The invisible work that keeps teams moving: refactoring, cleanup, automation, and optimization.

💡 Ever wondered how platforms like LeetCode run and evaluate your code? I decided to find out — and built my own Distributed Code Execution Platform from scratch ⚙️ 💻 Tech Stack: Go · Spring Boot · React · RabbitMQ · Docker · Redis · PostgreSQL 🚀 Highlights: Built-in code Editor supporting multiple languages (Java, C++, Python) 💻  Secure sandboxed code execution in Docker 🐳 Run code with custom testcases ▶️ submit code with predefined testcases ✅ Asynchronous execution using RabbitMQ queues ⚙️  Real-time feedback via Server-Sent Events 🔄 This project taught me about system design, and safe execution of external code, asynchronous communication and real-time feedback — the foundations of platforms like LeetCode. 🔗 Check out the GitHub repository to explore the architecture, database design and execution workflow: 👉 https://lnkd.in/grTXtH83 🎥 Watch the demo below #SystemDesign #Docker #Golang #SpringBoot #RabbitMQ #React #LeetCodeClone

🚀 New DevOps Starter Released! Following the success of the Java, Python, and Go editions, here comes a new stack for high-performance developers 👇 🎯 Rust + Actix Web + Svelte + PostgreSQL (CI/CD Ready) A fully production-ready starter kit that includes everything you need to build, deploy, and monitor modern Rust web apps: ✅ Rust (Actix Web) backend — REST API + Prometheus metrics ✅ Svelte + Vite + TypeScript frontend ✅ PostgreSQL + Docker Compose ✅ Prometheus + Grafana monitoring ✅ GitHub Actions CI/CD pipelines ✅ Optional Keycloak realm for OIDC auth Build and run locally in one command: cd infra/docker && docker compose up -d --build 💻 Get it here: 👉 https://lnkd.in/edkR9JGf Perfect for developers, DevOps engineers, and SaaS builders who want a Rust-based full-stack template with CI/CD and monitoring built in. #Rust #Actix #Svelte #PostgreSQL #Docker #DevOps #Grafana #Prometheus #GitHubActions #FullStack #WebDev #CI_CD #SaaS

🚀 Improving API Performance with CompletableFuture in Spring Boot In one of my recent financial-domain microservices, I optimized multiple downstream calls using CompletableFuture — running them in parallel instead of sequentially. This reduced the overall API latency Here’s a quick example 👇 CompletableFuture<String> user = CompletableFuture.supplyAsync(() -> userService.getUser()); CompletableFuture<String> account = CompletableFuture.supplyAsync(() -> accountService.getDetails()); CompletableFuture.allOf(user, account).join(); log.info("User: {}", user.get()); log.info("Account: {}", account.get()); 1: Why this worked Parallel execution for I/O-bound downstream calls Clean, non-blocking async pattern Simple integration with Spring’s async executor and WebClient Great way to boost response time in distributed systems Asynchronous programming is a powerful way to make microservices faster and more scalable — especially when you’re dealing with multiple service calls or APIs. Curious to know — how have you used CompletableFuture or reactive programming to improve performance in your projects? 👇 #Java #SpringBoot #CompletableFuture #Microservices #AsyncProgramming #Performance #AWS #BackendDevelopment #ProgrammingTips

🚀 New Guide: The Ultimate Guide to Setting Up Zabbix Observability in Kubernetes From Helm install to production-ready architecture—Proxy, Agent2 (DaemonSet + sidecar), Prometheus scraping, and live examples in Rust, Go, and Java/Spring Boot. 🔧 What you’ll get: • ✅ Full-stack Zabbix on K8s (with TimescaleDB) • 🔍 Kubernetes API auto-discovery (nodes, pods, events) • 📈 App metrics via Prometheus endpoints • 🧩 Patterns: DaemonSet vs Sidecar (when to choose which) • 🛡️ HA proxy, network policies, and DB tuning tips • 🧪 Ready-to-use code + Zabbix items for Rust/Go/Java If you’re scaling microservices and want enterprise-grade observability without licensing costs, this is for you. https://lnkd.in/g6W_4wbq #Kubernetes #Zabbix #Observability #DevOps #SRE #CloudNative #K8s #Helm #Prometheus #Grafana #TimescaleDB #Microservices #Rust #Golang #Java #SpringBoot #Monitoring #Alerting #PlatformEngineering #SiteReliabilityEngineering

Every commit should move closer to production, not pile up in branches. That’s the power of a CI/CD pipeline: • Code → Built • Tested → Verified • Deployed → Instantly Faster feedback. Fewer bugs. Happier developers. #DevOps #CICD #Automation #SoftwareEngineering #Developers #GitHubActions #Jenkins #Cloud #Python #Java #happynewmonth

🚀 New DevOps Starter Released! After Java + Angular, Next + Nest, and Go + Vue, I’m excited to share the next one in the series: 🎯 Rust + Axum + Svelte + PostgreSQL (CI/CD Ready) A production-grade starter kit that includes: ⚙️ Rust (Axum) backend — REST API + Prometheus metrics 🎨 Svelte + Vite + TypeScript frontend 🗄️ PostgreSQL database 🐳 Docker Compose setup 📊 Prometheus + Grafana monitoring 🔁 GitHub Actions CI/CD ready 🪪 Keycloak realm export (optional) Ready to run with just one command 👇 cd infra/docker && docker compose up -d --build 💻 Get it here: 👉 https://lnkd.in/ed_VcYbD Perfect for developers who want a Rust-based full-stack starter with modern DevOps tools built in. #Rust #Svelte #DevOps #FullStack #CI_CD #Docker #Grafana #PostgreSQL #GitHubActions #SaaS #WebDevelopment

The first time I saw a NullPointerException in production, my heart sank. It wasnt the error itself that was scary—it was the fact that I hadnt handled it gracefully. Java exception handling is more than just try-catch. In a Spring Boot microservice, proper handling determines if your API returns a clean 404 Not Found or a messy 500 Internal Server Error stack trace. Always differentiate: use Checked exceptions for recoverable business logic (e.g., file not found), and Unchecked for runtime programming errors (e.g., NPEs, index out of bounds). Stop scattering try-catch blocks everywhere. 🛠️ The best practice for Spring Boot is centralized handling using the @ControllerAdvice and @ExceptionHandler annotations. This decouples error logic, cleans up your service layer, and ensures consistent error responses (often mapped to specific HTTP status codes). This pattern is crucial for building robust, scalable microservices. Good exception handling is a DevOps superpower. If your code swallows exceptions or logs poorly, debugging in Docker or Kubernetes becomes a nightmare. Always log the error correctly (using SLF4J/Logback) and ensure your logging framework can export structured logs that tools like Splunk or ELK can easily digest. This shifts error handling from a panic moment to a proactive observation point. 💡 What's the nastiest exception you've had to debug in a Spring Boot application, and how did you finally solve it? Share your war stories! #Java #SpringBoot #DevOps #Microservices #SystemDesign #CodingTips

🚀 Learning Update: Handling RESTful APIs in Spring Boot This week, I deepened my understanding of RESTful API handling in Spring Boot using various mapping annotations like @GetMapping, @PostMapping. Through hands-on practice, I learned how these annotations help connect HTTP requests to specific controller methods, making backend communication more structured, readable, and efficient. Key takeaways: ✅ Creating and testing REST endpoints ✅ Understanding request-response lifecycles ✅ Implementing CRUD operations smoothly ✅ Writing clean, maintainable controller code This learning gave me a stronger grasp of how real-world APIs function behind the scenes — and how to design them effectively for scalable applications. #SpringBoot #Java #RESTAPI #BackendDevelopment #LearningJourney #SoftwareEngineering

💻 The Real Full-Stack Flow: Where Backend Logic Meets Frontend Experience Being full-stack is more than knowing two sides of a codebase. It is about how data, design, and delivery flow together without friction. Every line connects to a user moment that should just work fast, secure, and reliable. ⚙️ Spring Boot with GraphQL and REST APIs builds the bridge between business logic and user intent. 🧠 Redis caching and Kafka messaging keep data fast and consistent across requests. 🪄 React with Redux and Angular Material turns backend responses into meaningful, responsive interactions. ☁️ Docker and Kubernetes ensure everything runs smoothly, no matter the environment. 🧩 Jenkins pipelines and GitHub Actions automate every merge, test, and deployment. 📈 Prometheus and ELK give full visibility from API latency to frontend load times. Full-stack is not a title. It is the art of connecting systems, data, and people in one continuous loop of feedback and improvement. #Java #SpringBoot #GraphQL #RESTAPI #Kafka #Redis #React #Angular #Redux #Docker #Kubernetes #Jenkins #GitHubActions #Prometheus #ELK #FullStackDevelopment #Microservices #CloudEngineering #SoftwareDevelopment

💥 Supercharge Your Kubernetes Development Workflow with Tilt! 💥 Are you tired of rebuilding Docker images and manually redeploying to Kubernetes every time you make a small code change? 😩 In my latest blog, I walk you through how Tilt brings “hot reload for Kubernetes” to your local dev workflow — with a complete Angular + Java (Spring Boot) + Kubernetes example. ⚙️ ✨ What you’ll learn: ✅ How Tilt automates builds, applies, and log collection ✅ Setting up Live Update for instant rebuilds ⚡ ✅ Structuring your full-stack project for rapid iteration ✅ Real-world productivity tips for microservice teams ✅ Full working setup using Angular, Spring Boot, Postgres & Kubernetes 🔹 Build → Deploy → Feedback → Repeat — all in seconds. 🔹 Run your entire app locally inside Kubernetes, not in simulation. 🔹 Experience true Dev Environment as Code. 🎯 If you’re developing microservices, this is a must-read to level up your Kubernetes productivity! 👉 Read the full guide here: https://lnkd.in/gZ9SnKp4 #Kubernetes #Tilt #DevOps #DeveloperExperience #Angular #Java #SpringBoot #Docker #CloudNative #Microservices #CNCF #K8s #Productivity #EngineeringExcellence #DevEnvironmentAsCode 🚀