What is an MBean in Java and its uses

Java 26 is here, and it's one of the most practical releases in years. !!! Released on March 17, 2026, Java 26 may not have flashy headline features, but it introduces 10 solid JEPs that enhance the platform's performance, safety, and intelligence. Key updates for enterprise Java developers include: ⚡ G1 GC throughput boost (JEP 522): Reduced synchronization between application threads and GC threads leads to more work done per second, with no code changes needed—your application simply gets faster. 🚀 AOT Caching now works with ZGC (JEP 516): Project Leyden enables AOT object caching for all garbage collectors, including ZGC, resulting in faster startup and low-latency GC in production. Lambda and containerized Java have reached a new level. 🌐 HTTP/3 in the standard HTTP Client (JEP 517): Java's built-in client now supports HTTP/3, offering lower latency, no head-of-line blocking, and improved mobile performance, all with minimal code changes. 🔐 Final means Final again (JEP 500): Java is addressing a 30-year loophole—reflective mutation of final fields will now trigger warnings and be blocked in a future release, promoting "integrity by default." 🪦 Goodbye, Applets (JEP 504): After being deprecated in Java 9 and marked for removal in Java 17, Applets are finally gone in Java 26. The bigger picture? This marks the 17th consecutive on-time release under the 6-month cadence. Java is not just alive; it's functioning like a well-run product team. #Java #Java26 #JVM #SpringBoot #BackendEngineering #Microservices #SoftwareEngineering #systemdesign #distributedsystems 

📚 Strengthening My Core Java Knowledge – Collections Framework Today, I actively engaged in strengthening my understanding of the Java Collections Framework, focusing on internal implementations and performance aspects. I explored the hierarchy and relationships between key interfaces and classes: 🔹 List Implementations ArrayList → Dynamic array, O(1) access, amortized O(1) insertion LinkedList → Doubly linked list, efficient insert/delete, O(n) access 🔹 Queue / Deque PriorityQueue → Min-heap based, O(log n) insertion/removal Deque → Supports both stack & queue operations (ArrayDeque preferred over Stack) 🔹 Set Implementations HashSet → Backed by HashMap, O(1) average operations Ensures uniqueness via hashing & equals() contract 🔹 Map Implementations HashMap → Array + LinkedList/Tree (since Java 8), O(1) average TreeMap → Red-Black Tree, O(log n), sorted keys Understanding how these data structures work internally and when to use them is crucial for writing efficient and optimized code. 💡 Key Takeaways: ✔ Lists maintain order and allow duplicates ✔ Sets store unique elements ✔ Queues follow FIFO (with variations like priority-based) ✔ Maps store key-value pairs for fast lookup Sincerely grateful to my guide kshitij kenganavar sir for providing such clear and insightful explanations that made the concepts easy to understand. This strengthens my foundation in DSA, system performance, and backend development, especially for writing scalable and optimized Java applications. #Java #DSA #CollectionsFramework #Programming #SoftwareDevelopment #CodingJourney

🚀 The Evolution of Java (A Developer’s Lens) ⚡ Java 8 - The Game Changer (2014) Introduced lambda expressions and the Streams API, shifting Java toward a functional programming paradigm. This version significantly improved code readability and reduced boilerplate, enabling developers to write more expressive and efficient data-processing logic. It laid the foundation for modern Java development and is still widely used in enterprise systems. ⚡ Java 11 - The Enterprise Standard (2018) Marked as a Long-Term Support (LTS) release, Java 11 became the go-to version for production systems. It introduced the modern HttpClient API, improved garbage collection, and enhanced container awareness, making it highly suitable for cloud deployments and microservices architectures. ⚡ Java 17 - The Modern Standard (2021) Another LTS release that focused on cleaner and more maintainable code. Features like records reduced boilerplate for data models, while sealed classes improved control over inheritance. Combined with pattern matching enhancements, Java 17 made backend development more structured and robust. ⚡ Java 21 - The Future is Here (2023) A breakthrough release with Project Loom’s virtual threads, redefining concurrency in Java. It allows applications to handle massive numbers of lightweight threads efficiently, simplifying asynchronous programming and significantly improving scalability for high-throughput systems. 👉 The real question is: Are you still using Java, or are you leveraging modern Java? #Java #SoftwareEngineering #BackendDevelopment #Microservices #TechEvolution #Programming

I wrote an article for JAVAPRO about the Foreign Function and Memory (FFM) API, added in #Java 22, and how it got used to add a new and better plugin to The Pi4J Project. You can read it here: https://lnkd.in/em6K5xhM

⚡ Java 8 Streams — How It Works Internally Java 8 introduced Streams to simplify data processing with a clean and functional approach. But what actually happens behind the scenes? 👇 🔹 1. Source Data comes from collections, arrays, or I/O channels. 🔹 2. Stream Pipeline (Lazy Evaluation) Intermediate operations like: ✔️ filter() → Select required data ✔️ map() → Transform data ✔️ sorted() → Arrange data 💡 These operations are lazy — they don’t execute until a terminal operation is triggered. 🔹 3. Terminal Operation ✔️ collect() / reduce() → Produces final result 🚀 Key Concepts to Remember: ✔️ Lazy Processing → Executes only when needed ✔️ Functional Style → Uses lambdas & stateless operations ✔️ Parallel Processing → Easily scalable with .parallelStream() ✔️ Immutability → Original data remains unchanged 💡 Streams are not just about writing less code — they are about writing efficient, readable, and scalable code. 👉 Mastering Streams is a must-have skill for modern Java backend development. #Java #Java8 #Streams #BackendDevelopment #FunctionalProgramming #SoftwareEngineering

☕ Java 27 — JEP 527: Post-quantum TLS 1.3 hybrid key exchange SSLSocket socket = ( SSLSocket ) SSLContext.getDefault() .getSocketFactory() .createSocket(); SSLParameters params = socket.getSSLParameters(); params.setNamedGroups( new String[]{ "SecP256r1MLKEM768", "X25519MLKEM768", "secp256r1", "x25519" } ); socket.setSSLParameters( params ); • Java 27 adds hybrid post-quantum key exchange options to TLS 1.3. • The important message for developers is that javax.net.ssl users benefit by default, even without code changes. • This is the “quantum” feature worth talking about because it changes how teams think about long-term confidentiality. #java #java27 #jdk27 #tls13 #quantum #postquantum Go further with Java certification: Java👇 https://bit.ly/javaOCP Spring👇 https://bit.ly/2v7222 SpringBook👇 https://bit.ly/springtify JavaBook👇 https://bit.ly/jroadmap

☕ Java 26 — JEP 517: HTTP/3 for the HTTP Client API var client = HttpClient.newBuilder() .version( HttpClient.Version.HTTP_3 ) .build(); var request = HttpRequest.newBuilder( URI.create( "https://vvauban.com/" ) ) .version( HttpClient.Version.HTTP_3 ) .GET() .build(); var response = client.send( request, HttpResponse.BodyHandlers.ofString() ); • Java’s standard HttpClient can now opt into HTTP/3. • That gives developers access to QUIC-based transport without changing libraries. • If the peer does not support HTTP/3, the client can fall back to older HTTP versions. #java #java26 #jdk26 #pathtojava27 #jep517 Go further with Java certification: Java👇 https://bit.ly/javaOCP Spring👇 https://bit.ly/2v7222 SpringBook👇 https://bit.ly/springtify JavaBook👇 https://bit.ly/jroadmap

🚀 Java 8 vs Java 17 — What actually matters in production Everyone asks: “Should we upgrade from Java 8 to Java 17?” The real question is: what changes in production, not just in theory? After working on large-scale systems, here’s the practical difference 👇 ⚡ 1. Performance & GC (This is HUGE) Java 17 brings better GCs (ZGC, Shenandoah improvements) Lower pause times, better latency under load More predictable performance for microservices 👉 In real systems: Less GC tuning, fewer production surprises 🔒 2. Security & Support (Often ignored, but critical) Java 8 is nearing the end of meaningful enterprise support (depending on vendor) Java 17 = LTS + modern security updates 👉 In production: Fewer vulnerabilities, easier compliance (PCI, SOX, etc.) 🧠 3. Developer Productivity Java 17 adds features that actually reduce boilerplate: record → cleaner DTOs sealed classes → better domain modeling pattern matching → simpler code 👉 Result: Less code, fewer bugs, faster reviews 🧱 4. Better for Modern Architectures Java 17 works much better with: Spring Boot 3+ Cloud-native deployments (Docker, Kubernetes) Reactive and event-driven systems 👉 In production: Faster startup, better container performance 🐳 5. JVM + Container Awareness Improved memory handling in containers Better CPU utilization 👉 Real impact: Lower cloud cost + more stable pods ⚠️ But here’s the reality (most teams ignore this) Upgrading is NOT just changing the JDK: Dependency upgrades (Spring, libraries) Build pipeline changes Testing legacy behavior Compatibility issues 👉 Biggest risk: Hidden breaking changes in old libraries 💡 My Production Take ✔ Stay on Java 8 → only if legacy system is stable & not evolving ✔ Move to Java 17 → if you're building or scaling modern systems 👉 For most teams today: Java 17 is not optional — it’s inevitable 🔥 Final Thought Java 8 made Java relevant again. Java 17 makes it future-ready. 💬 Curious — are you still on Java 8 or already moved to Java 17? What challenges did you face? #Java #SpringBoot #Microservices #SystemDesign #Backend #Cloud #SoftwareEngineering

You have written thousands of Java objects. You have never actually seen one. Not the real thing — the bytes sitting on the heap, the hidden 12-byte header every object carries before a single field is stored, the padding the JVM adds without asking. Java 25 just made that header smaller for the first time in 13 years. I ran JOL (Java Object Layout) on the same Point(int x, int y) record on Java 21 and Java 25. Here is what came back: Java 21 → 24 bytes Java 25 → 16 bytes At 1 million objects that is 8 MB freed. At the allocation rates of a typical Spring Boot service, that is measurable GC pressure gone. The article walks through the actual JOL output byte by byte — the header tax, how it works, why it took 13 years to fix, and what it means if you are running services on AWS or Kubernetes. #Java #Java25 #JVM #SpringBoot #BackendDevelopment #SoftwareEngineering #Performance

Recently, while working on a backend application in Java, I encountered a common scalability issue. Even with thread pools in place, the system struggled under high load, particularly during multiple external API and database calls. Most threads were waiting but still consuming resources. While multithreading in Java is crucial for developing scalable backend systems, it often introduces complexity, from managing thread pools to handling synchronization. The introduction of Virtual Threads (Project Loom) in Java is changing the landscape. Here’s a simple breakdown: - Traditional Threads (Platform Threads) - Backed by OS threads - Expensive to create and manage - Limited scalability - Requires careful thread pool tuning - Virtual Threads (Lightweight Threads) - Managed by the JVM - Extremely lightweight (can scale to millions) - Ideal for I/O-bound tasks (API calls, DB operations) - Reduces the need for complex thread pool management Why this matters: In most backend systems, threads spend a lot of time waiting during I/O operations. With platform threads, resources get blocked, while with virtual threads, blocking becomes cheap. This leads to: - Better scalability - Simpler code (more readable, less callback-heavy) - Improved resource utilization When to use what? - Virtual Threads → I/O-heavy, high-concurrency applications - Platform Threads → CPU-intensive workloads Virtual Threads are not just a performance improvement; they simplify our approach to concurrency in Java. This feels like a significant shift for backend development. #Java #Multithreading #Concurrency #BackendDevelopment #SoftwareEngineering