Serverless CI/CD with AWS Java Angular

I saw a 148x speedup by switching to CloudFront for my CDN. I’ve been building an authenticated image gallery using Java, Spring Boot, and Angular. The initial performance serving out of an S3 Bucket with presigned URLs was... sluggish. By pivoting to Amazon CloudFront, I saw a speedup between 8x and 148x for Time to First Byte (TTFB). It’s a great reminder of how much edge caching matters when handling media, a lesson I learned from using managed services like Vercel. A few takeaways from the build so far: Angular vs. Next.js - Coming from a Java background, Angular’s structure and dependency injection feel much more natural than Next.js. Local Dev - Using Docker for PostgreSQL has made the local environment incredibly stable and quick to spinup. Time to move this build to a permanent home. DigitalOcean? Linode? Hetzner? I’d love to hear your recommendations for hosting personal projects. #SoftwareEngineering #AWS #Java #Angular #WebDevelopment 

Day 39 of making my self a BRAND 1 . Successfully Dockerized my Node.js + TypeScript backend using Multi-stage Dockerfile for optimized production image. 2 . Implemented proper build process with tsc + tsc-alias to handle path aliases (@/) in ESM environment. 3 . Configured single-service Docker Compose setup with environment variables support from .env file. 4 . Integrated external services (Aiven Redis, Kafka & MongoDB) seamlessly inside Docker container. 5 . Achieved a clean, lightweight, and production-ready Docker setup that runs perfectly with just one command: docker compose up. #Docker #NodeJS #TypeScript #BackendDevelopment #DevOps #SoftwareEngineering #Dockerization #ProductionReady #MultiStageDocker #TypeScriptDeveloper #NodeJSDeveloper #BackendEngineer #Containerization #DockerCompose #Redis #Kafka #MongoDB #CloudNative #Microservices #BuildInPublic #LearningInPublic #DeveloperJourney #Day39 #100DaysOfCode #CodingJourney #PersonalBranding #TechJourney #SoftwareDeveloper #FullStackDeveloper #DevOpsEngineer #InfrastructureAsCode #CI_CD #ProductionDeployment #CleanCode #OptimizedImage #ESM #PathAliases #TechGrowth #CareerGrowth #DeveloperLife #Programming #WebDevelopment #Engineering #Innovation #TechCommunity #LearnToBuild #SelfImprovement #Consistency #BrandBuilding

One of the biggest challenges in modern applications is startup time and memory usage especially in microservices and serverless environments. That’s where GraalVM stands out. GraalVM allows Java applications to be compiled into native executables, which means they start in milliseconds and use significantly less memory compared to traditional JVM-based applications. This is a game changer for cloud-native systems where performance and cost efficiency matter. In real-world use cases, frameworks like Spring Boot and Quarkus are leveraging GraalVM to build faster and more efficient microservices. Instead of waiting for the JVM to warm up, applications are ready almost instantly, making them ideal for Kubernetes and serverless deployments. What I find interesting is how GraalVM is pushing Java beyond its traditional boundaries bringing it closer to the performance of compiled languages while still keeping its ecosystem strong. My takeaway: GraalVM is not just an optimization tool it’s a shift toward building faster, leaner, and more scalable Java applications. Curious to hear have you tried running your applications with GraalVM native images? #Java #GraalVM #Microservices #Cloud #Kubernetes #Backend #Performance #SoftwareEngineering

🚀 I built a Vercel clone and finally understood what microservices actually mean. Most tutorials talk about microservices. I wanted to feel them. So I built a deployment platform for React/Next.js static sites, one that mimics how Vercel works under the hood. Here's the architecture in a nutshell: The system is split into independent services that each own one job: → Upload Service: takes your GitHub repo and pushes the raw code to S3 → Deploy Service: pulls from S3, runs the build, and stores the output back to S3 → Request Handler: serves the right static files from S3 based on the subdomain The glue between them? Redis as a job queue. The upload service drops a job, the deploy service picks it up. No tight coupling. No shared state. Pure async handoff. Tech stack: TypeScript + Next.js + Redis (for queue) + S3 Bucket (for storing files) What this taught me: - Why teams reach for a queue instead of direct API calls - How S3 can act as both a build artifact store and a static file server - What actually microservices are and there use case Github Repo: https://lnkd.in/em3ByJqY #SystemDesign #Microservices #NextJS #TypeScript #WebDev #BuildInPublic #AWS #Redis

🚀 Elevate Your Backend Engineering Stack Building scalable and robust systems requires a strategic choice of tools. Whether you are an aspiring developer or a seasoned architect, mastering these core technologies is essential in today’s landscape. The Modern Backend Ecosystem includes: - Languages: Python, Go, Rust, Java, JavaScript - Frameworks: FastAPI, Spring Boot, NodeJS, Django - Databases: PostgreSQL, MongoDB, Redis, DynamoDB - Cloud & Infrastructure: AWS, Kubernetes, Docker, Azure - CI/CD & Version Control: GitHub Actions, GitLab, Jenkins Staying ahead means constantly refining your toolkit to build more efficient and reliable applications. Which of these tools are central to your current workflow? Let’s discuss in the comments!

Java actually has a very massive spring ecosystem which contains many frameworks like spring framework for building applications, spring cloud for building microservices, spring AI for interacting with LLMs etc. Spring framework is a part of this massive ecosystem, it is like a toolbox to build Java apps, if we try to build a web application with it, that would require a lot of config setup, thats where spring boot comes into picture, with the help of spring boot we can avoid that heavy config setup and focus on building features and our application. #SPRINGBOOT #BACKEND

🚀 Just shipped the Event-Booking-Microservices-Platform — a production-grade Microservices system! Built with Java & Spring Boot , here’s what’s inside: 🧩 8 microservices — User, Event, Booking, Payment, Notification + Gateway, Eureka, Config Server 🔐 JWT + OAuth2 (Google Login) with RBAC at the gateway level ⚡ Kafka-driven async flows — BookingCreated → Payment → Notification 🔗 OpenFeign + Resilience4j circuit breakers for fault tolerance 🐘 Database per service (PostgreSQL) — true isolation 🐳 Fully containerized with Docker Compose The biggest lesson? Design for failure, not just for success. Next: Redis caching · Kubernetes · CI/CD 🔧 🔗 GitHub: https://lnkd.in/dch3hrcG 🌐 Portfolio: https://lnkd.in/dndjUxwU Open to feedback from anyone in the microservices space 🤝 #SpringBoot #Microservices #Java #Kafka #SystemDesign #BackendDevelopment #Docker #CloudNative

Day 39 of making my self a BRAND 1 . Successfully Dockerized my Node.js + TypeScript backend using Multi-stage Dockerfile for optimized production image. 2 . Implemented proper build process with tsc + tsc-alias to handle path aliases (@/) in ESM environment. 3 . Configured single-service Docker Compose setup with environment variables support from .env file. 4 . Integrated external services (Aiven Redis, Kafka & MongoDB) seamlessly inside Docker container. 5 . Achieved a clean, lightweight, and production-ready Docker setup that runs perfectly with just one command: docker compose up. #Docker #Dockerize #NodeJS #TypeScript #BackendDevelopment #DockerCompose #MultiStageBuild #ESM #JavaScript #WebDevelopment #DevOps #Containerization #SoftwareEngineering #FullStack #Backend #Programming #Code #Developer #Tech #SoftwareDeveloper #Learning #CareerGrowth #LinkedIn #Success #Project #BuildProcess #Aiven #Redis #Kafka #MongoDB #ExpressJS #CleanCode #ProductionReady #Optimization #Cloud #Infrastructure #Automation #Engineering #TechJourney #DeveloperLife #Coding #100DaysOfCode #LearnInPublic #OpenSource #Skills #Growth #Motivation #Consistency

🚀 Building scalable Java applications with Spring Boot is no longer a "nice to have" it's survival. Have you ever stopped to think about how much a poorly designed architecture can cost a team? Slow systems, stuck deploys, an entire team waiting for a single service to come back up… I've seen (and lived) this scene more times than I'd like to admit. That's exactly why I dove headfirst into the world of Spring Boot microservices. And one thing became crystal clear: ✅ Scaling isn't just about "adding more servers." ✅ It's about designing services that talk well, fail gracefully, and grow without pain. In my recent projects, I've been working with: 🔹 Spring Boot + Spring Cloud to orchestrate independent services 🔹 Kafka / RabbitMQ for async communication (because nobody deserves tight coupling) 🔹 Docker + Kubernetes for deploys that don't stop the business 🔹 Resilience4j for failures that don't take the whole system down 🔹 Observability with Prometheus and Grafana — because what you can't measure, you can't improve The result? Applications that handle traffic spikes, teams that ship faster, and users who never notice when something goes wrong behind the scenes. #Java #SpringBoot #Microservices #BackendDeveloper #SoftwareEngineer #JavaDeveloper #SpringCloud #Kubernetes #Docker #CleanCode #SoftwareDevelopment #Backend #DevOps #CloudComputing #RESTAPI #Kafka #SystemDesign #ScalableArchitecture #AWS

Stop building "modern" backends that can't handle 10,000 users. I’ve seen too many projects fail because the team spent 3 months over-engineering a "perfect" microservices architecture before they even had 100 signups. The truth about high-scale systems? The "old" stuff is often the best stuff. Here is my "unpopular" stack for 2026 that actually scales: Laravel: For speed of delivery. The developer experience is still unmatched. Node.js (for the heavy lifting): When I need non-blocking I/O and real-time performance. PostgreSQL over everything: Don't reach for NoSQL until your SQL joins actually break (which is much later than you think). The Load Balancer is your best friend: Stop tweaking code until you've checked your Nginx config. Scaling isn't about using the newest tool on GitHub. It’s about understanding where the bottleneck is before it happens. Agree or disagree? Let’s fight it out in the comments. 👇 #Backend #SystemDesign #SoftwareEngineering #WebDev #Laravel #NodeJS