Spring Boot Circular Dependencies Can Break Your App at Startup

You’re Only Using 20% of Spring Boot… And That’s the Catch #Java #SpringBoot #Microservices #BackendDevelopment #SoftwareEngineering #CleanCode #Programming #Developers #Coding #Tech #JavaDeveloper #SystemDesign #Debugging #Architecture #Spring “You use 20% of Spring Boot… But it quietly solves 80% of your backend problems.” The real question is : Do you know which 20% is being used… and what the other 80% is doing behind the scenes ? Because the day it breaks - • it’s no longer debugging code. • It’s debugging Spring itself. Example : • Add one starter → App runs. • Override one config → Everything stops working. Spring Boot feels simple… until it needs to be understood. Behind every “simple” app… there’s hidden complexity waiting to be uncovered. Understand what most developers use… but very few truly understand. "𝗕𝗲𝘆𝗼𝗻𝗱 𝗦𝘆𝗻𝘁𝗮𝘅" Follow to understand the 80% of Spring Boot most developers never see.

Ever noticed how one small backend concept can quietly make your entire application more reliable? 💡 Today I explored something powerful in Spring Boot — "OncePerRequestFilter". At first, it looks like just another filter. But when you start building real-world applications with JWT authentication, request logging, security checks, and tracing, this class becomes a game changer. The best part? It ensures your filter logic runs only once for every HTTP request. Sounds simple, right? But imagine a production system where the same request gets internally forwarded and your filter executes multiple times. That could mean: 🔁 repeated token validation 📝 duplicate logs ⚠️ unnecessary processing 🐢 slower performance This is where "OncePerRequestFilter" saves the day. It brings consistency, security, and cleaner request flow to your application. One of the most common use cases is in JWT authentication: ➡️ Read token from header ➡️ Validate it ➡️ Authenticate user ➡️ Set security context ➡️ Pass request forward And all of this happens exactly once. For me, this is one of those concepts that proves: Great backend engineering is often about controlling what should happen once — and only once. Small concept. Big impact. 🚀 Backend developers, where have you used "OncePerRequestFilter" in your projects? Would love to learn your real-world use cases in the comments 👇 #Java #SpringBoot #SpringSecurity #BackendDevelopment #JavaDeveloper #SoftwareEngineering #CodingJourney #TechLearning #JWT #WebDevelopment #Programming #Developers #unique2

Spring Boot CommandLineRunner — Run logic at startup ⚡ Want to execute code after app starts? Use this 👇 @Component public class StartupRunner implements CommandLineRunner { @Override public void run(String... args) { System.out.println("App Started!"); } } 💡 Use cases: ✔ Preload data ✔ Validate configs ✔ Initialize resources ⚠️ Mistake: Putting heavy logic → slows startup ❌ 👉 Keep it lightweight Startup logic should be fast & clean 🚀 #SpringBoot #Java #BackendDeveloper

Most Spring Boot startup failures are not random. They happen at a very specific stage of the application lifecycle. The problem is that many developers never learn what happens after: SpringApplication.run(Application.class, args) Spring Boot feels like magic until something breaks in production. A bean is missing. The app takes 90 seconds to start. Memory usage spikes during deployment. Tomcat refuses to start because the port is already in use. A circular dependency suddenly appears after one small code change. At that point, understanding the startup lifecycle becomes one of the most valuable backend skills you can have. Internally, Spring Boot follows a very predictable sequence: 1. Create the SpringApplication object 2. Detect whether the application is Servlet-based or Reactive 3. Load auto-configurations from spring.factories 4. Prepare the environment from properties, YAML files, environment variables, and command-line arguments 5. Create the ApplicationContext 6. Scan components and register bean definitions 7. Apply conditional auto-configurations 8. Instantiate and wire beans 9. Start the embedded server such as Tomcat 10. Publish lifecycle events like ApplicationReadyEvent What makes this important is that most production issues map directly to one of these phases. i) Slow startup time → too many beans, expensive initialization logic, unnecessary dependencies. ii) Missing bean problems → conditional annotations like @ConditionalOnMissingBean silently skipping configuration. iii) Circular dependency failures → issues during bean instantiation. iv) Port conflicts → embedded server initialization failure. v) High memory consumption → large applications loading thousands of beans before serving a single request. vi) Unexpected auto-configuration behavior → framework assumptions not matching application design. One of the biggest misconceptions about Spring Boot is that it “does everything automatically.” It does not. It follows a highly structured startup pipeline with clear decision points. Once you understand that pipeline, debugging becomes faster, startup optimization becomes easier, and architectural decisions become more intentional. That is the difference between someone who can use Spring Boot and someone who can operate Spring Boot systems in production. #SpringBoot #Java #BackendDevelopment #SoftwareEngineering #Microservices #SystemDesign #JavaDeveloper #Programming #DistributedSystems

Spring Boot Lazy Initialization — Boost startup performance ⚡ By default: 👉 All beans load at startup ❌ But you can delay it using: spring.main.lazy-initialization=true 💡 What happens: Beans load ONLY when needed ✅ ✔ Faster startup ✔ Reduced memory usage ⚠️ Trade-off: First request may be slower 👉 Best use case: Large applications with many beans Performance is about smart trade-offs 🔥 #SpringBoot #Performance #Java

Most developers start with Spring Boot thinking “it’s simple and everything just works”… and it does—initially. But as the project grows, things start breaking, slowing down, and becoming hard to maintain. I’ve seen (and made 😅) some of these common mistakes: ❌ Overusing @Autowired everywhere ❌ No proper layering (Controller → Service → Repository) ❌ Ignoring exception handling ❌ Writing everything in one class (“God class”) ❌ Hardcoding configs The shift happens when you start writing **clean, scalable, and maintainable code**: ✅ Constructor-based dependency injection ✅ Clean architecture principles ✅ Global exception handling (@ControllerAdvice) ✅ Small, focused components ✅ Environment-based configs (application.yml / profiles) 💡 Spring Boot is powerful—but without structure, it can quickly turn into a monolith that’s hard to manage. Have you faced any of these issues in real projects? Let’s discuss 👇 #SpringBoot #Java #BackendDevelopment #CleanCode #Microservices #JavaDeveloper

🚀 𝗦𝗽𝗿𝗶𝗻𝗴 𝗕𝗲𝗮𝗻 𝗟𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 — 𝗜𝗳 𝗬𝗼𝘂 𝗗𝗼𝗻’𝘁 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗧𝗵𝗶𝘀, 𝗬𝗼𝘂’𝗿𝗲 𝗗𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗕𝗹𝗶𝗻𝗱 Most developers use Spring daily… But can’t answer this: 👉 𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝘁𝗼 𝗮 𝗯𝗲𝗮𝗻 𝗮𝗳𝘁𝗲𝗿 𝗶𝘁’𝘀 𝗰𝗿𝗲𝗮𝘁𝗲𝗱? 🧠 The Lifecycle: Creation → Injection → Initialization → Ready → Destruction That’s it. But each step matters. ⚙️ 𝗞𝗲𝘆 𝗦𝘁𝗮𝗴𝗲𝘀 𝗕𝗲𝗮𝗻 𝗗𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻 𝗟𝗼𝗮𝗱𝗲𝗱: Spring reads the config and decides what beans need to be created 𝗕𝗲𝗮𝗻 𝗜𝗻𝘀𝘁𝗮𝗻𝘁𝗶𝗮𝘁𝗲𝗱: Object is created in memory (constructor runs) 𝗗𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝗰𝗶𝗲𝘀 𝗜𝗻𝗷𝗲𝗰𝘁𝗲𝗱: Required dependencies are wired into the bean 𝗕𝗲𝗮𝗻𝗣𝗼𝘀𝘁𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗼𝗿 (𝗕𝗲𝗳𝗼𝗿𝗲 𝗜𝗻𝗶𝘁): Custom logic runs before the bean is initialized 𝗜𝗻𝗶𝘁𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 (@𝗣𝗼𝘀𝘁𝗖𝗼𝗻𝘀𝘁𝗿𝘂𝗰𝘁 / 𝗶𝗻𝗶𝘁()): Final setup happens — bean becomes fully usable 𝗕𝗲𝗮𝗻𝗣𝗼𝘀𝘁𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗼𝗿 (𝗔𝗳𝘁𝗲𝗿 𝗜𝗻𝗶𝘁): Bean may be wrapped/modified (e.g., proxies, AOP) 𝗕𝗲𝗮𝗻 𝗥𝗲𝗮𝗱𝘆 𝘁𝗼 𝗨𝘀𝗲: Bean is now used by the application 𝗕𝗲𝗮𝗻 𝗗𝗲𝘀𝘁𝗿𝗼𝘆𝗲𝗱 (@𝗣𝗿𝗲𝗗𝗲𝘀𝘁𝗿𝗼𝘆 / 𝗱𝗲𝘀𝘁𝗿𝗼𝘆()): Cleanup happens — resources are released before shutdown 💣 𝗪𝗵𝗲𝗿𝗲 𝘁𝗵𝗶𝗻𝗴𝘀 𝗯𝗿𝗲𝗮𝗸 ❌ Using bean before initialization → NullPointerException ❌ Ignoring destroy phase → Memory leaks ⚠️ Hard Truth Field injection causes hidden issues Most devs don’t know when init runs Almost nobody handles cleanup properly If you don’t know the lifecycle stage your bean is in… 👉 You’re not debugging 👉 You’re guessing 𝗡𝗲𝘅𝘁 𝘁𝗶𝗺𝗲 𝘆𝗼𝘂𝗿 𝗮𝗽𝗽 𝗳𝗮𝗶𝗹𝘀 — Ask: “Which lifecycle stage broke?” That’s how real backend engineers think. #Java #BackendDeveloper #Hiring #ImmediateJoiner #ServingNoticePeriod #SpringBoot #JavaDeveloper

Most developers use Spring Boot… but not to its full potential. It’s not just about building APIs — it’s about building production-ready, scalable systems efficiently. Here are 15 powerful Spring Boot features that can level up your backend game: ⚙️ Auto-configuration exclusions → remove unnecessary overhead 🌍 Advanced profiles → manage environments like dev, prod, k8s 🧠 Conditional annotations → load beans only when needed 🔒 Built-in security → strong defaults out of the box 📊 Actuator & observability → real-time insights into your system 🔄 DevTools → faster development cycles 📦 Layered JARs → optimized Docker builds 🛠 Externalized config → flexible and environment-driven setup 📡 Application events → clean decoupling between components 🧪 Testing support → robust and faster test execution …and more that experienced engineers rely on daily. 💡 Why this matters: • Lower infrastructure cost • Faster deployments • Fewer production bugs • More resilient systems 🚀 Senior mindset: Don’t reinvent what Spring already solves. Use features intentionally. Build with production in mind from day one. Spring Boot isn’t just a framework — it’s a complete platform. #SpringBoot #Java #BackendDevelopment #Microservices #SoftwareEngineering #Coding #Developers #Tech

Most developers use Spring Boot… but not to its full potential. It’s not just about building APIs — it’s about building production-ready, scalable systems efficiently. Here are 15 powerful Spring Boot features that can level up your backend game: ⚙️ Auto-configuration exclusions → remove unnecessary overhead 🌍 Advanced profiles → manage environments like dev, prod, k8s 🧠 Conditional annotations → load beans only when needed 🔒 Built-in security → strong defaults out of the box 📊 Actuator & observability → real-time insights into your system 🔄 DevTools → faster development cycles 📦 Layered JARs → optimized Docker builds 🛠 Externalized config → flexible and environment-driven setup 📡 Application events → clean decoupling between components 🧪 Testing support → robust and faster test execution …and more that experienced engineers rely on daily. 💡 Why this matters: • Lower infrastructure cost • Faster deployments • Fewer production bugs • More resilient systems 🚀 Senior mindset: Don’t reinvent what Spring already solves. Use features intentionally. Build with production in mind from day one. Spring Boot isn’t just a framework — it’s a complete platform. #SpringBoot #Java #BackendDevelopment #Microservices #SoftwareEngineering #Coding #Developers #Tech

Here’s what happens after you push code. You think the job is done. Tests passed. Feature shipped. But that’s where the real story starts 👇 🚨 Something breaks in production 🐌 Performance suddenly drops 📉 Users start bouncing 📦 Queue jobs start failing 😅 And now… it’s “urgent” Every Laravel developer has been there. Because pushing code is easy. Maintaining stability is hard. What I learned the hard way: ✔️ Write code for production, not just local ✔️ Monitor everything (logs, queues, errors) ✔️ Optimize before it becomes a problem ✔️ Always expect edge cases ✔️ Have rollback plans ready Because “it works on my machine.” is not a deployment strategy. Real developers don’t just ship code… They take responsibility for what happens after. — Be honest 👇 What’s the worst thing that broke right after you deployed? #Laravel #WebDevelopment #Developers #Programming #SoftwareDevelopment #Backend #DevLife #Coding #Tech