Reducing API Payload Size with DTOs Improves Performance

Recently worked on improving API performance in a backend system ⚡ 📉 Problem: High response time under load 🔧 What I did: Optimized DB queries Introduced caching Refactored inefficient logic 📈 Result: ~40% performance improvement 🚀 💡 Lesson: Performance issues are rarely about one thing — it’s always a combination. Small improvements → Big impact. #BackendDevelopment #PerformanceOptimization #Java #Engineering

Have you ever debugged a production issue where logs show the same error everywhere… but you still can’t figure out what actually failed? I used to make this mistake a lot — catch exception → log error → throw again Service logs Repository logs Controller logs Same exception 3–4 times. Just noise. Then I changed one simple thing: don’t log where you’re just throwing the exception. Now I follow this: Service/Repository → just throw or wrap the exception Log only once at the boundary (API / consumer) Always add context We often don’t pay much attention to logging, but it plays a crucial role when debugging a system. You need clarity on where to log, what to log, and where not to. Now instead of messy logs, I get one clear error log with full context. Debugging feels less like guessing and more like tracing a story. Less logs. Better logs. That’s the real strategy. #BackendDevelopment #Microservices #SystemDesign #Java #SpringBoot #Logging #SoftwareEngineering #CleanCode

#Post7 In the previous post, we saw how to handle exceptions globally using @ControllerAdvice. Now let’s take it one step further 👇 How do we handle specific errors properly? That’s where Custom Exceptions come in 🔥 Instead of using generic exceptions, we can create our own exception based on the use case. Example: public class UserNotFoundException extends RuntimeException { public UserNotFoundException(String message) { super(message); } } 👉 Now we can throw this exception when user is not found Example usage: if(user == null){ throw new UserNotFoundException("User not found"); } 💡 Why use Custom Exceptions? • Better error clarity • Easy debugging • More control over API responses Key takeaway: Use custom exceptions to make your API errors more meaningful and structured 👍 In the next post, we will understand validation using @Valid 🔥 #Java #SpringBoot #BackendDevelopment #RESTAPI #LearnInPublic

🚨 @Transactional doesn’t always work the way you think I assumed it works everywhere. I was wrong. 💥 Issue I faced: Transaction was NOT rolling back on failure. Root cause? Method was called internally within the same class. Spring uses proxies → internal calls bypass them. ✅ Fix: * Moved logic to separate service class 💡 Takeaway: @Transactional works only when called via Spring proxy. This is one of those bugs that wastes hours. #Java #SpringBoot #BackendDevelopment #SoftwareEngineering  #Microservices #JPA #RESTAPI  #DeveloperLife #CareerGrowth

I had an API returning correct data. But response time was too high. Issue turned out to be unnecessary data being fetched from DB. Reduced fields, optimized query. Small change, big impact. #Backend #Java #SpringBoot #Performance

Day 19 of #Leetcode150DaysChallenge Today’s problem: 237. Delete Node in a Linked List Instead of deleting the node directly, we copy the value of the next node into the current node and then skip the next node. This way, the current node effectively becomes the next node, and the original next node gets removed. #LeetCode #DataStructures #Java #ProblemSolving

🚀 Day 7 – Exception Handling: More Than Just try-catch Today I focused on how exception handling should be used in real applications—not just syntax. try { int result = 10 / 0; } catch (Exception e) { System.out.println("Error occurred"); } This works… but is it the right approach? 🤔 👉 Catching generic "Exception" is usually a bad practice 💡 Better approach: ✔ Catch specific exceptions (like "ArithmeticException") ✔ Helps in debugging and handling issues more precisely ⚠️ Another insight: Avoid using exceptions for normal flow control Example: if (value != null) { value.process(); } 👉 is better than relying on exceptions 💡 Key takeaway: - Exceptions are for unexpected scenarios, not regular logic - Proper handling improves readability, debugging, and reliability Small changes here can make a big difference in production code. #Java #BackendDevelopment #ExceptionHandling #CleanCode #LearningInPublic

Is REST really enough for everything… or are we just used to it? I’ve been working with GraphQL lately and spent some time exploring it in detail — and it definitely changed how I think about APIs. So I put together a PDF with what I learned, practical insights, and a few things that made me pause and rethink. Sharing it here — curious to know what you think: Is GraphQL actually better, or just another hype? #GraphQL #APIs #BackendDevelopment #TechDiscussion #Java #RestAPI

Struggling with a 'Java heap space error' in your application? 🤯 It is a frustrating but solvable issue! Troubleshooting these OutOfMemoryErrors is a clear, multi-step process: 1️⃣ Collect GC Logs: Enable GC logging to get a timeline of memory pressure, which helps you understand whether your heap is gradually filling up from a leak or if there was a sudden traffic burst. 2️⃣ Capture a Heap Dump: Grab a snapshot of your application memory right before the JVM throws the error (e.g., using -XX:+HeapDumpOnOutOfMemoryError) to see exactly what objects are present, their references, and their sizes. 3️⃣ Analyze the Dump: Use tools like HeapHero or JHat to dig into the dump and uncover valuable insights into your application's memory usage patterns. 4️⃣ Capture a Thread Dump: If your app becomes unresponsive before crashing, a thread dump can reveal stuck threads that are holding onto large object graphs and preventing garbage collection. Ready to dive deeper into these steps and master Java memory issues? Read the full guide here: 👉 https://lnkd.in/gQu6cy5w #Java #JavaDevelopment #SoftwareEngineering #PerformanceTuning #HeapDump #GarbageCollection #HeapHero #OutOfMemoryError

What actually happens when you hit a REST API? 🤔 Let’s break it down step by step 👇 1️⃣ Client sends HTTP request 2️⃣ Request hits DispatcherServlet 3️⃣ HandlerMapping finds the correct controller 4️⃣ Controller processes request 5️⃣ Service layer applies business logic 6️⃣ Repository interacts with DB 7️⃣ Response is returned as JSON 💡 Behind the scenes: - Jackson converts Java → JSON - Spring handles dependency injection - Exception handling via @ControllerAdvice ⚡ Real benefit: Understanding this flow helps you: ✔ Debug faster ✔ Write better APIs ✔ Optimize performance Next time you call an API, remember — a lot is happening inside 🔥 Follow for more backend deep dives 🚀 #SpringBoot #Java #RestAPI #BackendDeveloper