💡 Java Memory Analysis Made Simple Ever wondered why your Java application slows down under load? Understanding memory usage is key. Tools like Eclipse Memory Analyzer (MAT) and jmap let you inspect heap dumps, identify memory leaks, and optimize your app’s performance. Pro tip: Regular memory profiling can save hours of debugging and improve user experience dramatically. #Java #Performance #MemoryAnalysis #EclipseMAT #JVM
Java Memory Analysis with Eclipse MAT and jmap
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🚀 Java Concept Series Java is a high-level, object-oriented language based on “Write Once, Run Anywhere.” It is widely used in real-world applications like: ✔ Banking systems ✔ Android apps ✔ Web applications ✔ Enterprise software 👉 Next: JVM, JDK, JRE (core basics) #Java #Programming #PlacementPreparation #LearnInPublic #CodingJourney
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While building a recent Spring Boot application, I realized... The Hook: Stop defaulting to .parallelStream() to make your Java code "faster." 🛑 The Insight: It’s a common misconception that parallel streams always improve performance. Under the hood, parallelStream() uses the common ForkJoinPool. If you are executing CPU-intensive tasks on a massive dataset, it’s great. But if you are doing I/O operations (like database calls or network requests) inside that stream, you will exhaust the thread pool and bottleneck your entire application. The Pro Tip: Always benchmark. For I/O bound tasks, look into asynchronous programming (like CompletableFuture) or Java 21's Virtual Threads instead of parallel streams. #Java #PerformanceOptimization #SoftwareEngineering #CleanCode
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By recently working with Java, I asked myself: 4GB for heap memory and vm still crashing during unit tests? I believe this turned into something common to Java devs, I mean, not the crash, but reserve 4GB to the app to run. The whole sort of boxing, garbage collection and syntax sugar available on Java, made language more easier over the time, but also made software produced by it less efficient to deal with actual hardware. Java should be consuming less hardware, not more. I decided to focus on rust because he has a more honest approach on how tech is evolving. #rust #java #programming #memory #hardware #tech #performance
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We’re excited to introduce Webswing 26.1! This release comes packed with new features and improvements designed to bring even more value to your Java applications. With a strong focus on Java 25, Webswing 26.1 ensures you’re ready to take advantage of the latest advancements in the Java ecosystem. 👉 Download now at https://lnkd.in/eZFPXDWf #java #oracleforms #swing #javafx #eclipse #swt #netbeans #webswing #LegacyModernisation #JavaApps #oracle #technology #software #programming #app
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Last week, we faced a critical production issue that reminded me how tricky multithreading can be in Java. 🔍 Problem: Our application suddenly became slow under load. CPU usage was low, but requests were timing out. 🧠 Root Cause: After analyzing thread dumps using tools like jstack and VisualVM, we discovered a classic deadlock situation. Two threads were waiting on each other’s locks — and nothing was moving forward. ⚠️ Key Learnings: Always maintain a consistent lock ordering to avoid deadlocks Avoid excessive use of synchronized blocks Prefer high-level concurrency utilities like ExecutorService, ReentrantLock, and ConcurrentHashMap Monitor thread pools in production (size, queue, rejection policy) Use tools like jconsole, VisualVM, and thread dumps regularly 💡 Pro Tip: Multithreading issues rarely appear in development — they show up under real traffic. Always design with concurrency in mind. 👨💻 As developers, writing correct concurrent code is not just a skill — it's a responsibility. #Java #Multithreading #BackendDevelopment #ProductionIssues #SoftwareEngineering #Debugging #TechLearning
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Over reliance on exceptions is a big performance drain! Easy to overlook. Check out Jonathan Vogel ‘s post for the full list of anti-patterns.
One method in my Java demo app was using 71% of CPU. The code looked perfectly fine. After my DevNexus talk, attendees kept asking about the specific anti-patterns. This post shows eight patterns that compile fine, pass code review, and silently kill performance. Before/after: 1,198ms → 239ms. 85K → 419K orders/sec. 19 GC pauses → 4. Part 1 of 3. Link in comments. Shoutout to Vinicius Senger for bringing me into his DevNexus talk on Java modernization, this series wouldn't exist without that.
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Built a Vehicle Service Manager Android App using Java & SQLite 📱 ✔ Add, update & delete service records (CRUD) ✔ Service history tracking ✔ DatePicker integration ✔ Cost & notes management ✔ AlertDialog for delete confirmation Clean UI with efficient local data handling. #AndroidDevelopment #Java #SQLite #CRUD #MobileApp
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Most Java apps don’t have performance problems… they have hidden inefficiencies. Streams, SQL queries, memory usage — everything looks fine until your CPU spikes in production. I built a simple tool to detect these issues in seconds: → Run one command → Get a clear report → Fix what actually matters No complex setup. No guesswork. If you’re working with Java and care about performance: 👉 try it here : https://joptimize.io #java #performance #backend #programming #devtools #optimization #jvm #softwareengineering
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#day24 🛠️ Debugging multithreading — what happens in production Concurrency bugs don’t always show in development — they appear in production ⚠️ 👉 Key tools I explored: Thread dump (jstack) VisualVM / JConsole Java Flight Recorder 👉 Common issues: Deadlocks High CPU usage Thread contention 💡 Example insight: Too many BLOCKED threads → lock contention → performance bottleneck 👉 Fix: reduce synchronization or use concurrent structures #Java #Multithreading #Debugging #PerformanceTuning #Concurrency #JavaDeveloper #InterviewPreparation #LearningInPublic
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Java 17 brought major improvements for modern application development, and it’s a great step forward for building scalable enterprise systems. 🚀 Some standout features I really like: ✅ Sealed Classes – Better control over inheritance and cleaner domain models ✅ Pattern Matching for switch (preview) – Cleaner and more readable logic ✅ Records – Less boilerplate for data carrier classes ✅ Enhanced Random Generator API – Better flexibility for random values ✅ Strong encapsulation of JDK internals – More secure and maintainable apps ✅ Long-Term Support (LTS) – Stability for enterprise production systems Why it matters: 🔹 Better performance 🔹 Cleaner code 🔹 Improved security 🔹 Modern language enhancements 🔹 Ideal for upgrading legacy systems Recently, many organizations are upgrading older Java versions to Java 17 to gain long-term support and modern capabilities. Which Java 17 feature do you use most in your projects? 👇 #Java #Java17 #Programming #SoftwareEngineering #BackendDevelopment #SpringBoot #CleanCode #Developers #Tech #Coding
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