Java 25 Improves Performance and Productivity

I’ve been exploring some of the features introduced in Java 25 recently, and it’s interesting to see how the language continues to evolve toward better performance and developer productivity. What stands out to me: - Continued focus on JVM performance and scalability - Improvements that simplify complex code patterns - Enhancements that align well with modern microservices architectures In real-world systems, especially when working with distributed services and high-throughput applications, even small improvements at the language/runtime level can have a noticeable impact. Curious to hear — are you already using Java 25 in production, or still evaluating? #Java #Java25 #Microservices #BackendDevelopment #SoftwareEngineering

🔥 After 9 years of Java development, here's the #1 insight I wish I had on Day 1: The JVM is your best friend — if you understand it. Most devs write Java for years without ever looking at: → How the Garbage Collector actually works → What happens during class loading → Why JIT compilation changes everything at runtime After nearly a decade, I can tell you: every major performance bug I've solved came down to JVM internals. ✅ Learn G1GC vs ZGC vs Shenandoah ✅ Use -XX flags to tune heap size and GC behavior ✅ Read GC logs — they tell you the whole story You don't need to be a JVM engineer. But you DO need to know what's happening under the hood. What JVM concept changed how you write Java? Drop it below 👇 #Java #JVM #SoftwareDevelopment #BackendDevelopment #JavaDeveloper

🚀 Day 1 – Strengthening Java Fundamentals Starting with something simple but powerful: How Java Works Behind the Scenes When we write a Java program, it doesn’t directly run on the machine. Instead: 👉 Java code → compiled into Bytecode 👉 Bytecode → executed by the JVM (Java Virtual Machine) Why this matters? Because this is what makes Java platform independent — “Write Once, Run Anywhere.” Also, JVM doesn’t just run code — it handles: ✔ Memory Management (Garbage Collection) ✔ Security ✔ Performance optimization Understanding this foundation helps in writing better, optimized applications—especially when working with frameworks like Spring Boot. #Java #BackendDevelopment #LearningInPublic #JVM #SoftwareEngineering

𝗨𝗽𝗴𝗿𝗮𝗱𝗶𝗻𝗴 𝗝𝗮𝘃𝗮 𝗜𝘀 𝗘𝗮𝘀𝘆. 𝗨𝗽𝗴𝗿𝗮𝗱𝗶𝗻𝗴 𝗛𝗼𝘄 𝗬𝗼𝘂 𝗪𝗿𝗶𝘁𝗲 𝗝𝗮𝘃𝗮 𝗜𝘀 𝗛𝗮𝗿𝗱𝗲𝗿. 𝗠𝗮𝗻𝘆 𝘁𝗲𝗮𝗺𝘀 𝗽𝗿𝗼𝘂𝗱𝗹𝘆 𝘀𝗮𝘆: ✔ We moved to Java 17 ✔ We’re now on Java 21 ✔ Planning Java 25 next That’s great. But the bigger question is: Did the code actually evolve too? A lot of projects run on the latest Java version while still being written with an old Java 8 mindset. 𝗠𝗼𝗱𝗲𝗿𝗻 𝗝𝗮𝘃𝗮 𝗴𝗶𝘃𝗲𝘀 𝘂𝘀: 🚀 Records for cleaner data models 🔒 Sealed classes for safer hierarchies 🧠 Pattern matching for better readability ⚡ Virtual threads for simpler concurrency 📦 Gatherers for smarter stream pipelines The real value of upgrading Java is not the version number. It’s adopting the new ways of expressing intent. Otherwise, it’s just old design running on a newer JDK. What modern Java feature changed how you write code the most? #Java #ModernJava #Java21 #Java25 #BackendDevelopment #SoftwareEngineering

Recently watched a session by Ben Evans (GOTO, available on YouTube) on the State of Java — found it quite insightful. A few points that stood out for me: - The comparison of Java 8 as the “XP of Java” vs Java 17 as the modern LTS baseline - Also touched on the evolving ecosystem — Spring and Quarkus growing together, along with tools like OpenTelemetry, Kafka, and Spark shaping modern Java applications - Continued focus on performance and concurrency improvements, keeping Java relevant at scale - Insights from New Relic data showing Java’s strong and sustained usage in production systems - How Java is still evolving to align with modern workloads, including AI-driven systems Nice reminder that Java isn’t just legacy — it’s steadily adapting to new demands. Thanks to @Benand GOTO for sharing the session. #Java #SoftwareEngineering #Backend #Learning https://lnkd.in/gj9d7UBu

Day 10 of my Java Streams practice focused on solving a classic problem—finding all anagrams of a given word. The approach is based on a simple observation: two words are anagrams if they contain the same characters in the same frequency. By converting each word into a stream of characters, sorting them, and comparing the result with the sorted version of the target word, we can identify matching anagrams efficiently. This exercise helped strengthen my understanding of working with streams, transforming data, and applying comparison logic in a functional style. It also reinforced how breaking a problem into smaller transformations can lead to clean and readable solutions. #Java #JavaStreams #DSA #CodingJourney #BackendDevelopment #100DaysOfCode

Java 25 is shaping up to be a very compelling LTS release. From Scoped Values and Structured Concurrency to runtime and JVM improvements, there’s a lot here for teams building modern distributed systems. I put together a breakdown of the features I think matter most in practice — not just what’s new, but why it matters. Would be curious what others are most excited about in Java 25. https://lnkd.in/epgszT4Q #Java25 #Java #JVM #SoftwareEngineering #CloudNative

The Latest Java Versions Are Quietly Changing How We Design Systems For years, Java upgrades mostly felt like: ✔ performance improvements ✔ syntax polish ✔ library updates But recent versions are doing something bigger. They are changing how we think about design. 🔹 Records reduce accidental mutability 🔹 Sealed classes make boundaries explicit 🔹 Pattern matching improves type-driven logic 🔹 Virtual threads simplify concurrency models These are not just language features. They shape architecture decisions. The biggest shift is this 👇 Modern Java is helping developers write code that is: • clearer • safer • easier to reason about • more scalable under real load The language is becoming more expressive, which means better design can now be written more naturally. Java upgrades are no longer only about speed. They are about better software design choices. Which recent Java feature changed the way you design code? #Java #ModernJava #Java21 #Java25 #SoftwareEngineering #BackendDevelopment

#Day02 After understanding how Java code gets executed, the next question is: 👉 Where does the data actually get stored? In JVM, memory is mainly divided into two parts: 🔹 Heap Memory • Used to store objects and class instances • Shared across all threads • Managed by Garbage Collection • Objects generally have longer lifetime 🔹 Stack Memory • Stores method calls and local variables • Each thread has its own stack • Automatically managed • Data exists only during method execution 📌 Key difference: Heap → Stores Objects Stack → Handles Execution (methods & variables) Understanding this difference helps in writing better and more efficient Java applications. #Java #JVM #BackendDevelopment #Learning