Mansimran Kaur Bedi’s Post

🚀 Just built and deployed my own AWS EC2-like cloud platform — NimbusCloud! Over the past few weeks, I worked on understanding how cloud services actually work under the hood — and ended up building a mini version of EC2 from scratch. 💡 What it does: Launch compute instances (powered by Docker containers) Start, Stop, and Delete instances (full lifecycle management) Connect to instances via a browser-based Linux terminal Execute real Linux commands using xterm.js + WebSockets Fully deployed on AWS EC2 and accessible publicly 🌐 Live Demo: 👉 http://3.17.204.2:5000 (Anyone can try launching and connecting to instances) ⚙️ Tech Stack: Flask (Backend / API layer) Docker (Compute layer – simulating EC2 instances) xterm.js + WebSockets (Real-time terminal) HTML, CSS, JS (Frontend) AWS EC2 (Deployment) 🔥 What I learned: How EC2-like services manage compute resources How to connect frontend ↔ backend ↔ infrastructure Real-time communication using WebSockets Debugging real-world issues (routing, Docker behavior, deployment) Importance of proper backend serving instead of static file handling 📌 Key Highlight: Building a web-based terminal where users can run commands directly inside their instances — similar to AWS EC2 Instance Connect — was the most exciting part. 🚧 Next Improvements: Add authentication & security layers Instance monitoring dashboard Persistent shell sessions This project helped me move beyond tutorials and think like a DevOps + Backend engineer. Would love your feedback 🙌 #DevOps #CloudComputing #AWS #Docker #Flask #WebSockets #FullStack #Projects #LearningInPublic

I thought deploying a Node.js + Next.js + ClickHouse stack on AWS would take a few hours. It took two days 💀 What looked like a simple “Docker + Nginx on EC2” setup turned into a reminder that deployment is never just: "docker-compose up" I was running: ⚡ Node.js backend ⚡ Next.js frontend ⚡ ClickHouse ⚡ Docker ⚡ Nginx reverse proxy ⚡ AWS EC2 And almost every layer had its own way of failing. A few lessons the process taught me: 👾 Existing services on the same EC2 instance matter,Old apps can still occupy ports and silently break new containers. 👾 If your app is served from a subpath like /dashboard, you need to configure basePath correctly.Otherwise CSS, routes, and static assets fail in confusing ways. 👾 One small mistake in an Nginx reverse proxy rule can create an endless redirect loop. 👾 Backend containers often fail for tiny reasons:Wrong startup command, Incorrect database credentials, Database doesn’t exist yet The biggest lesson: Don’t debug deployment issues by guessing. My process became:  1. Check whether the container is running  2. Read the logs  3. Test the service locally on localhost  4. Validate the Nginx config  5. Only then test from the browser. That one change saved me hours. Deployment problems are frustrating, but they teach you more about infrastructure than any tutorial ever will. What’s the most painful deployment bug you’ve ever had to track down? #Docker #AWS #Nextjs #Nodejs #DevOps #AWS #ClickHouse #404

🚀 Successfully deployed my first Node.js backend to AWS EC2! After years of running apps on localhost, I finally took the leap into cloud deployment. Here's what the journey taught me: 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝘁: Full-stack fitness tracking platform with AI-powered workout coaching Backend API: Node.js + Express Database: MongoDB Atlas AI: Google Gemini with RAG for personalized recommendations 𝗧𝗵𝗲 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀: ✅ Launched EC2 instance (Ubuntu t3.micro - free tier!) ✅ Configured Security Groups for network access ✅ Set up SSH key-based authentication ✅ Installed Node.js and dependencies ✅ Implemented PM2 for process management ✅ Configured auto-restart on server reboot 𝗞𝗲𝘆 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴𝘀: • SSH keys > passwords • Use environment variables for secrets (never commit .env) 💡 Process Management is Critical Without PM2, the app stops when SSH disconnects With PM2, it keeps running in the background 💡 Cloud Basics Matter Understanding ports, networking, and instance lifecycle is key 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗙𝗮𝗰𝗲𝗱: ❌ First attempt: Forgot to open port 5000 in Security Groups Lesson: Network access needs proper configuration ❌ PM2 stopped working after reboot Lesson: Always run pm2 startup and pm2 save 𝗡𝗲𝘅𝘁 𝗨𝗽: 📦 Deploying Angular frontend 🔄 Setting up CI/CD pipeline 🔒 Adding HTTPS for secure connections 𝗙𝗼𝗿 𝗙𝗲𝗹𝗹𝗼𝘄 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀: If you’ve been thinking about trying cloud deployment, just start. Launch an instance, experiment, break things, and learn along the way. Also curious — for those who’ve worked with different platforms, which do you prefer for beginners: AWS, Azure, or something else? #CloudComputing #WebDevelopment #FullStackDeveloper #DevOps #NodeJS #LearningInPublic #SoftwareEngineering #BuildInPublic

🔴 Not a tutorial-based project built from scratch Over the last 2 days, I worked on automating a full-stack application using AWS (EC2, S3, ECS Fargate, VPC, IAM, Security Groups), Docker, Terraform, GitHub Actions, and Nginx. While building the project, I faced several issues not very complex, but enough to reinforce how real-world debugging actually works. 🧩 Day 1: Networking Reality Check 🔴 Problem: - Application was not accessible via browser (timeout) - But curl localhost worked inside EC2 ❌ Misconception: “If the app runs on the server, it should be accessible publicly.” ✅ Solution: - Fixed VPC, Subnet, Internet Gateway, and Route Table - Opened port 80 in Security Group - Ensured EC2 was in a public subnet ✔ Result: Application became publicly accessible 🧩 Day 2: Deployment & Execution Issues 🔴 Problem: - Docker container running but not accessible from browser - Inconsistent behavior with port access ❌ Misconception: - Terraform apply = everything works automatically - docker run = app is publicly accessible 👉 Actual issues: - EC2 was not fully initialized - Incorrect port exposure / Nginx confusion - Mixing old and new infrastructure resources ✅ Solution: - Waited for EC2 health checks (2/2) - Correct Docker port mapping (-p 80:80) - Clean reset using Terraform - Explicit HTTP usage ✔ Result: Frontend successfully served via public IP 🎯 Key Takeaways: - Running app ≠ Public accessibility - AWS networking (VPC, routing, SG) is critical - Terraform provisions infrastructure, not application runtime - Proper container port exposure is essential - Timing and deployment sequence matter Building from scratch (instead of following tutorials blindly) really shows where things break and more importantly, how to fix them. #DevOps #AWS #Terraform #Docker #ECS #CloudComputing #FullStack #Debugging #LearningInPublic #SoftwareEngineering #fixbug #productionlevel

One of those days where I just had the urge to build something personal. Had an idea for an app, started building it, and once it was done I thought — why not use this as a real AWS deployment project? So that’s what I did. 🔧 Infrastructure: • VPC with public & private subnets + custom route tables • Internet Gateway for public access, NAT routing for private resources ⚙️ Stack: • Frontend → AWS Amplify (with built-in CI/CD) • Backend → Node.js on EC2 (public subnet, PM2 for process management) • Database → RDS on private subnet (zero direct internet exposure) • Auth → Amazon Cognito • File storage → S3 (public assets) Keeping the DB isolated in a private subnet while giving it controlled internet access via route table config was a key focus — security without sacrificing functionality. PM2 keeps the backend resilient, and Cognito removes the overhead of building auth from scratch. 📌 What's next: • Move backend behind an Application Load Balancer + private subnet • Add CloudFront CDN in front of S3 and Amplify • Introduce auto-scaling for the EC2 layer • Set up CloudWatch monitoring & alerts • Migrate toward containerization with ECS or explore serverless with Lambda • Terraform to automate and codify the entire infrastructure Every project teaches you something new about trade-offs. This one was about balancing simplicity with production-readiness. You can check it out here https://lnkd.in/epsw3xH7 PS: deleting link soon once i destroy resources because of cost #AWS #CloudArchitecture #FullStack #DevOps #NodeJS #RDS #Amplify #Cognito

I've been learning AWS lately and honestly, the best way I found to understand it was to just build something with it. So I built a File Upload System using AWS S3 and Next.js But first — what even is AWS S3? S3 (Simple Storage Service) is basically a giant hard drive on the internet provided by AWS(Amazon Web Services). Instead of saving files on your server (which can crash), you store them in S3 , which has: → Unlimited storage → Accessible from anywhere in the world → 99.99999999% reliable → Used by Netflix, Instagram, WhatsApp and almost every major app Think of it like this: 📦 Bucket = your folder in the cloud 📄 Object = any file inside that folder 🔗 Presigned URL = a temporary link to access a private file ⚙️ What I built A full-stack file upload system where: ✅ Upload any file directly to AWS S3 ✅ Access files via presigned URLs (auto-expires in 10 mins) ✅ Delete files with confirmation ✅ Clean minimal UI with Tailwind CSS What I learned building this ? → How S3 buckets and objects actually work → What presigned URLs are and why they matter for security → How IAM users and access keys control permissions → Connecting AWS SDK with Next.js API routes → Handling binary file data with Buffer and FormData The source code is fully commented — every single line explains what it does and why. Perfect if you're also learning AWS and want a real working project to reference. If you're a beginner trying to understand AWS S3, feel free to clone it, break it, and learn from it. That's exactly what it's for. 🙌 GitHub link - https://lnkd.in/dZh-frQW #AWS #S3 #CloudComputing #NextJS #WebDevelopment #SelfLearning #FullStack #JavaScript 

AWS Project: Highly Available Web Application Recently completed an AWS project on building a Highly Available Web Application Over the past few days, I worked on designing and deploying a production-style architecture on AWS, focusing on scalability, security, and real-world implementation. What I implemented: • Custom VPC with public and private subnets • EC2 instances deployed in private subnets • Bastion host for secure SSH access • Application Load Balancer with path-based routing • Separate target groups for text and image services • Auto Scaling Group based on CPU utilization • Multi-AZ setup for high availability Traffic Flow: User → ALB → Target Groups → EC2 Instances I also faced and resolved a few practical issues like health check failures, 403 errors, and routing misconfigurations — which really helped me understand how things work in real scenarios. GitHub Repository: https://lnkd.in/dvk5q3FH Included architecture diagram and working screenshots in the repo. (Created in draw.io) This project gave me a solid understanding of how scalable and secure architectures are built on AWS. Would appreciate any feedback or suggestions! #AWS #CloudComputing #DevOps #Linux #AutoScaling #LoadBalancing #Project

Microsoft Shows. AWS Actually Does: I deployed the exact same .NET 8 app on both free tiers. Same code. Same Dockerfile. Completely different results. AWS EC2 (t2.micro): x86 architecture (Intel) Standard Docker build: 2-3 minutes Deploys smoothly. Just works. ✅ Azure Free Tier (B2pts v2): ARM64 architecture (Ampere) Standard Docker build: 10+ minutes → TIMEOUT My x64 container ran under emulation. 5-10x slower. ❌ Here's the kicker: This is Microsoft's own tech stack. .NET 8. ASP.NET Core. Their own cloud free tier can't run their own framework's default deployment without choking. Meanwhile, AWS EC2—boring, predictable, x86—handles it without breaking a sweat. Why does this matter? Because beginners will hit this and blame themselves. They'll think their code is broken. They'll waste hours debugging architecture mismatches they didn't even know existed. I've been doing cloud deployments for months across both platforms, and even I was frustrated. A newcomer? Demoralized. My Experience I've deployed production workloads on both AWS and Azure. AWS free tier is what a free tier should be: honest about what you get, compatible with standard tooling, and actually usable for learning. Azure's free tier is cost-cutting dressed up as "better specs." ARM VMs have their place, but shoving them as the default free option—especially for .NET developers—is a trap. If you're starting your cloud journey or building side projects: AWS EC2 free tier is the clear winner. Don't let Azure's spec sheet fool you. #AWS #Azure #DotNet #DevOps #CloudComputing #Developer #FreeTier

Mistakes in Terraform don't break production. They teach you exactly why things work. My latest project took the IaC foundations I've been building and put them to the test across two assignments. 𝗔𝘀𝘀𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝟭 - WordPress on EC2 The user data script wasn't executing on boot. After some digging the cause was simple. I was targeting an Amazon Linux AMI with a bash script it didn't support. Swapped to Ubuntu, ran terraform destroy to reset cleanly, redeployed and it worked. The real win wasn't fixing it. It was understanding why. 𝗔𝘀𝘀𝗶𝗴𝗻𝗺𝗲𝗻𝘁 𝟮 - EC2 + Cloud-Init + Route53 Modules I set myself a harder target this time. Not just a running web server, but one accessible via a custom domain with zero manual steps. The tricky part was wiring two Terraform modules together. The Route53 module needed the EC2 public IP, which meant getting my head around how outputs flow between modules. Once that clicked, terraform apply ran clean first time. Web server up. Domain resolving. No console touched. What these two assignments reinforced - Clean state matters. Run terraform destroy between broken attempts rather than patching over problems - Modules aren't added complexity, they make infrastructure readable and reusable - The friction from early on pays off when the problems get harder Every blocker is just a gap in understanding waiting to be closed. If you are at all interested you can see my assignment repo here: https://lnkd.in/eQ999s-Q CoderCo