Spring Boot Config: Properties vs YAML

I recently worked on containerizing a Spring Boot application using Docker, and it was a great hands-on experience in understanding how deployment works in real-world scenarios. The application I built is a simple REST API that returns the message “Hello Namaste” when accessed through a browser. I started by developing the Spring Boot application with a basic controller that handles HTTP requests and returns the response. Once the application was ready, I packaged it into a JAR file using Maven with the command mvn clean package. This generated the required JAR file inside the target folder. Next, I created a Dockerfile in the root directory of my project. In the Dockerfile, I used an OpenJDK base image, added the generated JAR file into the container, and specified the entry point to run the application. This step helped define how my application should run inside a container. After that, I built a Docker image using the command docker build -t rest-demo .. This created an image of my application along with all necessary dependencies. Then, I ran the container using docker run -p 8081:8081 rest-demo, which allowed me to access the application on my local machine. Finally, when I opened http://localhost:8081/, I successfully got the output “Hello Namaste”, confirming that my Spring Boot application was running inside a Docker container. Through this process, I learned how Docker helps in making applications portable, consistent, and easy to deploy across different environments. #Docker #SpringBoot #Java #Maven #DevOps #Containerization #Microservices #BackendDevelopment #CloudComputing #SoftwareDevelopment #Programming #Tech #Learning #OpenJDK #RESTAPI #WebDevelopment #BuildAndDeploy #DeveloperLife

Most Spring Boot microservices tutorials lie to you. They show: CRUD APIs Clean controllers Happy path flows They don’t show: What happens when 3 services fail together Why your DB melts under load How one retry can take down your system If your microservice only works on localhost, it’s not a microservice. Over the next 30 days, I’ll show how to build Spring Boot microservices that actually survive production. Follow along if you’re tired of theory. #microservices #springboot #backend #java #softwareengineering

🚀 Started my journey with Spring Boot! Built a small project to understand Spring Boot architecture, created REST APIs. Also learned how to connect a database and perform basic CRUD operations. This gave me a clear foundation of how backend systems work.  I’ve also attached a short notes PDF to help beginners get started with Spring Boot. Github Repo: https://lnkd.in/g6Z4kTKP #SpringBoot #Java #Backend #Learning #CRUD #API

Spring Boot Profiles — Managing Dev & Prod Like a Pro In real-world projects, we don’t use the same configuration everywhere Development ≠ Production So how do we handle different environments? Spring Boot gives us Profiles. --- 🔹 What is @Profile? It allows us to load different configurations based on environment. --- 🔹 Example: application-dev.properties https://lnkd.in/g5MBnKA2 --- 🔹 Usage: @Profile("dev") → Runs only in development @Profile("prod") → Runs only in production --- Why this is important: ✔ Separate configurations for different environments ✔ Safer deployments ✔ Clean and maintainable code ✔ Easy switching between dev & prod --- In simple terms: Spring Boot = “Tell me the environment, I’ll adjust everything.” --- Currently learning and applying these concepts step by step #SpringBoot #Java #BackendDevelopment #DevOps #Profiles #LearningInPublic

It’s Friday. A few years ago, deploying a full-stack application on a Friday afternoon involved sweating over an SSH terminal, manually dragging a .jar file via FTP, and praying the database didn't lock up. 😅🔥 Today? I just hit "Merge to main" and go grab a coffee. When I was architecting the Railway Management System, I knew I couldn't rely on manual deployments. When you are dealing with live ticket inventories and concurrent transactions, one missed environment variable or forgotten build step brings the whole booking engine down. A recruiter recently asked me how I ensure my code doesn't break production. The answer is simple: I don't trust myself. I trust my pipeline. Here is the exact anatomy of the CI/CD pipeline I use to sleep peacefully at night: 🛑 1. The Gatekeeper (Continuous Integration): The moment I open a Pull Request, GitHub Actions wakes up. It compiles the Spring Boot backend, lints the React frontend, and runs my JUnit tests. If even a single test fails or the code coverage drops below a certain threshold, the "Merge" button turns gray. No broken code is allowed to even touch the main branch. 📦 2. The Factory (Dockerization): Once the code is merged, the pipeline builds the artifacts. Maven packages the Java code, Vite bundles the React app, and then Docker wraps them up into clean, immutable images. It tags them with a specific version number and pushes them to a secure container registry. 🚢 3. The Delivery (Continuous Deployment): The server pulls the fresh Docker images. But before the new app spins up, a database migration tool (like Flyway or Liquibase) automatically runs any new SQL scripts to ensure the database schema matches the new code. Finally, the containers swap with zero downtime. Automation isn't just a DevOps buzzword. It is the ultimate safety net for software engineers. What is powering your CI/CD pipeline in 2026? Are you a modern GitHub Actions fan, or are you still maintaining a massive Jenkins server? Let’s debate below! 👇 Follow RAHUL VIJAYAN for more. #DevOps #CICD #GitHubActions #SpringBoot #ReactJS #SoftwareEngineering #TechCareers #FullStackDeveloper

Learning Docker & Containerizing My Spring Boot Application Lately, I’ve been diving into Docker and understanding how modern applications are built and deployed using containers. Here’s what I’ve worked on so far: - Learned how Docker works (images, containers, layers) - Built my own Docker images from scratch - Ran containers and understood port mapping & isolation - Containerized a Spring Boot application - Created a working Dockerfile and successfully ran my backend inside a container One of the most exciting parts was taking a Spring Boot project and turning it into a portable Docker image that can run anywhere without worrying about environment setup. This experience really helped me understand how developers ship applications in real-world production environments. #Docker #SpringBoot #BackendDevelopment #Java #DevOps #LearningInPublic #SoftwareDevelopment

We will reduce your Spring Boot deployment size and complexity by 20% in 14 days. Or you don’t pay. Most Spring Boot applications we analyze at Vistaar Digital Solution are 20–40% heavier than they need to be. Not because of bad engineers. But because of: • years of dependency buildup • unused auto-configurations • hidden transitive bloat • “just add it” culture So we built something different. 👉 Refactoring-as-a-Result No consulting decks. No endless audits. No “recommendations.” Just outcome. We will reduce your Spring Boot deployment size and complexity by 20% in 14 days. Or you don’t pay. What does “20% reduction” actually mean? We don’t deal in vague promises — we quantify everything. Deployment size reduction (measurable): • JAR / Docker image size ↓ • Total dependency footprint ↓ • Number of bundled libraries ↓ Complexity reduction (measurable): • Spring bean count ↓ • Auto-configurations loaded ↓ • Classpath size ↓ • Startup time ↓ • Memory footprint ↓ 👉 You must see ≥20% improvement in at least 2 of these metrics. How do we prove it? You get a before vs after report with: • Exact JAR size comparison • Startup time benchmarks • Heap/memory usage snapshots • Dependency graph diff • Bean & config count comparison No opinions. Just numbers. What you get ✔ Smaller JARs ✔ Faster startup times ✔ Lower memory usage ✔ Cleaner dependency graph ✔ Reduced production risk How we do it Our proprietary refactoring engine: • detects dead dependencies • prunes unnecessary Spring auto-config • simplifies runtime footprint • optimizes build artifacts This works best if: • your service has grown over 2+ years • your JAR is >100MB • startup time is increasing • your dependency tree is hard to reason about If that sounds familiar, comment “REFactor” or DM us. We’ll analyze your application and tell you upfront if we can achieve the 20%. No risk. Just results. #SpringBoot #Java #Microservices #Performance #TechDebt #SoftwareEngineering

🚀 Spring Boot – Building Production-Ready APIs Yesterday, I focused on making my Spring Boot application more robust, secure, and production-ready. 🧠 Key Learnings & Implementations: ✔️ Validation Layer • Used DTO + validation annotations (@NotBlank, @Email, @Size) • Ensures clean and correct input data ✔️ Global Exception Handling • Implemented "@RestControllerAdvice" • Centralized error handling instead of scattered try-catch blocks ✔️ Custom Error Response • Designed structured error format (timestamp, status, errors) • Makes APIs consistent and frontend-friendly ✔️ Clean Architecture Controller → Service → Repository → DTO → Exception Layer 💡 Why this matters: • Prevents bad data from entering the system • Improves API reliability and maintainability • Provides clear and predictable responses for frontend integration 💻 DSA Practice: • Array operations (reverse, sorted check, move zeros) • Strengthening problem-solving alongside backend concepts ✨ From basic CRUD to validation, exception handling, and structured responses — this feels like a big step toward real-world backend development. #SpringBoot #Java #BackendDevelopment #RESTAPI #Microservices #CleanCode #DSA #LearningInPublic #SoftwareEngineering

CI/CD isn’t just a "best practice" — it’s the last line of defense. 🛡️ A robust automated workflow to keep production rock-solid: 🔄 Every PR Triggers: • Build Check & Lint (Spotless) • Unit Tests (JUnit/Mockito) • Quality Gate (SonarQube) ⚖️ Merge Rules: • Min. 1 Peer Approval • 100% Status Checks Pass • No Direct Push to main 🚀 Deployment: • Auto-deploy to Staging • Manual Approval for Production 🚨 3 Non-Negotiable Rules: 1. No Build, No Merge. No exceptions for "urgent" fixes. 2. Fix Tests, Don't Skip. Flaky tests are technical debt. 3. The 5-Min Rule. If it's slow, optimize it immediately. A deployment pipeline is a safety net. Don't let it have holes. What’s your pipeline’s average runtime? 👇 #CICD #GitHubActions #SpringBoot #SoftwareEngineering #Java #AWS

Image Build & Promotion Pipeline with GitHub Actions In actual projects, You do not just build an image and push it to a registry. The image needs to pass through several quality and security gates first. We have a hands-on guide that walks you through a complete, production-grade Docker image build and promotion pipeline using GitHub Actions. Here is what is covered in this blog. - Automating a Java application build and Dockerization with GitHub Actions - Managing container registry credentials securely with GitHub Secrets - Promoting images through dev, stage and prod registries - Signing the final container image using Cosign - Build caching, image tagging strategy, registry architecture, and more.. 𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gWWWEMTV Bookmark it, try the pipeline in your own repo, and let us know what you would add or change. #devops #practicaldevops #docker