GraalVM Reachability Metadata v0.3.19: Kafka support

⚡ Java 21 Virtual Threads in real APIs Swapped a blocking fan-out (DB + 2 downstream calls) to virtual threads—same code style, way more concurrency, fewer timeouts. Why it works: I/O-heavy workloads, simpler thread management, smoother bursts. Tip: keep timeouts/back-pressure; CPU-bound stays on platform threads. #Java #Java21 #VirtualThreads #SpringBoot #Performance #Concurrency 🚀

On Reactive Programming (Highlights WebFlux & Kafka) Showcase deep technical expertise in a core skill. One of the most powerful shifts in modern backend development is the synergy between reactive frameworks like Spring WebFlux and event-streaming platforms like Kafka. It's more than just a trend; it's a new paradigm for building truly scalable systems. WebFlux provides the non-blocking foundation to handle I/O efficiently, while Kafka offers a durable, high-throughput message backbone. Combining them allows us to build services that are not only incredibly responsive under load but also resilient and decoupled. This architecture is a game-changer for high-performance financial and real-time data applications. How have you combined reactive frameworks with event streaming in your projects? #Java #SpringWebFlux #Kafka #EventDrivenArchitecture #Microservices #SoftwareArchitecture"

Oracle is ending GraalVM support after JDK 24. The visual below compares key platforms such as vanilla OpenJDK, Azul Platform Prime, GraalVM & Semeru — across JDK features, latency, and cloud-readiness. Take a look at your options: java.azul.com/3J3PuY7 #Java #GraalVM

Oracle is ending GraalVM support after JDK 24. The visual below compares key platforms such as vanilla OpenJDK, Azul Platform Prime, GraalVM & Semeru — across JDK features, latency, and cloud-readiness. Take a look at your options: java.azul.com/3J3PuY7 #Java #GraalVM

🚀 Traditional Threads vs Virtual Threads in Java 21 — Rethinking Concurrency For decades, Java developers have dealt with the limitations of platform threads: 🧱 high memory footprint, ⚡ costly context switches, and 🔧 complex thread pool tuning. These issues often force compromises between scalability and simplicity. Enter Virtual Threads (Java 21) — lightweight, user-mode threads that fundamentally change the concurrency landscape: 💥 Massive scalability: Spin up millions of virtual threads without exhausting memory. ⚡ Efficient context switching: Managed by the JVM, not the OS, dramatically reducing overhead. 🧩 Simplified I/O-bound design: No more callback hell or reactive boilerplate; blocking I/O no longer blocks the OS thread. 🔗 Seamless integration: Works with existing synchronous APIs and frameworks — thread-per-task becomes practical again. 🛠️ Simpler architecture: Less boilerplate, higher throughput, and improved maintainability. With virtual threads, we can rethink architecture: 🧠 simpler code, 💨 higher performance, and 📈 better scalability without sacrificing reliability. If you’re building high-concurrency systems, it’s time to evaluate the impact of virtual threads on your design patterns and scalability strategies. #Java21 #VirtualThreads #Concurrency #JVM #HighPerformance #SoftwareArchitecture #Java #Scalability

Oracle is reshaping GraalVM’s future With the release of GraalVM for JDK 25, Oracle is introducing new native image features while shifting the platform’s long-term focus away from Java toward languages like GraalPy and GraalJS. Highlights: - Enhanced Foreign Function & Memory (FFM) API support - Early optimizations from the Vector API - Graal JIT compiler discontinued after JDK 24 - Native image work moving under OpenJDK’s Project Loom 👉 What does this pivot mean for Java developers and the future of GraalVM? https://lnkd.in/ey9S-NFV #GraalVM #JDK #Java

💡 Rethinking Concurrency: Lessons from Using Java 21 Virtual Threads We recently upgraded one of our Spring Boot services to Java 21, excited to leverage virtual threads for lightweight and scalable concurrency. Everything worked smoothly — until production faced a real-world spike. Within just 5 minutes, a few lakh events arrived to be processed. The database remained stable, and CPU usage stayed normal, yet we observed a few lost events due to the overwhelming concurrency. The reason? Virtual threads made it too easy to process everything in parallel — without backpressure or rate control, our service pushed a massive number of concurrent DB calls at once. As an immediate fix, we switched back to a traditional ExecutorService and added backpressure at the service level (not at the DB). This stabilized processing and restored reliability. 🧠 Key lessons learned: New features should be adopted intentionally, not just because they’re modern or exciting. Virtual threads are powerful, but unbounded concurrency can lead to logical overload, even if CPU and DB metrics look fine. ✅ How we could have used virtual threads more safely: Apply bounded concurrency using limited scheduler. Introduce rate-limiting or backpressure on the RabbitMQ listener. Batch DB operations instead of firing one query per event. Tune DB connection pool limits according to workload. Configure Dead Letter Queues (DLQs) for safe retries. Virtual threads aren’t a silver bullet — they’re a precision tool. With proper boundaries and flow control, they can unlock huge performance gains without compromising reliability. #Java21 #VirtualThreads #SpringBoot #Concurrency #Scalability #RabbitMQ #ProductionLearnings #EngineeringExcellence

💡 Rethinking Concurrency: Lessons from Using Java 21 Virtual Threads We recently upgraded one of our Spring Boot services to Java 21, excited to leverage virtual threads for lightweight and scalable concurrency. Everything worked smoothly — until production faced a real-world spike. Within just 5 minutes, a few lakh events arrived to be processed. The database remained stable, and CPU usage stayed normal, yet we observed a few lost events due to the overwhelming concurrency. The reason? Virtual threads made it too easy to process everything in parallel — without backpressure or rate control, our service pushed a massive number of concurrent DB calls at once. As an immediate fix, we switched back to a traditional ExecutorService and added backpressure at the service level (not at the DB). This stabilized processing and restored reliability. 🧠 Key lessons learned: New features should be adopted intentionally, not just because they’re modern or exciting. Virtual threads are powerful, but unbounded concurrency can lead to logical overload, even if CPU and DB metrics look fine. ✅ How we could have used virtual threads more safely: Apply bounded concurrency using limited scheduler. Introduce rate-limiting or backpressure on the RabbitMQ listener. Batch DB operations instead of firing one query per event. Tune DB connection pool limits according to workload. Configure Dead Letter Queues (DLQs) for safe retries. Virtual threads aren’t a silver bullet — they’re a precision tool. With proper boundaries and flow control, they can unlock huge performance gains without compromising reliability. #Java21 #VirtualThreads #SpringBoot #Concurrency #Scalability #RabbitMQ #ProductionLearnings #EngineeringExcellence

Recently explored Spring WebFlux – a reactive and non-blocking framework built on top of Reactor and powered by Netty’s event-loop model. Key highlights I learned: ✅ Uses event loops instead of one-thread-per-request model ✅ Non-blocking I/O → better scalability ✅ Reactive Streams & Backpressure support ✅ Ideal for high-performance microservices Really excited to apply this in real-world projects! 💻⚡ #SpringBoot #WebFlux #Java #Netty #ReactiveProgramming