Until now, I was writing code… But in these days, I finally understood how real applications actually work behind the scenes. 👨🏫 Thanks to Siva Kumar Sir at DevGnan for guiding us step by step. 💭 What changed in these days? I moved from just frontend thinking → to understanding the complete flow of an application From clicking a button… to knowing where that data goes, how it travels, and where it gets stored. 🧠 Concepts I Explored ⚡ How backend works using Node.js ⚡ Building servers with Express.js ⚡ Sending responses from backend ⚡ Connecting frontend to backend (real communication) ⚡ Introduction to MongoDB ⚡ Using Mongoose to structure and store data 🔥 What I Built Instead of just learning theory, I implemented a real signup system ✔️ User enters details in frontend ✔️ Data travels through API ✔️ Backend handles it properly ✔️ Database stores it successfully 👉 For the first time, I felt like I built something real, not just practice code. 🔄 The Flow I Now Understand Clearly Frontend → Request → Server → Database → Stored Data Simple line… but powerful understanding 💡 📌 Big Realization Backend is not just code. It’s the brain of the application. And once you understand the flow, everything starts connecting. This phase gave me a lot of confidence. Now I’m not just learning… I’m building with understanding 🚀 #MERNStack #BackendDevelopment #NodeJS #ExpressJS #MongoDB #CodingJourney #FullStackDeveloper

Production Bugs Will Humble You Every Time It sometimes feels like there is an unseen hand making sure bugs never stop showing up especially in production. You spend hours building and testing. Everything works fine locally. Then you deploy and suddenly, new issues appear. Earlier this year, I decided to upgrade my portfolio website from a static site to a dynamic one, especially for the blog section. I wanted to be able to publish articles, allow users to sign up, and leave comments. So I rebuilt the site using Next.js, Prisma, and PostgreSQL. Everything worked perfectly on my local machine. But after deploying on Vercel, I kept running into database connection timeouts. To be honest, I avoided debugging it for a while. Today, I finally decided to face it and I fixed it. It feels really good. Now I can publish blog posts, and users can sign up and interact with my content here https://lnkd.in/eRdz_8pb This post is not really about the blog itself. It’s about the reality that bugs will always come especially in production. That’s part of the journey. Keep going. https://lnkd.in/erZQR5uU #SoftwareEngineering #WebDevelopment #NextJS #Prisma #PostgreSQL #Vercel #Debugging #ProductionBugs #BuildInPublic #DevLife #BackendDevelopment #FullStackDeveloper #Programming #TechJourney

Day 7 of my Backend Development Journey 🚀 Today I learned about Schemas and Models in Mongoose… but honestly, this one tested my patience. Getting everything to work wasn’t as smooth as I expected. At some point, I had errors I didn’t understand, my data wasn’t saving, and I kept questioning if I set things up correctly. But after going through it step by step, things finally started to click. Here’s how I understand it now: Schema → defines how your data should look Model → allows you to interact with that data in the database Simple example: const mongoose = require('mongoose'); const userSchema = new mongoose.Schema({ name: String, email: String, age: Number }); const User = mongoose.model('User', userSchema); Looking at this now, it feels simple… But getting here took trial, errors, and a lot of debugging. One thing I’m learning about backend development is this: It’s not always smooth, but the moment things work, everything starts to make sense. Still learning, still pushing.

Most backend developers underestimate one thing: Your settings file is part of your system design, not just configuration. In a production Django backend I’ve been working on, I started treating settings like infrastructure decisions, not just environment variables. Instead of random values scattered around the codebase, everything is intentional: Cloud storage handled through Cloudinary (no local file chaos) Strict media rules to control uploads (size + format enforcement) Cache layers to reduce database pressure and speed up profile reads Presence system tuned for real-time “online/offline” behavior Debounced writes to avoid unnecessary DB hits Structured fallback logic for usernames What changed for me is this mindset shift: Settings are not static values They are performance + scalability decisions For example: caching profile data instead of hitting DB every request controlling how often “last seen” updates defining how long a user stays “online” in real-time systems These small decisions quietly determine how well your system scales under load. At scale, it’s never just about APIs. It’s about how controlled your system behaves under pressure. And it all starts here — in the settings layer.

𝐓𝐡𝐞 𝐔𝐥𝐭𝐢𝐦𝐚𝐭𝐞 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐭𝐨 𝐁𝐞𝐜𝐨𝐦𝐢𝐧𝐠 𝐚 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 Most backend developers learn randomly and wonder why they can't get hired. This roadmap shows you the exact path from core basics to production deployment. 𝟏. 𝐂𝐨𝐫𝐞 𝐁𝐚𝐬𝐢𝐜𝐬 • What is backend? • Backend vs Frontend • Client-Server • DNS & Hosting Start here.  Understand what backend actually does before writing code. 𝟐. 𝐁𝐚𝐜𝐤𝐞𝐧𝐝 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 • Java • Python • JavaScript • C# • Go • Rust Pick one. Master it. Don't jump between languages. 𝟑. 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬 & 𝐃𝐚𝐭𝐚 𝐇𝐚𝐧𝐝𝐥𝐢𝐧𝐠 Database Types: • SQL (PostgreSQL, MySQL, SQLite) • NoSQL (MongoDB, Cassandra, CouchDB) • NewSQL (CockroachDB, VoltDB) Querying Databases: • Sequelize ORM Tools: • Hibernate • SQLAlchemy Caching Systems: • Redis • Memcached You can't build backend systems without databases.  SQL for structured data. NoSQL for flexibility.  Caching for speed. 𝟒. 𝐀𝐏𝐈𝐬 & 𝐖𝐞𝐛 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 API Styles: • REST • SOAP • gRPC • GraphQL Security & Authentication: • JWT • OAuth 2.0 • API Keys APIs connect your backend to the world.  REST is the standard. GraphQL is the future.  Authentication keeps it secure. 𝟓. 𝐒𝐞𝐫𝐯𝐞𝐫𝐬 & 𝐇𝐨𝐬𝐭𝐢𝐧𝐠 Cloud Platforms: • AWS • Azure • GCP Containerization: • Docker • Kubernetes Web Servers: • Nginx • Apache Your code runs somewhere. Cloud platforms scale it.  Containers package it. Web servers serve it. 𝟔. 𝐃𝐞𝐯𝐎𝐩𝐬 & 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 CI/CD: • GitHub Actions • Jenkins • GitLab CI/CD IaC: • Terraform • Ansible Monitoring: • Prometheus • Grafana • ELK Stack Deployment isn't the end.  It's the beginning.  CI/CD automates releases.  IaC manages infrastructure.  Monitoring catches failures. ♻️ Repost this to help your network get started ➕ Follow Sathish for more #BackendDevelopment #Programming #CloudComputing

Hot take: I've seen engineers spend 2 hours configuring a Docker Compose file just to test a 10-line function. You don't need a full Postgres instance to test a user service. You don't need a Redis container to test a cache layer. You need fast, isolated, reliable tests. That's why I open-sourced @backend-master/test-utils. package- https://lnkd.in/guWmyCRe github- https://lnkd.in/gtx9GYPR Here's what it solves: ❌ Before: Spinning up databases just to test a findOne query ✅ After: MockDatabase with full CRUD in 3 lines of code ❌ Before: Manually building mock HTTP response objects ✅ After: HttpTestBuilder.ok({ userId: 1 }) — done ❌ Before: Hardcoded test data that breaks randomly ✅ After: Fixtures.user(), Fixtures.products(10) — realistic every time ❌ Before: let wasCalled = false; someService.fn = () => { wasCalled = true; } ✅ After: Spy.create() — call count, args, errors, all built-in Built with TypeScript. Zero runtime dependencies. MIT licensed. I'd love feedback from backend engineers — what testing pain point should I tackle next? What should I build next? Drop a comment 👇 → PostgreSQL adapter → GraphQL test utilities → Stream mocking → Event emitter mocks #TypeScript #BackendEngineering #SoftwareTesting #NodeJS #OpenSource #NPM #JavaScript

One line that matters in production: Your App should never “guess” whether the database schema matches the code you just deployed. I’ve been tightening our deployment story so releases are boring in the best way: - Wait until PostgreSQL is actually reachable (with bounded retries) - Apply TypeORM migrations as part of startup, so schema and code move together - Then boot the NestJS service This is the kind of work recruiters and engineering leaders notice because it’s not flashy — it’s reliability engineering: fewer surprise 500s after deploys, fewer “works on my machine” schema mismatches, and a cleaner path as the product grows. Stack in focus: NestJS · TypeORM · PostgreSQL · Docker · production-minded releases If you care about backend quality beyond features — consistency, deploy safety, and maintainability — let’s connect. #NestJS #TypeORM #PostgreSQL #Docker #DevOps #BackendEngineering #SoftwareEngineering #Reliability #DatabaseMigrations

Leaving Node.js behind: Building a raw HTTP server in Go. After spending the week locking down my PostgreSQL database, it is finally time to build the API server. But moving from Node.js to Go requires a complete mental reset. In Node, you reach for Express.js immediately. You write app.get("/", (req, res) => {}) and you're good to go. In Go? There is no Express by default. You build it raw using the standard library (net/http). This simple block of code completely flips the script on how you handle data. package main import (   "log"   "net/http" ) // The mental shift happens HERE: (w, r) func handler(w http.ResponseWriter, r *http.Request) {   w.Write([]byte("hello world")) } func main() {   http.HandleFunc("/", handler)   if err := http.ListenAndServe(":8080", nil); err != nil {     log.Fatal(err)   } } In Node, it’s always (req, res) - Request first, Response second. In Go, the handler looks like this: (w http.ResponseWriter, r *http.Request). Response first, Request second. Why? Because Go treats the ResponseWriter (w) as a literal tool you are handed to execute your job. The server effectively says: "Here is your pen (w). Now look at the paperwork (r) and write your response back immediately." I'm officially writing my first route to start the Auth sequence. It’s raw, it’s fast, and there’s no framework magic hiding the fundamentals from me. We move! 💪🏾 To the devs who made the switch from JavaScript/Node.js to Go: What was the hardest habit you had to break? Let’s gist in the comments 👇🏾 #Golang #NodeJS #BackendEngineering #API #SoftwareDevelopment #TechBro #TechInNigeria #WeMove