Building Modular Backend Architecture with Node.js and PostgreSQL

Building a real-time DevOps terminal on a 1GB RAM cloud server forces you to get incredibly creative with infrastructure. Today, I am opening up DriftSeek for core open-source contributions. DriftSeek is an AIOps infrastructure lifecycle manager. It monitors server drift via a Redis-backed cron engine, triggers Telegram alerts with smart cooldowns, and instantly spins up a web-based "War Room" terminal for the team to debug the server together. The Current Architecture: - Frontend: Next.js with node-pty and Socket.io for managing multiple concurrent terminal tabs. - Backend: Express server dynamically spawning alpine:latest Docker containers. - Resource Control: Containers are strictly hardware-capped at 256MB RAM and 0.5 vCPUs to prevent OOM crashes on the host machine. - Speed Layer: Redis Pub/Sub handles the live system metric broadcasting. What we are building next (Looking for Collaborators): We have the foundation, but we are currently tackling a major distributed systems challenge to make the platform production-ready: - Ephemeral Git Workspaces: Intercepting WebSocket disconnects to auto-commit the container's state back to GitHub before instantly destroying the Alpine container (NextAuth repo scopes are already configured). If you are a builder wrestling with Docker resource constraints, Next.js WebSocket state management, or cloud architecture, drop a comment or send me a DM. I will share the repo and the architectural blueprint. Let's build something that actually scales under pressure. #DevOps #Docker #NextJS #OpenSource #SoftwareEngineering #CloudArchitecture

⭐ 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐞𝐝 𝐚𝐧 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐰𝐨𝐫𝐭𝐡 𝐬𝐡𝐚𝐫𝐢𝐧𝐠: 𝐊𝐮𝐛𝐞𝐏𝐨𝐥𝐚𝐫𝐢𝐬 If you've ever managed multiple Kubernetes clusters, you know the pain: - Jumping between servers just to switch clusters - Writing endless long kubectl commands to check a pod log - Opening Grafana, then AlertManager, then back to the terminal all for a single issue - Configuring RBAC just to give a developer read-only access KubePolaris addresses all of this with a clean, modern web UI built in React + Go. 𝐖𝐡𝐚𝐭 𝐦𝐚𝐤𝐞𝐬 𝐢𝐭 𝐢𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐢𝐧𝐠: 🏢 Multi-cluster management from a single interface no more context switching chaos 🔌 Native integration with Prometheus, Grafana, AlertManager, and ArgoCD 🔒 Enterprise-grade RBAC, audit logs, and permission control out of the box 🖥️ Built-in web terminal powered by xterm.js — no local kubectl required 🚀 One-command Docker deployment to get started in minutes 💯 Fully open source under Apache 2.0 The name says it all "𝐏𝐨𝐥𝐚𝐫𝐢𝐬" is the North Star, meant to guide your K8s operations reliably. It's still a young project, but the architecture is solid (single Go binary with embedded React frontend), the documentation is clean, and it already solves real DevOps pain points. If you work with Kubernetes at scale, it's definitely worth a look 👇 https://lnkd.in/es_7E_B9 #Kubernetes #CloudNative #DevOps #OpenSource #K8s #Platform Engineering

Being a full-stack dev taught me this: Your backend choices become your frontend problems. Your database design becomes your 3AM problems. Your DevOps skills become your “it works now” problems. Learn the glue between layers. That’s where 90% of bugs live. What’s your hardest “glue” lesson? 👇 #FullStackDeveloper #WebDev #DevTips

When people talk about Ruby, one of the first associations they make is with Rails and web applications. Vagrant, however, is a different case: a tool for creating and managing virtualized development environments, written entirely in Ruby. It was created by Mitchell Hashimoto while he was working at a Ruby on Rails consultancy. Every time he switched to a different client's project, he had to reconfigure the development environment, wasting a lot of time in the process. In 2010, he wrote Vagrant: a tool in Ruby to create virtualized development environments that are replicable via a single configuration file (specifically the Vagrantfile, written in Ruby). From that personal project, born out of necessity, HashiCorp was founded, which later developed the Terraform, Vault, Consul, Nomad, and Packer projects. This demonstrates how needs can turn into opportunities, the fundamental driving force behind Ruby code. — #Rubycon2026 #Ruby #DevOps #SoftwareEngineering #Innovation

Most projects stop at “it works on my machine.” This one doesn’t. I built a simple full-stack application — but focused on how it actually runs in a real environment. Here’s what’s inside: • Frontend served via Nginx (containerized) • Backend API built with Node.js (Express) • Separate containers for each service • Docker Compose used to run everything together Instead of mixing everything in one setup, the application is split into services — just like real systems. How it flows: User → Frontend (Nginx) → Backend API → JSON Response No complexity for the sake of it. Just a clean setup that shows how services talk to each other. What this project helped me understand better: • How containers isolate services • How frontend and backend communicate in a containerized setup • Why multi-container architecture matters • How Docker Compose simplifies orchestration This is a small project, but it reflects a mindset shift: From writing code → to thinking about deployment. GitHub: https://lnkd.in/gctxFU4Z #Docker #DevOps #NodeJS #Nginx #FullStack #DockerCompose

🚀 Building a Real-World Scalable System — Need Your Suggestions! I’m starting a new project to challenge myself and grow as a complete engineer. I’m going to build a BookMyShow-like Ticket Booking Platform using a modern, production-grade architecture with: 🔹 Node.js (Express + TypeScript) 🔹 Microservices Architecture 🔹 Multi-database setup (PostgreSQL + MongoDB + Redis) 🔹 Event-driven system (Kafka / RabbitMQ) 🔹 Docker & CI/CD 🔹 Observability (ELK, Prometheus, Grafana) 🔹 Real-time features (WebSockets) The goal is not just to build a project, but to understand how real-world systems work at scale — from frontend to backend, DevOps, monitoring, and system design. 💡 I want to become someone who can: Design and build applications end-to-end Handle production systems Work across Full Stack + DevOps + Observability Solve real-world scalability problems Before I start, I’d love your suggestions: 👉 What features should I add to make this project more production-ready? 👉 Any must-use tools or technologies I should include? 👉 What mistakes should I avoid while building this system? Also, if you’ve worked on similar systems, your advice would mean a lot 🙌 I’ll be sharing my learnings and progress throughout this journey. #FullStack #NodeJS #SystemDesign #Microservices #DevOps #LearningInPublic #BackendDevelopment #SoftwareEngineering

I push to main. Two minutes later, the site updates. But only if 132 tests pass first. Most developers set up CI/CD to automate deploys. I set it up to block them. Here's the full flow: → Push to main → GitHub Actions runs 80 backend tests — every API route, auth middleware, Prisma mock → Then 52 frontend tests — components, fetch wiring, admin tabs → Any failure? Deploy stops. Nothing reaches Azure. → All green? Build runs. Frontend + backend deployed automatically. No manual FTP. No SSH. No "did it deploy?" anxiety. Early on, a stale package-lock.json broke the install step. Fixed it, pushed again, green. That's what CI/CD teaches you — environment issues surface in the pipeline, not in production. https://lnkd.in/gjM8tKr2 Next: the part most devs skip — a custom content editor built directly into the admin panel. #CICD #GitHubActions #DevOps #Azure #Testing #WebDev #Portfolio #TechMalaysia

🚀 Building a 3-Tier Kubernetes App I just deployed a full-stack application on Kubernetes to master containerization, orchestration, and real-world troubleshooting. What I Built: - Frontend (React + Nginx) - Backend (Node.js + Express) - Database (PostgreSQL) Users submit messages → stored in the database → displayed in the UI. Simple but powerful! 💪 The Tech Stack: Docker → Docker Hub → Kubernetes (Minikube) Key Learnings: ✅ Containerized each tier independently ✅ Configured Nginx reverse proxy for service-to-service communication ✅ Deployed with Kubernetes manifests for reproducibility ✅ Debugged real issues: service discovery, build errors, data persistence Want to try it? git clone https://lnkd.in/gxK49hKm cd project kubectl apply -f k8s/ minikube service frontend-service This project shows how DevOps practices bring multiple technologies together into a working system. Each challenge taught me something new about how containers and orchestration work in production. 🎯 Ready to build the next one! 🚀 #DevOps #Kubernetes #Docker #ContainerOrchestration #CloudNative #FullStack #Learning

What is actually running behind ZenSpend. People see the ZenSpend UI and ask about the design. What I want to talk about is what is running underneath it. The frontend is Next.js, served through CloudFront via S3. Behind that, two Node.js microservices, one handling authentication, one handling transaction logic. They run as separate pods on an EKS cluster, deployed across three availability zones. If one zone goes down, the app keeps running. That is not an accident, that is the architecture working the way it was designed to. Each service lives in a private subnet. The database — RDS PostgreSQL 15 — lives in a separate database subnet with no public IP address. The only thing that can reach it is the EKS worker node security group. Not the VPC CIDR, not some broad rule. Specifically the node group. That is the difference between infrastructure that is convenient and infrastructure that is secure. The deployment pipeline runs on GitHub Actions. Every commit triggers a lint check, the test suite, and a Trivy container scan before anything gets pushed to ECR. ArgoCD watches the repo and syncs the cluster automatically when a new image lands. No manual kubectl apply. No SSH into a server at 2am wondering what is different. The GitOps model means the cluster state is always exactly what the repo says it should be. The Dockerfiles are multi-stage builds. The builder stage handles npm installs including all the dev dependencies. The runtime stage copies only what is needed to run, no Nodemon, no dev tooling, and no unnecessary packages. Image sizes dropped by over 80% compared to single-stage builds. Smaller images mean faster pod starts and a smaller attack surface. The observability layer has Prometheus scraping metrics from every pod, Grafana tracking SLOs, and ELK centralizing logs across all three services. When something breaks, and something always breaks eventually, there is a trail. This is what it takes to run a real product seriously. Not because it is a unicorn startup. Because the habits you build on small systems are the ones that carry you to big ones. Full architecture diagram below. #DevSecOps #Kubernetes #EKS #Terraform #Docker #Microservices #AWS #CloudArchitecture #ZenSpend